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Apifacts MCP Server

Developer ToolsLow Risk10.0MCP RegistryLocal
Free

Server data from the Official MCP Registry

Verified facts and typed fixes for failing third-party API calls (Stripe, GitHub, Google…)

About

Verified facts and typed fixes for failing third-party API calls (Stripe, GitHub, Google…)

Security Report

10.0
Low Risk10.0Low Risk

Valid MCP server (3 strong, 1 medium validity signals). No known CVEs in dependencies. Package registry verified. Imported from the Official MCP Registry.

8 files analyzed · 1 issue found

Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.

Permissions Required

This plugin requests these system permissions. Most are normal for its category.

file_system

Check that this permission is expected for this type of plugin.

HTTP Network Access

Connects to external APIs or services over the internet.

database

Check that this permission is expected for this type of plugin.

How to Install

Add this to your MCP configuration file:

{
  "mcpServers": {
    "io-github-illouminus-apifacts": {
      "args": [
        "apifacts"
      ],
      "command": "uvx"
    }
  }
}

Documentation

View on GitHub

From the project's GitHub README.

apifacts

A verified changelog of reality for AI agents. An open registry of typed, dated facts about what third-party machine interfaces (HTTP APIs, SDK packages, CLIs) actually do today, as opposed to what their docs say.

Why

Interfaces change, docs lag, and nobody tells the agent. Every session pays tokens to rediscover the same traps: a 200 with an empty array instead of a 429, a rate limit reported as status: 0 in the body, an SDK release that silently dropped a field. Documentation tools answer "give me the right docs"; apifacts answers "the docs are wrong about this endpoint right now, here is the verified difference".

Install

pip install apifacts-pytest   # pytest plugin: a test failing on an HTTP error prints the known facts
uvx apifacts check https://api.stripe.com/v1/charges -X GET --status 401   # CLI (and library)
npx skills add Illouminus/apifacts   # agent skill: on an API error, ask the registry first

Both packages are on PyPI, carry the same version and ship together from one tag (release). The plugin sends nothing until a test fails. The skill (skills/apifacts/SKILL.md) tells Claude Code and other agents when to call apifacts check and how to read the answer.

CI

Agents that fix a red build read the failing step's log, the annotations and the job summary. The GitHub Action puts the known facts in all three (action/README.md):

- uses: Illouminus/apifacts/action@v0
  with:
    run: pytest -q   # same exit code as without the action; scanned only when it fails

Anywhere else, pipe a log through apifacts scan (uvx apifacts scan build.log): it finds the failed HTTP calls that requests, httpx, gh, axios and curl -f print, and asks about each.

MCP

One tool, check(target, method, status, body), over stdio; no resources, no prompts. Claude Code:

claude mcp add apifacts -- uvx --from 'apifacts[mcp]' apifacts mcp

Claude Desktop, Cursor and other clients (mcpServers in their JSON config):

{"mcpServers": {"apifacts": {"command": "uvx", "args": ["--from", "apifacts[mcp]", "apifacts", "mcp"]}}}

apifacts mcp --offline answers from the snapshot packaged in the wheel and sends nothing.

How a fact is verified

  • One fact per YAML file in facts/<service>/, with a kind (error_meaning, rate_limit, breaking_change, ...), the exact error signal, a one-sentence claim, dimensions (env, plan, region, account_state) and evidence.
  • Truth comes only from deterministic probes: declarative HTTP steps and assertions that our runner executes on a schedule. No language model is called anywhere in the verification path.
  • Fixes are data, not advice: members of a closed vocabulary with typed parameters (no free text, no shell, no foreign URLs), rendered to one English sentence by us.
  • A probe in another environment never refutes a fact; it adds a dimension.

Calling check()

One endpoint answers and learns at the same time: the request is the contribution. Send the target and, optionally, the error you got; receive matching facts with typed fixes and what the probes observe. If the target matches a registered template, a normalized observation is stored (no bodies, headers, query strings or raw IPs).

curl -s https://apifacts.dev/v0/check \
  -H 'Content-Type: application/json' \
  -d '{"target": {"method": "POST", "url": "https://api.stripe.com/v1/payment_intents"},
       "error": {"status": 400, "body_excerpt": "Keys for idempotent requests can only be used with the same parameters they were first used with."}}'

The response is never empty: facts, observed, and an unknown.reason when nothing matches.

Status

The API is live at https://apifacts.dev (/v0/check, /v0/services, /openapi.json, /healthz; facts.baillot.dev, the old address, redirects there). The registry covers the services and facts listed at apifacts.dev/registry, each fact page showing how it was established; /llms.txt describes the API for agents. Design contracts live in docs/specs/.

Running your own copy: the API reads facts/ and services/ once, at startup, so after a git pull restart it; ops/deploy.sh checks out, syncs and restarts in one step.

Contributing

Calling check() is contributing. Pull requests are for humans and API producers: see CONTRIBUTING.md. Producer signatures are always free.

License

Code: MIT. Data (facts/ and the generated fact pages): CC BY 4.0.

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