flanj — Flanj SDK for Python

Your integration didn't break. It started being wrong. Every call succeeded. That's why nothing caught it.

Early — MCP only. See Status.

flanj.io

flanj instruments an MCP client session (mcp.ClientSession). It records the tools/list catalogue each MCP server hands your agent and the tools/call traffic that follows. It redacts sensitive data at the source, then exports the redacted records over OTLP to a Flanj collector. The collector checks every call against the contract the server published and flags drift.

Trust posture. Capture is out of band: the SDK wraps the session your agent already uses, and never proxies, rewrites, delays or blocks a call. Arguments pass through by reference, the tool's own result object is returned, and exceptions propagate unchanged. Redaction runs in your process, before a record is exported. Redacted records go only to a collector you run in your own environment; bodies never leave it. See REDACTION.md for the floor and how it is held identical across languages.

Quick start

Needs Python 3.10+ and a running Flanj collector. The collector README's Run it on Kubernetes section is the preferred way to deploy it; Run it with Docker is the other. Python 3.10 is the floor of the official mcp package this SDK instruments, so there is no supported MCP client below it; an older runtime is refused with one sentence rather than failing somewhere inside a capture path.

pip install flanj

Needs Python 3.10+: on an older interpreter pip does not refuse, it silently installs the unrelated 0.0.1 placeholder that once held the name.

Make this the first line of your program — before anything imports mcp:

import flanj.register  # noqa: F401

That is one line, and nothing else changes. It starts the OTLP pipeline, flushes on exit and auto-instruments every MCP client session your program opens afterwards, placing each server on its own edge. It prints one line naming the endpoint and the resolved service name (FLANJ_QUIET=1 silences it). It is the counterpart of the TypeScript SDK's node -r @flanj/sdk/register.

If your collector is running with Docker, there is nothing to point it at: http://localhost:4318/v1/logs is this SDK's default FLANJ_OTLP_ENDPOINT already, and that is where that collector listens.

On Kubernetes

The chart creates a front Service with a fixed name, so the one address that is right for everyone who installed with the Run it on Kubernetes command is http://flanj-collector.flanj:4318/v1/logs. Set it on your own workload, not your shell: the SDK runs in the agent's pod, where localhost is not the collector.

env:
  - name: FLANJ_OTLP_ENDPOINT
    value: http://flanj-collector.flanj:4318/v1/logs

The chart also renders a ConfigMap/flanj-endpoint for teams that would rather use envFrom than a literal value. A pod can only reference a ConfigMap in its own namespace, so the chart has to be told which namespaces to render it into — see the chart README.

Verify — after your agent has made at least one tool call. On Docker, docker compose up -d already starts the bridge that publishes the collector's UI at 127.0.0.1:5335. On Kubernetes, forward it first:

kubectl -n flanj port-forward sts/flanj-flanj-collector-store 5335:5335

curl -s http://127.0.0.1:5335/api/health

then open http://127.0.0.1:5335 and look at the Traffic tab: your tool call should be there, redacted.

If that curl answers Failed to connect: on Docker, confirm the compose stack is still up (docker compose ps); on Kubernetes, confirm the port-forward above is still running. Ingest on :4318 is a separate, ordinary port either way.

Load flanj first

A Python ClientSession holds two in-memory streams and no URL, so the SDK learns where each MCP server is when its transport opens — it wraps streamable_http_client, sse_client and stdio_client. A program that did from mcp.client.stdio import stdio_client before flanj loaded holds the unwrapped function, and flanj never sees those transports. The same rule applies to Datadog's import ddtrace.auto, for the same reason.

A session whose transport flanj never saw is not guessed at: its edge is unknown, its calls are recorded without bodies (it might be an internal server, whose bodies are never read), and flanj says so once on stderr, naming the fix. unknown is the one behaviour this SDK has that the TypeScript SDK does not; a JavaScript MCP client keeps its transport, so it can always place a server.

MCP quick start

Nothing is configured per server. With the zero-code entry loaded, an ordinary session is already captured:

import flanj.register  # noqa: F401  — first line, before `mcp` is imported

from mcp import ClientSession
from mcp.client.streamable_http import streamable_http_client

async with streamable_http_client("https://mcp.acme.com/mcp") as (read, write):
    async with ClientSession(read, write) as session:
        await session.initialize()
        await session.list_tools()                                  # -> a contract snapshot
        await session.call_tool("get_balance", {"account_id": "x"}) # -> a captured, redacted call

For each tools/call: the arguments as the request body; structuredContent — else the content[] text — as the response body; the outcome (isError); the server's identity from the result's _meta; and the JSON-RPC request id your client generated, labelled as client-generated. A call the server rejected (a JSON-RPC error rather than a result with isError) also records the error's code. A Tasks handle (tasks/get) is recorded as an envelope with no body, so nothing models the envelope as the tool's own output shape.

For each complete tools/list: the server's own declared schemas, verbatim, never re-inferred. The catalogue is refetched and re-snapshotted on notifications/tools/list_changed (refetch_on_list_changed, on by default), so a server that changes its tools mid-session is caught when it does.

For a server your app launched over stdio: how it was launched (npx @stripe/mcp@0.2.1 …) — the command and its arguments only, each floor-redacted, never the environment or the working directory.

Your service's name is the only thing you configure, and it defaults to your app's own name (python -m myapp → myapp), then flanj-sdk. It travels as the OTLP resource service.name, and the collector shows it as a Service column beside the counterparty and as a Traffic filter. It names your own internal topology, so it stays on your collector: a service name is never sent to the control plane.

Instrumenting a client yourself

import flanj                        # still first
handle = flanj.start()              # the OTLP pipeline; wraps the transport openers

from mcp import ClientSession
from mcp.client.streamable_http import streamable_http_client

async with streamable_http_client("https://mcp.acme.com/mcp") as (read, write):
    async with ClientSession(read, write) as session:
        handle.instrument(session)  # this handle's logger and body cap
        await session.initialize()
        # Use `session` exactly as before. Nothing about its behavior changes.
        result = await session.call_tool("get_balance", {"account_id": "acct_1"})

To instrument every session without the zero-code entry, call flanj.register_mcp_auto_instrumentation(logger=handle.logger) after start().

Configuration

Records are flushed on normal exit and on SIGTERM / SIGINT (flanj.flush_on_exit(handle), which flanj.register installs), bounded to five seconds, after which your own signal handling runs as before.

What is captured

Captured: every tools/call and tools/list on an instrumented session, over any transport the official client supports (streamable HTTP, stdio). The fields are listed under MCP quick start.

Not captured:

• HTTP request/response bodies. Python has no node:http choke point to patch the way the TypeScript SDK does. Per-library HTTP capture (requests/httpx/aiohttp) is not started. This is the one intended difference between the two SDKs.
• tasks/get payloads. A Tasks handle is recorded as an envelope with no body, so nothing models the envelope as the tool's output shape.

Edges. A server reached over a URL is external or internal by its host, the same rule the collector uses; internal servers are metadata-only. A server your app launched over stdio is local-process, keyed by the name it reports, and its bodies are captured: it usually wraps someone else's API. A server flanj could not place is unknown, metadata-only. Every captured body is redacted in your process before it is exported; see REDACTION.md for what is redacted and how.

When capture itself fails it stops collecting and says so — once, on stderr, naming what broke and that your application is unaffected. Silence is the failure mode this SDK exists to remove, and a collector showing nothing looks exactly like an agent making no calls. FLANJ_SILENCE_CAPTURE_WARNINGS=1 turns the line off once you have read it.

MCP clients: the contract arrives with the traffic

REST drift detection needs a spec somebody published and kept accurate. MCP servers publish their contract on every single call — tools/list is the spec. So the collector has the baseline from the first call your agent makes, for every MCP server it touches, with nothing to configure and nothing to upload: the observed tools/list is forwarded as a contract snapshot, versioned by content hash, and every later tools/call is checked against it.

That is not a convenience difference. "Nobody publishes an accurate OpenAPI spec" is the strongest practical objection to drift detection on REST, and it does not apply to MCP at all. It matters most for agents, the most drift-fragile API consumers anyone has built: an agent reads a tool's description to decide what to do, so a description that changes under it changes what it does, and nothing anywhere logs an error. For this SDK that is not one feature among several — it is the whole product.

There is nothing to configure per server: the collector derives each MCP server's integration from its peer host (or, over stdio, the name it reports), so two servers never share a baseline.

It stays out of the way

call_tool is a coroutine, so three properties matter more here than in a synchronous SDK. Each is locked by a test rather than asserted in prose (tests/mcp/test_async_transparency.py):

• cancellation passes through untouched: a cancelled call is the caller withdrawing, not an outcome, so it is neither captured nor delayed;
• no suspension point is added: the wrapper awaits the wrapped coroutine and nothing else, so scheduling order is unchanged;
• the result is read, never consumed: capture holds no reference past the call and iterates nothing.

Status

Early — MCP only. Not Supported: a language is called supported only once the whole loop runs on it end to end in our own integration harness, with that suite's assertions green. Until then it says early, here and everywhere else.

Languages. Node / TypeScript — supported: @flanj/sdk, HTTP egress and ingress plus the MCP client. Python — early: this package, MCP client only. Apart from HTTP capture the two are the same SDK: same defaults, same records, same entry points.

Where this stops, said out loud. No HTTP body capture (see What is captured). A call the collector cannot check against a contract is captured and reported as not validated, never as conforming. Pre-release (v0); see docs/CONCEPTS.md for the engineering model and CLAUDE.md for the repo map.

Flanj turns a detection into something you can act on with the other team. The SDK is open source under Apache-2.0; the collector is source-available under the Elastic License 2.0; the network layer that carries a flagged finding between the two teams is hosted.

Development

uv venv --python 3.10 && uv pip install -e ".[dev]"
pytest                       # the floor's contract suites, the wire seam, the async contract
ruff check . && mypy         # lint and types
bash scripts/smoke-pack.sh   # build the wheel, install it into a FRESH venv, drive a real MCP server

Security

Report vulnerabilities, including any redaction gap, privately — see SECURITY.md. Never include a real card number or real personal data.

License

Apache-2.0. Contributions require a DCO sign-off; see CONTRIBUTING.md.