mcp-bastion-python 2.0.1

Security middleware for MCP servers protecting LLM agents from prompt injection, resource exhaustion, and PII leakage

MCP-Bastion

The Zero-Trust control plane for MCP agents. Your agent can call databases, APIs, and shell tools. One bad prompt can leak PII; one runaway loop can burn your API budget in minutes; three agents on one server with no identity boundary is a confused-deputy incident waiting to happen. MCP-Bastion wraps your MCP server with local guardrails: agent IAM, supply-chain checksums, injection blocking, PII redaction, and denial-of-wallet caps, under 5ms overhead, with no third-party safety API.

Guiding rule: Stay a zero-infra, drop-in library - the guardrail brain that composes with any gateway, not a gateway itself. Strategy: docs/ZERO_INFRA_STRATEGY.md.

Why MCP-Bastion? (Solving the 2026 MCP Security Crisis)

As noted in the NSA's recent Cybersecurity Information Sheet on MCP security and the OWASP MCP Top 10, traditional AppSec tools cannot secure agentic workflows. The gap is runtime governance and the confused deputy problem: multiple AI agents sharing one MCP server with no native identity boundary. Public registry typosquatting and unverified servers have made supply-chain verification a board-level concern.

MCP-Bastion acts as the Zero-Trust Control Plane for your agents, addressing the hardest production problems:

1. The Confused Deputy (Agent IAM): Identity-aware routing binds API tokens to Agent Identities and enforces strict per-tool RBAC. Your customer-support bot can call search_docs, not delete_user.
2. Supply chain & typosquatting defense: Cryptographic SHA-256 manifest verification blocks traffic when MCP server artifacts drift from your signed-off checksums.
3. Data exfiltration & injection prevention: PromptGuard heuristics + ML block jailbreaks locally; Presidio scrubs outbound PII before it hits a model context window.

Define your agent policies (bastion.yaml)

# Stop the Confused Deputy Problem  -  Identity-Aware Routing
agent_iam:
  enabled: true
  token_metadata_key: bastion_agent_token
  agents:
    - id: customer_support_bot
      token_env: BASTION_TOKEN_SUPPORT
      allowed_tools: ["search_docs", "get_ticket_status"]
      blocked_tools: ["execute_sql", "delete_user"]
      rate_limit:
        max_iterations: 5

# Supply-chain checksums before any tool executes
server_verification:
  enabled: true
  on_mismatch: block
  base_path: .
  manifest_path: mcp-server.manifest.json

Generate a manifest after a trusted build: mcp-bastion manifest server.py pyproject.toml -o mcp-server.manifest.json

Deep dive: docs/RUNTIME_GOVERNANCE.md · docs/ROADMAP.md (future 3.0+ plan)

Full MCP surface + horizontal scale (2.0.0)

Previously, most pillars ran only on tools/call. 2.0.0 extends the pipeline to resources/read, prompts/get, sampling/createMessage, and elicitation/create - closing exfil/injection gaps on the rest of the MCP surface.

For multi-replica deployments, enable state_backend.type: redis so rate limits, replay nonces, cost budgets, and session tool scope are shared across pods (default memory is single-process).

state_backend:
  type: redis
  redis_url: redis://127.0.0.1:6379/0

pip install mcp-bastion-python[redis] · Deep dive: docs/MCP_SURFACE_AND_SCALE.md

Production hardening adopted in 2.0.0

Battle-tested patterns from the broader MCP gateway ecosystem, wired into the middleware stack:

Feature	What you get
JSONPath argument guards	Block or redact tool arguments by tool glob + JSONPath + regex before execution (argv-array evasion aware). pip install mcp-bastion-python[policy]
RBAC fnmatch globs	Role permissions like read_* / files_* with specificity-aware matching
Audit JSONL + mcp-bastion tail	Append-only compliance log; audit.jsonl_path in config or mcp-bastion tail -p audit.jsonl
Cost checkpoint	Optional disk persistence for session totals across restarts (cost_tracker.checkpoint_path, memory backend only)
Cost-aware policy (cost_policy)	Live spend rules: degrade model, force discovery filter, require approval; expensive-chain blocking
Governance attestation	mcp-bastion attest export --session … - signed session bundle with policy hash + controls fired
Boundary mode	Mandatory proxy auth on every request (boundary_mode + edge_auth / agent_iam) - GATEWAY_BOUNDARY.md
Ungated PromptGuard	prompt_guard.use_ungated_default: true → ProtectAI DeBERTa classifier (no HF gate)

cost_policy:
  enabled: true
  rules:
    - when: { session_spend_pct_gte: 80 }
      action: degrade_model
      target_model: gpt-4o-mini
    - when: { session_spend_pct_gte: 95 }
      action: require_approval
  expensive_chain:
    enabled: true
    max_projected_cost_usd: 1.0

governance:
  attestation_enabled: true

boundary_mode:
  enabled: true   # requires edge_auth or agent_iam

argument_guards:
  enabled: true
  rules:
    - name: block_shell
      match: "run_*"
      arg: "$.command"
      pattern: "(rm\\s+-rf|curl\\s+.*\\|.*sh)"
      action: block

audit:
  jsonl_path: .bastion/audit.jsonl

cost_tracker:
  checkpoint_path: .bastion/cost-checkpoint.json

Why developers adopt it

You need…	MCP-Bastion gives you…
Guardrails without a rewrite	Drop-in middleware: secure_fastmcp(mcp) or one bastion.yaml
Privacy your legal team accepts	PromptGuard + Presidio run in your process; data stays on your network
Stop runaway agents & budget burn	On by default: 15 tool calls/session, 60s timeout, 50k token budget. Optional: per-tool caps, USD session/day limits, response offload
Shrink context & cut token spend	Opt-in: discovery filter (fewer tools in tools/list), output budget + session offload (up to ~99% on oversized tool outputs), lexical similarity cache - measured benchmarks
Something that ships today	PyPI, npm, Docker on GHCR, FastMCP, TypeScript wrapper, CI validate, live dashboard
Policy your team can review	bastion.yaml in Git, hot reload, OWASP-aligned controls (docs/PILLARS.md)

FinOps & abuse protection (denial-of-wallet)

Agents can loop on expensive tools (search, LLM calls, paid APIs) until your bill spikes. Bastion enforces session-level FinOps at the MCP boundary before each tools/call:

Attack pattern	What Bastion does	Default
Infinite tool loop	Blocks after max iterations per session	On (15 calls)
Long-running session abuse	Session timeout	On (60s)
Token / context budget burn	Token budget per session; optional output offload	On (50k tokens); offload opt-in
Same tool hammered	Per-tool call cap (max_per_tool)	Opt-in
Paid API spend runaway	USD caps via cost tracker	Opt-in
Flaky or hostile tool cascade	Circuit breaker opens after failures	Opt-in in example config
Tool sprawl in one session	Cap distinct tools per session	Opt-in

Blocked calls return standard errors (RateLimitExceededError -32002, TokenBudgetExceededError -32003, CostBudgetExceededError -32009) and show up in the dashboard and audit log. See docs/ATTACK_PREVENTION.md.

Token reduction & cost saving

Bastion does not only block runaway spend - it reduces how much tool output and tool-catalog tokens reach the model on each turn (not the user’s LLM prompt text itself):

Savings lever	What it does	Default
Discovery filter	Hides unused tools from tools/list so agents carry a smaller tool catalog in context (~85% fewer catalog tokens in benchmarks with 20→3 tools)	Opt-in
Output budget + offload	Truncates oversized tool responses; stores the rest in-session for bastion_get_offloaded (up to ~99.7% on 50k-token dumps; 0% when already under budget)	Opt-in
Lexical similarity cache	Skips redundant tool calls when queries are near-identical (Jaccard word overlap - not embedding “semantic” search)	Opt-in
Token budget caps	Hard stop before session token burn exceeds your limit	On (50k tokens)
USD session/day limits	Dollar ceilings via cost tracker	Opt-in

There is no honest single “X% prompt reduction” figure - savings are input-dependent. See docs/BENCHMARKS.md for reproducible pytest benchmarks and live numbers.

_{Reproduce: PYTHONPATH=src python -m pytest tests/test_benchmarks_finops_rbac.py -v · Regenerate report: python scripts/generate_benchmark_report.py}

Less tool output and catalog noise per turn means lower LLM input cost - without sending prompts to a third-party optimizer API.

Bottom line: MCP turned every server into an agent gateway overnight. Bastion is the firewall that makes that gateway safe to run in production - in three lines of code or one config file.

OWASP MCP Top 10 + production attacks

All 10 OWASP MCP Top 10 risks are mitigated at the MCP boundary (see controls below). Bastion also blocks FinOps and abuse patterns that OWASP does not list separately.

OWASP MCP Top 10 (all addressed)

ID	Risk	Bastion controls
MCP01	Token / secret exposure	PII redaction, audit trail, outbound response scan
MCP02	Privilege escalation	RBAC, agent IAM, rate limits, cost caps, session tool scope
MCP03	Tool poisoning	Prompt guard, content filter, response scan, metadata guard, grounding guard
MCP04	Supply chain	Circuit breaker, server_verification checksums, doctor CLI, mcp-bastion manifest, audit
MCP05	Command injection	Prompt guard, content filter, schema validation
MCP06	Intent subversion	Rate limits, replay guard, per-tool caps, semantic firewall
MCP07	Weak authentication	RBAC, edge auth, agent IAM (per-agent tokens)
MCP08	Audit & telemetry	Audit log, dashboard, Prometheus, OTEL, alerts
MCP09	Shadow MCP servers	Central bastion.yaml policy, metrics, discovery filter
MCP10	Context injection	PII redaction, response scan, output budget, discovery filter

FinOps & abuse attacks (beyond OWASP)

Attack	Controls
Denial of wallet	Iteration cap, token budget, cost tracker, output budget
Runaway tool loops	Session timeout, rate limiter, circuit breaker
Per-tool hammering	max_per_tool session caps
API spend runaway	USD session/day caps
Session tool sprawl	Distinct-tool limit per session
Replay abuse	Replay guard + nonces

Token reduction & cost saving

Lever	Controls	Benchmark
Smaller tool catalog in context	Discovery filter on tools/list	~85% catalog tokens (20→3 tools) - BENCHMARKS.md
Less tool output in every turn	Output budget, session offload, bastion_get_offloaded	Up to ~99.7% on oversized dumps; 0% when under budget
Fewer redundant calls	Lexical similarity cache (Jaccard overlap)	Exact repeat hits; paraphrase misses at 0.9
Predictable spend	Token budget caps, USD session/day limits	Session defaults on

Deep-dive mapping and integration hooks: docs/SECURITY_OBSERVABILITY.md · docs/ATTACK_PREVENTION.md

Secure your MCP server in 3 lines (FastMCP)

pip install mcp mcp-bastion-fastmcp

from mcp.server.fastmcp import FastMCP
from mcp_bastion_fastmcp import secure_fastmcp

mcp = FastMCP("My Server")
secure_fastmcp(mcp)  # wires prompt guard, PII redaction, rate limits into tools/call

Policy-as-code instead? Copy bastion.yaml.example → bastion.yaml, then pip install mcp-bastion-python[policy]:

from mcp_bastion import build_middleware_from_config

middleware = build_middleware_from_config()  # loads bastion.yaml

More paths (TypeScript, CI validate, Docker): docs/QUICK_START.md · docs/README.md · website

• Prompt injection defense: Heuristic jailbreak blocking out of the box; Meta PromptGuard ML when Hugging Face access is configured.
• PII redaction: Presidio masks SSN, email, phone in outbound content.
• Denial-of-wallet protection: Token buckets, iteration caps, token budget, cost tracking.
• Response scan: Blocks jailbreak patterns in outbound tool/resource text.
• Output budget & grounding guard: Optional response truncation and path verification (opt-in).

How it works

MCP-Bastion sits in-process on your MCP server and inspects every tools/call before it reaches databases, APIs, or shell tools - then redacts sensitive data on the way back.

flowchart LR
  Agent["AI agent / LLM client"]
  Server["Your MCP server"]
  Bastion["MCP-Bastion<br/>middleware"]
  Tools["Tools & upstream APIs"]

  Agent -->|"JSON-RPC"| Server
  Server --> Bastion
  Bastion -->|"✓ allow / ✗ block"| Tools
  Tools -->|"raw result"| Bastion
  Bastion -->|"PII masked · audited"| Server
  Server --> Agent

Three ways to adopt

flowchart TB
  Start(["Protect my MCP server"])
  Start --> FastMCP["FastMCP · Python<br/><code>secure_fastmcp(mcp)</code>"]
  Start --> Policy["Policy-as-code<br/><code>build_middleware_from_config()</code>"]
  Start --> TS["TypeScript<br/><code>wrapWithMcpBastion(server)</code>"]
  FastMCP --> Docs["docs/QUICK_START.md · path A"]
  Policy --> Yaml["bastion.yaml + CI validate"]
  TS --> Sidecar["Rate limit in-process · ML via sidecar"]

Releases: npm, PyPI, and prebuilt Docker on GHCR - see DOCKER.md. Community: SUPPORT.md · CONTRIBUTING.md · FUNDING.md · Security: SECURITY.md.

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Core Features

Zero-Click Prompt Injection Prevention

Integrates Meta's PromptGuard model locally to detect and block malicious payloads, jailbreaks, and adversarial tokenization before they reach your external tools.

PII Redaction

Microsoft Presidio scans outbound tool results and masks PII (redaction, substitution, generalization).

Infinite Loop and Denial of Wallet Protection

Implements stateful cycle detection and configurable FinOps token-bucket algorithms to automatically terminate runaway agents and prevent massive API bill overruns.

100% Local Execution (Data Privacy)

All security classification and data redaction happen entirely within the local memory space of your server. Sensitive data never leaves your enterprise network for third-party safety evaluations.

Low Latency

Drop-in middleware, under 5ms overhead.

Framework Integration

Hooks into MCP SDKs (TypeScript, Python) and FastMCP via standard middleware. No business logic changes.

Complete feature catalog

Pillar definitions: Security controls, bastion.yaml sections, and how they relate to dashboard health rows are documented in docs/PILLARS.md (canonical reference; avoids ambiguous “total pillar” counts). The same page lists extended features restored in 1.0.16+ (semantic firewall, sensitive classifier, external policy, edge auth, tool allowlist, session scope, tool metadata guard, multi-tenant, audit hash chain, pricing hooks, telemetry sinks, red team and doctor CLIs, etc.), FinOps/context pillars in 1.0.17+ (output budget, discovery filter, response scan, grounding guard), and runtime governance (agent IAM, server verification - introduced in 1.0.18+, shipped in 2.0.0).

Deeper context: docs/SECURITY_OBSERVABILITY.md - OWASP MCP Top 10 alignment, attack scenarios, and SIEM/log integrations. Framework add-ons (LangChain, OpenAI, Bedrock, …) are listed under Framework Integrations below.

Threat prevention & content safety

Feature	What you get
Prompt injection defense	Meta PromptGuard scores tool arguments; malicious / jailbreak-style payloads can be blocked before execution (local inference, no third-party API).
Content filter	Block shell/code execution patterns, sensitive file paths, and URLs; optional allowlist / denylist regex or substring rules.
PII redaction	Microsoft Presidio detects many entity types in outbound tool/resource text (SSN, email, phone, cards, passport, IBAN, licenses, etc. - see Presidio docs).

Access control, integrity & abuse

Feature	What you get
Agent IAM (Confused Deputy)	Bind API tokens to agent identities; per-agent allowed_tools / blocked_tools, resource URI allow/block, optional rate limits - stops a support bot from calling admin tools or reading secret resources. See docs/RUNTIME_GOVERNANCE.md.
Full MCP surface guards (2.0.0)	resources/read, prompts/get, sampling/createMessage, elicitation/create - same inbound/outbound pillars as tool calls (not only tools/call). docs/MCP_SURFACE_AND_SCALE.md
Distributed state (2.0.0)	state_backend: redis - shared rate limits, replay nonces, cost caps, session scope across replicas. pip install mcp-bastion-python[redis]
Server verification (supply chain)	SHA-256 manifest checksums verified at startup and on every tools/call; mcp-bastion manifest generates trusted manifests after a signed-off build.
RBAC	Tool-level allow/deny by role (from request metadata); fnmatch globs (read_*) with specificity-aware matching in bastion.yaml. Pair with Agent IAM or edge auth - alone, roles are only as trustworthy as whatever sets metadata["role"]. Live matrix →
Argument guards (2.0.0)	JSONPath + regex block/redact on tools/call arguments before schema validation - stops shell injection and secret exfil in argv-style payloads.
Schema validation	Validate tools/call arguments against JSON Schema before the tool runs (block malformed or bypass attempts).
Replay guard	Nonce tracking to reject replayed requests (configurable require_nonce).
Rate limiting	Token-bucket style limits: max iterations per session, timeout, token budget - stops runaway loops and brute-force patterns.
Circuit breaker	Stop calling tools that fail repeatedly (limits blast radius of bad upstreams or poisoned tools).

FinOps & performance

Feature	What you get
Cost tracker	Per-session and optional per-day USD caps; blocks when budget is exceeded. Optional disk checkpoint for restart-safe totals (memory backend).
Semantic cache (lexical)	Optional Jaccard word-overlap cache for near-identical tool queries - not embedding-based; see benchmarks.
Low overhead	Middleware on the hot path targeting <5 ms typical overhead (see docs/METRICS.md).

Audit, metrics & alerting

Feature	What you get
Audit logging	Structured allow/deny decisions with reason, tool, tenant_id, trace_id, request_id - feed SOC / compliance. Optional JSONL file sink + mcp-bastion tail.
Alert sinks	Slack incoming webhook; generic HTTP webhooks (PagerDuty, Teams, custom APIs); multiple URLs; retry, backoff, timeout in bastion.yaml.
In-memory metrics	Global MetricsStore: requests, blocks, PII counts, cost, per-tool stats, latency samples, rolling time series buckets.
Real-time dashboard	Web UI with a top KPI summary (totals, block %, top threat, active users/tenants), traffic & block charts, blocked-by-reason/kind (with readable reasons / tooltips), PII by entity (severity-style coloring, e.g. high-risk types emphasized), top tools, cost by user, latency P50/P95/P99, forensics table (tenant filter, trace/replay helpers), recent alerts, insights & anomalies (heuristic signals), dark/light theme, Prometheus /metrics, JSON /api/metrics, loading/empty guidance instead of a blank first paint.
OpenTelemetry	Optional OTLP span export - pip install mcp-bastion-python[otel] - docs/OTEL.md.

Policy, packaging & developer experience

Feature	What you get
Policy-as-code	Single bastion.yaml: toggles for all request-path controls plus audit, alerts, and hot reload (docs/PILLARS.md); load via load_config / build_middleware_from_config.
Hot reload	Optional reload bastion.yaml on change without restarting the MCP server (docs/POLICY_AS_CODE.md).
Composable middleware	compose_middleware ordering; MCPBastionMiddleware flags for each pillar.
CLI	mcp-bastion validate, manifest, attest export, serve, dashboard, redteam, doctor, tail - docs/CLI.md.
Python + TypeScript	mcp-bastion-python on PyPI; @mcp-bastion/core on npm for TypeScript MCP servers (rate limits in-process; prompt/PII via optional sidecar).
Containers	Dockerfile, docker-compose profiles (proxy + optional dashboard) - DOCKER.md. Prebuilt images (GHCR): mcp-bastion-proxy, mcp-bastion-dashboard - published on each v* tag (publish-docker.yml).

Real-Time Dashboard and Alerts

🎥 Demo (screen recording): Watch on Vimeo - overview of the dashboard and metrics (link opens the player on Vimeo).

_{Click the screenshot for the video demo · Seed demo data: mcp-bastion dashboard --demo}

Run the optional dashboard for a live view of requests, blocked count, PII redacted, cost, top tools, and recent alerts.

mcp-bastion dashboard --port 7000
# or: PYTHONPATH=src python dashboard/app.py

URL	What it returns
http://localhost:7000/	Charts, KPIs, forensics, insights & anomalies, alerts, tool drill-down (signal vs global block rate), theme toggle
http://localhost:7000/api/metrics	JSON: requests_total, blocked_total, blocked_pct, pii_redacted_total, cost_total, blocked_by_reason, blocked_by_kind, top_tools, tool_stats, cost_by_user, time_series, latency_ms, dashboard_insights, blocked_incidents, alerts, …
http://localhost:7000/api/health	{"status": "ok"}
http://localhost:7000/metrics	Prometheus text format for Grafana/Datadog

_{/api/metrics JSON for Grafana, Datadog, or custom pollers}

Dashboard: total requests, blocked count and %, PII redacted, cost; blocked-by-reason bars; top tools; cost by user; recent alerts - open http://localhost:7000/ while mcp-bastion dashboard is running.

• Alerts: Slack webhook and cost-threshold alerts. See dashboard/README.md.

Documentation: Use Cases, Attacks, Metrics, Tutorials

Adoption paths (start-to-finish):

Goal	Read in order
Policy-as-code (bastion.yaml)	docs/PILLARS.md → docs/POLICY_AS_CODE.md → bastion.yaml.example → docs/CLI.md (validate)
LLM clients (OpenAI, Claude, Gemini, …)	docs/LLM_INTEGRATION.md → docs/INTEGRATION_MODELS.md → examples/ (llm_*.py)
FastMCP / TypeScript / third-party MCP	docs/TUTORIALS.md → docs/DETAILED_TUTORIAL.md
Fleet rollout of bastion.yaml + SIEM / SOC audit	docs/SECURITY_OBSERVABILITY.md → docs/POLICY_AS_CODE.md
Minimal “hello world” + CI / registries	docs/QUICK_START.md → examples/ci/README.md → docs/DISCOVERY.md

Full index: docs/README.md (docs hub) · published site entry: docs/index.md · quick wrap: docs/QUICK_START.md · discovery: docs/DISCOVERY.md · contribute: CONTRIBUTING.md.

Doc	Description
docs/index.md	GitHub Pages-ready docs home
docs/POLICY_AS_CODE.md	bastion.yaml reference: keys, examples, hot reload, alerts
docs/LLM_INTEGRATION.md	LLM integration: OpenAI, Claude, Gemini, Mistral, Grok (stdio + HTTP configs)
docs/DETAILED_TUTORIAL.md	Step-by-step implementation tutorial for new teams
docs/USE_CASES.md	Real use cases: enterprise gateway, LLM products, internal tools, SaaS, compliance
docs/ATTACK_PREVENTION.md	Examples showing how MCP-Bastion prevents real attacks (injection, PII leak, rate exhaustion, path traversal, RBAC, replay)
docs/PILLARS.md	Canonical pillar counts: 18 request-path features (10 core + 8 extended), 14 dashboard pillar_health rows, 20+ bastion.yaml top-level areas - see the doc for scope
docs/SUPPLY_CHAIN.md	CI merge gates, releases, npm provenance, PyPI Trusted Publishing
docs/INTEGRATION_MODELS.md	Middleware + bastion.yaml vs “change base URL”; bridge for Python, TS, Desktop, HTTP, integrations
examples/ci/README.md	Copy-paste GitHub Actions snippet to run mcp-bastion validate on your policy file
docs/BENCHMARKS.md	Measured RBAC matrix, output-budget reduction (up to ~99% on large tool outputs), discovery filter, lexical cache - pytest + report generator
docs/REDTEAM.md	Interpreting harness / red-team scores; which bastion.yaml pillars to enable; Node vs Python scope (packages/core/README.md)
docs/SECURITY_OBSERVABILITY.md	OWASP MCP Top 10, integration hooks, fleet-scale bastion.yaml rollout, SIEM / SOC audit patterns
docs/METRICS.md	Performance overhead (<5ms) and effectiveness metrics (dashboard, Prometheus, OTEL)
docs/TUTORIALS.md	Tutorials: integrating with FastMCP, TypeScript, GitHub MCP, and open-source MCP servers
docs/GITHUB_PAGES.md	Publish docs as a GitHub Pages website from this same repo
docs/QUICK_START.md	Minimal FastMCP / bastion.yaml / CI snippets (time-to-value)
docs/DISCOVERY.md	Registry and ecosystem discovery checklist
docs/ROADMAP.md	Future roadmap (3.0+): security, identity, FinOps, discoverability, maturity
docs/COMPARISON.md	vs unguarded MCP, thin proxy, full AI/MCP gateway
docs/ENGINEERING_10_10.md	Strategic path to 10/10 on injection depth, tool poisoning, gateway maturity, FinOps metrics, project maturity
CONTRIBUTING.md	Contributor guide and good first issue ideas

One-Line Docker

Prebuilt images (after the first publish-docker run, usually on a v* release tag):

docker pull ghcr.io/vaquarkhan/mcp-bastion-proxy:v2.0.1
docker run -p 8080:8080 ghcr.io/vaquarkhan/mcp-bastion-proxy:v2.0.1
# Dashboard (optional, port 7000):
# docker pull ghcr.io/vaquarkhan/mcp-bastion-dashboard:v2.0.1
# docker run -p 7000:7000 ghcr.io/vaquarkhan/mcp-bastion-dashboard:v2.0.1
# :latest is updated on each v* tag publish

Build locally (any revision):

docker build -t mcp-bastion/proxy .
docker run -p 8080:8080 mcp-bastion/proxy

MCP endpoint: http://localhost:8080/mcp. Use docker-compose up -d for proxy; add --profile with-dashboard for the dashboard. See DOCKER.md (includes GHCR pull commands and package links for forks: replace vaquarkhan with your org or user in image paths).

Policy-as-Code (bastion.yaml)

Single config file controls policy (see docs/PILLARS.md for pillar definitions). Copy bastion.yaml.example to bastion.yaml, then:

from mcp_bastion import build_middleware_from_config
middleware = build_middleware_from_config()

See docs/POLICY_AS_CODE.md.

Tip: set hot_reload.enabled: true in bastion.yaml to apply policy changes without restarting your MCP server when using build_middleware_from_config().

CLI for developers

mcp-bastion validate              # validate bastion.yaml
mcp-bastion serve --http 8080     # run MCP server with config
mcp-bastion dashboard --port 7000 # run metrics dashboard

See docs/CLI.md.

Continuous integration (this repository)

On every pull request and push to main, .github/workflows/ci.yml runs:

1. pip install -e ".[dev,policy,dashboard]" - install the Python package with tests, YAML policy loading, and FastAPI for dashboard tests.
2. mcp-bastion validate --config bastion.yaml.example - ensure the example policy file loads.
3. python -m pytest --cov=mcp_bastion --cov-fail-under=92 - full Python test suite with ≥92% line coverage on src/mcp_bastion (see [tool.coverage.*] in pyproject.toml for measured paths and gates).
4. npm ci and npm test - TypeScript workspace tests.

To validate your repo’s bastion.yaml in CI without cloning MCP-Bastion, see examples/ci/README.md.

OpenTelemetry

Set OTEL_EXPORTER_OTLP_ENDPOINT to export tool-call spans to OTLP. Install optional deps: pip install mcp-bastion-python[otel]. See docs/OTEL.md.

Webhook alerts and external logging

Use Slack (slack_webhook / SLACK_WEBHOOK_URL), a generic HTTP webhook (webhook_url / BASTION_WEBHOOK_URL), or multiple URLs (alerts.webhooks in bastion.yaml). POSTs can drive PagerDuty, Microsoft Teams, Datadog Events, or any HTTP collector your SIEM exposes. Configure retry/backoff in bastion.yaml (retry_attempts, retry_backoff_seconds, retry_backoff_max_seconds, timeout_seconds).

Metrics & traces: scrape the dashboard /metrics (Prometheus) or poll /api/metrics (JSON) for Grafana, Datadog, or custom pollers. Set OTEL_EXPORTER_OTLP_ENDPOINT for traces to Jaeger, Honeycomb, AWS ADOT, etc. (pip install mcp-bastion-python[otel]). Route Python logs (including LoggingAlertSink) through Fluent Bit, Vector, or the CloudWatch agent into Splunk / Elastic / CloudWatch Logs.

See docs/SECURITY_OBSERVABILITY.md for the full integration table and OWASP MCP Top 10 alignment.

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Why MCP-Bastion

• Active enforcement - Intercepts MCP tool traffic so policies (prompt injection checks, PII handling, content rules, RBAC, and more) run before tools execute and before sensitive results propagate.
• Local-first classification - PromptGuard and Presidio run in your environment; you are not required to send prompts to a third-party API for guardrail scoring.
• Stateful guardrails - Per-session rate limits, iteration caps, token budgets, and cost tracking to reduce runaway loops and unexpected spend.
• Composable integration - Use bastion.yaml with build_middleware_from_config() or wire MCPBastionMiddleware / wrapWithMcpBastion in Python or TypeScript. For a separate process in front of an upstream MCP server, use a wrapper or proxy you control; see docs/INTEGRATION_MODELS.md.

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Structure

Path	Description
src/mcp_bastion/	Python package: PromptGuard, Presidio, rate limiting, RBAC, etc.
packages/core/	TypeScript package: rate limiting in-process; prompt/PII via sidecar (MCP_BASTION_URL)
examples/	Python examples (examples/README.md)
dashboard/	Real-time dashboard UI and metrics API (dashboard/README.md)
bastion.yaml.example	Policy-as-code sample; copy to bastion.yaml (docs/POLICY_AS_CODE.md)
scripts/validate_checklist.py	Enterprise validation runner
VALIDATION_CHECKLIST.md	Validation guide and MCP Inspector steps
SETUP_GUIDE.md	Setup, config, and validation
DOCKER.md	Docker one-line run and compose

Example Files

File	Purpose
examples/python_server_example.py	Minimal middleware chain
examples/full_demo.py	Multi-pillar stack (core toggles: rate limit, PII, RBAC, … - see docs/PILLARS.md)
examples/llm_server.py	Shared MCP server for LLM clients
examples/llm_openai_example.py	OpenAI
examples/llm_claude_example.py	Claude
examples/llm_gemini_example.py	Gemini
examples/llm_mistral_example.py	Mistral
examples/llm_grok_example.py	Grok (xAI)
examples/server_with_config.py	Policy-as-code (bastion.yaml)

Installation

Python

uv add mcp-bastion-python
# or
pip install mcp-bastion-python
# pinned latest
pip install mcp-bastion-python==2.0.0

Prerequisites (recommended)

• PII redaction: Presidio expects the spaCy English model. After install, run:
  python -m spacy download en_core_web_sm
  Without it, PII analysis can fail at runtime.
• Policy-as-Code (bastion.yaml): install YAML support:
  pip install mcp-bastion-python[policy]
  (adds pyyaml; otherwise you may get ImportError when loading policy files).
• Prompt injection (PromptGuard): two layers:
  1. Regex heuristics (always on) block obvious jailbreak strings such as “ignore previous instructions” - no model download required.
  2. Meta Llama Prompt Guard 2 (meta-llama/Llama-Prompt-Guard-2-86M) is a gated Hugging Face model. Request access, then run huggingface-cli login. Without ML, obvious attacks are still blocked; unverified payloads are blocked when fail_open: false (default). Run mcp-bastion doctor to verify ML availability.

The PyPI wheel ships the full mcp_bastion tree (including config, cli, otel, dashboard metrics, and alert sinks). If you use an older wheel that omits modules, upgrade to the current release.

TypeScript

npm install @mcp-bastion/core

npm

Framework Integrations

Drop-in security for your favorite LLM framework. Each package auto-installs mcp-bastion-python. Downloads for each row point to pypistats.org (trends) and pepy.tech (cumulative) for that PyPI name.

pip install mcp-bastion-langchain      # LangChain agents and tools
pip install mcp-bastion-openai         # OpenAI GPT API calls
pip install mcp-bastion-anthropic      # Anthropic Claude API calls
pip install mcp-bastion-bedrock        # AWS Bedrock runtime
pip install mcp-bastion-gemini         # Google Gemini
pip install mcp-bastion-crewai         # CrewAI agent crews
pip install mcp-bastion-llamaindex     # LlamaIndex RAG pipelines
pip install mcp-bastion-groq           # Groq inference
pip install mcp-bastion-mistral        # Mistral AI
pip install mcp-bastion-cohere         # Cohere
pip install mcp-bastion-azure          # Azure OpenAI Service
pip install mcp-bastion-vertexai       # Google Cloud Vertex AI
pip install mcp-bastion-huggingface    # Hugging Face Inference
pip install mcp-bastion-deepseek       # DeepSeek AI
pip install mcp-bastion-together       # Together AI
pip install mcp-bastion-fireworks      # Fireworks AI
pip install mcp-bastion-fastmcp       # FastMCP servers

Package	Protects	Version	Downloads
mcp-bastion-langchain	LangChain	2.0.0	pypistats · pepy
mcp-bastion-openai	OpenAI GPT	2.0.0	pypistats · pepy
mcp-bastion-anthropic	Anthropic Claude	2.0.0	pypistats · pepy
mcp-bastion-bedrock	AWS Bedrock	2.0.0	pypistats · pepy
mcp-bastion-gemini	Google Gemini	2.0.0	pypistats · pepy
mcp-bastion-crewai	CrewAI	2.0.0	pypistats · pepy
mcp-bastion-llamaindex	LlamaIndex	2.0.0	pypistats · pepy
mcp-bastion-groq	Groq	2.0.0	pypistats · pepy
mcp-bastion-mistral	Mistral AI	2.0.0	pypistats · pepy
mcp-bastion-cohere	Cohere	2.0.0	pypistats · pepy
mcp-bastion-azure	Azure OpenAI	2.0.0	pypistats · pepy
mcp-bastion-vertexai	Vertex AI	2.0.0	pypistats · pepy
mcp-bastion-huggingface	Hugging Face	2.0.0	pypistats · pepy
mcp-bastion-deepseek	DeepSeek AI	2.0.0	pypistats · pepy
mcp-bastion-together	Together AI	2.0.0	pypistats · pepy
mcp-bastion-fireworks	Fireworks AI	2.0.0	pypistats · pepy
mcp-bastion-fastmcp	FastMCP servers	2.0.0	pypistats · pepy

Publish (PyPI / npm)

• PyPI: python -m build && twine upload dist/* (or use GitHub Actions on tag).
• npm: From repo root, cd packages/core && npm publish --access public (or use Trusted Publishers).
• Version is set in pyproject.toml (Python), packages/core/package.json (npm), and server.json (MCP registry). Bump before releasing.

Developer Guide

Integration examples for Python and TypeScript. Full contributor and feature docs:

Doc	Description
docs/DEVELOPER_GUIDE.md	Repo layout, local dev, tests, release
docs/FEATURES.md	How-to for all 18 security pillars
docs/RBAC.md	RBAC roles, fnmatch globs, Agent IAM pairing
CONTRIBUTING.md	PR checklist and good-first issues
SUPPORT.md · FUNDING.md	Help and sponsorship

---

Quick Start (Python)

Add MCP-Bastion to an existing MCP server in three steps:

from mcp_bastion import MCPBastionMiddleware, compose_middleware

# 1. Create the security middleware
bastion = MCPBastionMiddleware(
    enable_prompt_guard=True,
    enable_pii_redaction=True,
    enable_rate_limit=True,
)

# 2. Compose with your middleware chain (Bastion runs first)
middleware = compose_middleware(bastion)

# 3. Pass the composed middleware to your MCP server
# (integration depends on your server framework)

Examples:

Example	Description
examples/python_server_example.py	Basic middleware chain
examples/full_demo.py	Full middleware stack: add, PII, rate limit, prompt injection, etc.
examples/llm_openai_example.py	MCP server for OpenAI
examples/llm_claude_example.py	MCP server for Claude
examples/llm_gemini_example.py	MCP server for Gemini
examples/llm_mistral_example.py	MCP server for Mistral
examples/llm_grok_example.py	MCP server for Grok (xAI, HTTP only)

# Windows: $env:PYTHONPATH="src"; python examples/full_demo.py
# Linux/Mac: PYTHONPATH=src python examples/full_demo.py

LLM integration: See docs/LLM_INTEGRATION.md for copy-paste config for OpenAI, Claude, Gemini, Mistral, and Grok.

Enterprise validation:

PYTHONPATH=src python scripts/validate_checklist.py

See VALIDATION_CHECKLIST.md and SETUP_GUIDE.md.

---

Python Tutorial: FastMCP Server

FastMCP server with MCP-Bastion via secure_fastmcp (patches tool dispatch - see integrations/mcp-bastion-fastmcp/README.md).

Step 1: Install dependencies

pip install mcp mcp-bastion-fastmcp

Step 2: Create your server file (server.py)

from mcp.server.fastmcp import FastMCP
from mcp_bastion_fastmcp import secure_fastmcp

mcp = FastMCP("My Secure Server")
secure_fastmcp(mcp)  # call right after FastMCP(), before mcp.run()

@mcp.tool()
def get_weather(city: str) -> str:
    """Get weather for a city."""
    return f"Weather in {city}: 22C, sunny"

if __name__ == "__main__":
    mcp.run(transport="streamable-http")

Step 3: Run the server

python server.py

MCP-Bastion (via secure_fastmcp):

• Scans tool arguments for prompt injection before execution
• Redacts PII in tool results on the way out
• Enforces default rate limits (15 calls per session, 60s timeout - see TokenBucketRateLimiter)

For full bastion.yaml policy or resource (resources/read) PII redaction, use the low-level MCP Server with build_middleware_from_config() - see docs/QUICK_START.md path B.

Alternative: Policy-as-Code

Use bastion.yaml instead of code. Copy bastion.yaml.example to bastion.yaml, then:

from mcp_bastion import build_middleware_from_config
middleware = build_middleware_from_config()

See docs/POLICY_AS_CODE.md and examples/server_with_config.py.

---

Python: Custom Rate Limits

Custom config example:

from mcp_bastion import MCPBastionMiddleware
from mcp_bastion.pillars.rate_limit import TokenBucketRateLimiter
from mcp_bastion.pillars.prompt_guard import PromptGuardEngine

# Stricter limits
rate_limiter = TokenBucketRateLimiter(
    max_iterations=10,
    timeout_seconds=30,
    token_budget=25_000,
)

# Higher threshold = fewer blocks, more risk
prompt_guard = PromptGuardEngine(threshold=0.92)

bastion = MCPBastionMiddleware(
    prompt_guard=prompt_guard,
    rate_limiter=rate_limiter,
    enable_prompt_guard=True,
    enable_pii_redaction=True,
    enable_rate_limit=True,
)

# Disable PII redaction if your data has no PII
bastion_no_pii = MCPBastionMiddleware(enable_pii_redaction=False)

---

Python: Custom Middleware

Extend Middleware to add logging, metrics, or custom logic:

from mcp_bastion import MCPBastionMiddleware
from mcp_bastion.base import Middleware, MiddlewareContext, compose_middleware

class LoggingMiddleware(Middleware):
    async def on_message(self, context, call_next):
        result = await call_next(context)
        # log method, elapsed, etc.
        return result

bastion = MCPBastionMiddleware()  # or use the configured instance from above
middleware = compose_middleware(bastion, LoggingMiddleware())

See examples/full_demo.py for a complete example.

---

TypeScript: Wrap an MCP Server

Step 1: Install dependencies

npm install @modelcontextprotocol/sdk @mcp-bastion/core

Step 2: Create your server (server.ts)

import { Server } from "@modelcontextprotocol/sdk/server/index.js";
import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js";
import {
  wrapWithMcpBastion,
} from "@mcp-bastion/core";

const server = new Server({ name: "my-mcp-server", version: "1.0.0" });

// Wrap the server with MCP-Bastion (rate limiting only by default)
// For prompt injection and PII, run the Python sidecar and set sidecarUrl
wrapWithMcpBastion(server, {
  enableRateLimit: true,
  maxIterations: 15,
  timeoutMs: 60_000,
  // Optional: enable ML features via Python sidecar
  sidecarUrl: process.env.MCP_BASTION_SIDECAR || "",
  enablePromptGuard: !!process.env.MCP_BASTION_SIDECAR,
  enablePiiRedaction: !!process.env.MCP_BASTION_SIDECAR,
});

// Register tools (handlers are automatically wrapped)
server.setRequestHandler("tools/call" as any, async (request) => {
  if (request.params?.name === "get_weather") {
    return {
      content: [{ type: "text", text: "Sunny, 22C" }],
      isError: false,
    };
  }
  throw new Error("Unknown tool");
});

async function main() {
  const transport = new StdioServerTransport();
  await server.connect(transport);
}

main();

Step 3: Run with rate limiting only

npx tsx server.ts

Step 4: Run with full ML features (Python sidecar)

For prompt injection and PII redaction, run a Python HTTP service that exposes /prompt-guard and /pii-redact endpoints (see the Python package for sidecar implementation). Then:

# Start the Python sidecar, then the TypeScript server (sidecarUrl or MCP_BASTION_URL)
MCP_BASTION_SIDECAR=http://localhost:8000 npx tsx server.ts

---

TypeScript: Wrap Individual Handlers

Wrap specific handlers only:

import {
  wrapCallToolHandler,
  wrapReadResourceHandler,
} from "@mcp-bastion/core";
import {
  CallToolRequestSchema,
  ReadResourceRequestSchema,
} from "@modelcontextprotocol/sdk/types.js";

// Wrap only the tool handler
const safeToolHandler = wrapCallToolHandler(
  async (request) => {
    // Your tool logic
    return { content: [{ type: "text", text: "OK" }], isError: false };
  },
  { enableRateLimit: true, maxIterations: 10 }
);

// Wrap only the resource handler (for PII redaction)
const safeResourceHandler = wrapReadResourceHandler(
  async (request) => {
    const contents = await fetchResource(request.params.uri);
    return { contents };
  },
  { sidecarUrl: "http://localhost:8000", enablePiiRedaction: true }
);

server.setRequestHandler(CallToolRequestSchema, safeToolHandler);
server.setRequestHandler(ReadResourceRequestSchema, safeResourceHandler);

---

Configuration Reference

Option	Python	TypeScript	Default	Description
enable_prompt_guard	Yes	Yes	True (Python) / False (TS)	Block malicious prompts via PromptGuard
enable_pii_redaction	Yes	Yes	True (Python) / False (TS)	Mask PII in outgoing content
enable_rate_limit	Yes	Yes	True	Enforce iteration and timeout caps
max_iterations	Via TokenBucketRateLimiter	Yes	15	Max tool calls per session
timeout_seconds / timeoutMs	Via TokenBucketRateLimiter	Yes	60	Session timeout
token_budget	Via TokenBucketRateLimiter	-	50,000	FinOps token cap per request
sidecarUrl	-	Yes	""	Python sidecar URL for ML features
threshold	Via PromptGuardEngine	-	0.85	Malicious probability cutoff
setLogLevel	-	Yes	"info"	TypeScript: "debug" | "info" | "warn" | "error"

---

Error Handling

When MCP-Bastion blocks a request, it returns standard MCP/JSON-RPC errors:

Code	Exception	When
-32001	PromptInjectionError	Tool args contain jailbreak/injection
-32002	RateLimitExceededError	Session exceeds iteration or timeout limit
-32003	TokenBudgetExceededError	Session exceeds token budget
-32004	CircuitBreakerOpenError	Tool’s circuit breaker is open after failures
-32005	ContentFilterError	Content filter matched a blocked pattern
-32006	RBACError	Caller not allowed to use this tool
-32007	SchemaValidationError	Tool arguments failed schema validation
-32008	ReplayAttackError	Duplicate nonce / replay detected
-32009	CostBudgetExceededError	Session cost budget exceeded
-32010	SemanticFirewallError	Tool sequence / argument pattern failed semantic firewall
-32011	ExternalPolicyDeniedError	OPA/Cedar (or other external) policy denied the request
-32012	SensitiveContentError	Sensitive-business classifier above threshold
-32013	AuthenticationError	Edge / gateway authentication (metadata token) failed
-32014	ToolNotAllowedError	Tool not on allowlist
-32015	SessionScopeExceededError	Too many distinct tools per session (scope creep)
-32016	ToolMetadataPoisoningError	Tool list / metadata failed safety checks
-32017	GroundingViolationError	Ungrounded file reference in tool output
-32018	PromptGuardUnavailableError	PromptGuard ML unavailable and fail-closed (or heuristics disabled)
-32019	AgentAccessDeniedError	Authenticated agent attempted a tool outside its IAM policy
-32020	ServerVerificationError	MCP server file checksums do not match trusted manifest

# Python: exceptions
from mcp_bastion.errors import (
    PromptInjectionError,
    RateLimitExceededError,
    TokenBudgetExceededError,
    CircuitBreakerOpenError,
    ContentFilterError,
    RBACError,
    SchemaValidationError,
    ReplayAttackError,
    CostBudgetExceededError,
    SemanticFirewallError,
    ExternalPolicyDeniedError,
    SensitiveContentError,
    AuthenticationError,
    ToolNotAllowedError,
    SessionScopeExceededError,
    ToolMetadataPoisoningError,
    GroundingViolationError,
    PromptGuardUnavailableError,
    AgentAccessDeniedError,
    ServerVerificationError,
)
import logging
logger = logging.getLogger(__name__)

try:
    result = await middleware(context, call_next)
except (
    PromptInjectionError,
    RateLimitExceededError,
    TokenBudgetExceededError,
    CircuitBreakerOpenError,
    ContentFilterError,
    RBACError,
    SchemaValidationError,
    ReplayAttackError,
    CostBudgetExceededError,
    SemanticFirewallError,
    ExternalPolicyDeniedError,
    SensitiveContentError,
    AuthenticationError,
    ToolNotAllowedError,
    SessionScopeExceededError,
    ToolMetadataPoisoningError,
    GroundingViolationError,
    PromptGuardUnavailableError,
    AgentAccessDeniedError,
    ServerVerificationError,
) as e:
    logger.warning("blocked: %s", e.to_mcp_error())

// TypeScript: handlers return isError: true
import { logger, setLogLevel } from "@mcp-bastion/core";
setLogLevel("debug");  // optional: "debug" | "info" | "warn" | "error"
const result = await guardedHandler(request);
if (result.isError) {
  logger.error("blocked", result.content);
}

---

Testing

MCP Inspector:

# Start your guarded server
python server.py   # or: npx tsx server.ts

# In another terminal, launch the Inspector
npx -y @modelcontextprotocol/inspector

Connect via HTTP (http://localhost:8000/mcp) or stdio, then:

1. List tools and call one with benign arguments (should succeed)
2. Call a tool with "Ignore previous instructions" (should be blocked)
3. Trigger 16+ tool calls in one session (should hit rate limit)

---

Testing

# Python (PYTHONPATH=src on Windows: $env:PYTHONPATH="src")
python -m pytest tests/ -v

# TypeScript
npm run test --workspace=@mcp-bastion/core

# Full validation checklist (build, pillars, latency)
PYTHONPATH=src python scripts/validate_checklist.py

# MCP Inspector (manual)
npx -y @modelcontextprotocol/inspector

Third-Party Components

See NOTICE for licenses. MCP-Bastion uses Meta Llama Prompt Guard 2 (Llama 4 Community License) and Microsoft Presidio. For OWASP-relevant mitigations and dependency audit, see docs/SECURITY.md. To report vulnerabilities privately, see SECURITY.md.

License

MCP-Bastion is distributed under the MCP-Bastion Community and Commercial License (LICENSE).

• Free for non‑commercial use when you cite MCP-Bastion and the copyright notice (see CITATION.cff; you can list your name, team, or org as authors or as who used the software, while still including the project and repository in the credit).
• Copyright is retained. Do not remove license or copyright text, and do not republish a duplicate of the work as if it were unrelated software without meeting the License terms.
• Commercial use (as defined in the License) may still require a separate written agreement - see COMMERCIAL_LICENSE.md.

See also:

• LICENSE
• COMMERCIAL_LICENSE.md
• FUNDING.md - sponsorship and sustainability
• SUPPORT.md - docs, issues, response expectations
• CITATION.cff

---

Product overview deck

MCP-Bastion features deck (PDF) - cost-aware runtime governance, pillar map, FinOps benchmarks, and deployment patterns in a short slide deck for evaluators and stakeholders.