nautilus-rkm 0.2.0

Policy-first data broker for AI agents — one call plans, routes, enforces, attests, and audits every data access. Built on Fathom.

Nautilus

Policy-first data broker for AI agents. One call plans, routes, enforces, attests, and audits.

Part of the Kraken stack: Fathom (reasoning engine) · Nautilus (policy data broker) · Stargraph (agent-graph framework).

Current version: 0.1.3 License: Apache-2.0 Language: Python 3.13+ Package Manager: uv Maintained by: KrakenNet

---

Why Nautilus?

Every AI agent framework gives agents direct access to data. For most tasks, that's fine.

For some tasks, unchecked access is unacceptable:

• Policy routing — "Which databases should this query hit?" can't be the agent's choice.
• Scope enforcement — "What rows is this agent allowed to see?" needs provable constraints.
• Audit — "What data did this agent touch, and why?" requires a tamper-evident trail.
• Attestation — "Can we prove this routing decision happened?" needs a signed token.

Nautilus provides deterministic, policy-first data brokering using Fathom — a CLIPS-based expert system — to route, scope, and attest every request.

Install

uv add nautilus-rkm

Quick Start

from nautilus import Broker

broker = Broker.from_config("nautilus.yaml")
try:
    response = broker.request(
        "agent-alpha",
        "Find vulnerabilities for CVE-2026-1234",
        {"clearance": "unclassified", "purpose": "threat-analysis", "session_id": "s1"},
    )
    print(response.data)                # {"main-db": [...]}
    print(response.sources_queried)     # ["main-db"]
    print(response.sources_denied)      # ["classified-db"]
    print(response.attestation_token)   # signed JWS
    print(response.duration_ms)         # 47
finally:
    broker.close()

See the Getting Started guide for a full walkthrough.

What Ships Today

Core runtime

• Broker facade with sync/async APIs (request, arequest, from_config, afrom_config)
• Fathom-based policy router for intent-aware source selection and scope enforcement
• Per-source scope constraints (WHERE-clause fragments) with injection-safe field validation
• Ed25519 JWS attestation service for signed routing decisions
• JSONL audit sink with per-request, append-only entries (fsync'd)
• Pattern-matching and LLM-based intent analysis (Anthropic, OpenAI)
• Cross-agent handoff reasoning with session-backed escalation detection

Adapters (8 built-in)

• PostgreSQL, PgVector, Elasticsearch, Neo4j, REST, ServiceNow, InfluxDB, S3
• Pluggable via entry points and the Adapter SDK

Transports

• FastAPI REST server (POST /v1/request, health/readiness probes)
• MCP transport (stdio and HTTP modes)
• CLI: nautilus serve, nautilus health, nautilus version

Rule packs

• data-routing-nist — NIST clearance/classification routing rules
• data-routing-hipaa — HIPAA-compliant routing rules

What You Get Per Request

Step	What happens
Intent analysis	Classify intent into data types, entities, temporal scope, sensitivity
Policy routing	Fathom evaluates (clearance, purpose, source) — route, scope, or deny
Adapter fan-out	Routed sources execute concurrently with per-adapter error isolation
Attestation	Ed25519 JWS signed over routing decision, bound to request_id
Audit	JSONL entry appended per request — success, denial, or error

Key Differentiator: Session-Aware Routing

Unlike stateless policy engines, Nautilus maintains working memory across requests within a session:

• Cumulative exposure — "This agent accessed PII from 3 sources — deny the 4th."
• Cross-agent handoffs — "Agent A is passing secret data to Agent B who has unclassified clearance — deny."
• Escalation detection — "Anomalous access pattern detected — escalate for forensic review."

Integration Shapes

As a library

from nautilus import Broker
broker = Broker.from_config("nautilus.yaml")
response = broker.request("agent-id", "intent", context)

As a REST sidecar

nautilus serve --config nautilus.yaml --transport rest --bind 0.0.0.0:8000
curl -H "X-API-Key: $KEY" -X POST localhost:8000/v1/request \
  -d '{"agent_id": "agent-alpha", "intent": "...", "context": {...}}'

As an MCP server

nautilus serve --config nautilus.yaml --transport mcp

Air-gapped mode

nautilus serve --config nautilus.yaml --air-gapped

Configuration

A nautilus.yaml declares sources, rules, analysis, audit, and attestation:

sources:
  - id: main-db
    adapter: postgres
    dsn: ${DATABASE_URL}
    classification: confidential
    data_types: [users, orders]

rules:
  paths: [./rules/]

attestation:
  enabled: true

audit:
  sink: file
  path: ./audit.jsonl

Documentation

Full documentation is available at nautilus.krakn.ai.

• Getting Started
• Concepts
• How-to Guides
• Reference

Related Projects

• Fathom — Deterministic reasoning runtime that powers Nautilus routing
• Bosun — Agent governance built on Fathom (fleet analysis, compliance attestation)

Development

git clone https://github.com/KrakenNet/nautilus.git
cd nautilus
uv sync
uv run pytest -m unit            # fast suite, no containers
uv run pytest -m integration     # full e2e, boots PostgreSQL via testcontainers
uv run ruff check && uv run ruff format --check && uv run pyright
uv run mkdocs serve              # docs preview

See CHANGELOG.md for release notes.

Contributing

We welcome contributions! Please read our Contributing Guide before submitting a pull request. All contributors are expected to follow our Code of Conduct.

Security

To report a security vulnerability, please see our Security Policy. Do not open a public issue for security concerns.

Star History

License

Apache-2.0 — see LICENSE for details.