Python Code Validator

An MCP server that validates, repairs and runs Python against the examples it is supposed to satisfy — validate_python, repair_python and execute_python over HTTP at https://api.statemind.ai/mcp, with a free key and no account.

A hosted service that proves AI-generated Python does what you asked. State the intent — assertions or doctest lines — and the code is run against it inside a container with no network and a read-only filesystem; a fix comes back only when every example passes. On the QuixBugs defects that is 41% repaired and 77% refused as not doing what they say, with no false alarms on the corrected programs — where ruff and mypy flag the defect in none of them (the numbers).

The checks that need no intent come with it: syntax and lint diagnostics, an AST security policy that also catches calls hidden behind dynamic imports and runtime attribute lookups, a bandit pass, a credential scan and deterministic repair — one verdict with a score. Asking the same question twice inside ten minutes is answered from the first answer and costs nothing (x-msvc-repeat: 1).

This repository holds the client side: the MCP configuration, the CI script and the pre-commit hook. The service itself runs at https://api.statemind.ai, so there is nothing to install or host.

A key, without an account

curl -s -X POST https://api.statemind.ai/v1/keys
# {"api_key": "msvc_free_…", "tier": "free", "calls_per_day": 25, "modes": ["static"]}

25 static checks a day, metered per UTC day, and a few keys per address: enough to try it and to run it over a small project, not a supply. Every answer carries the state of the allowance (x-quota-remaining, x-quota-reset), so a client can back off before it is cut off.

MCP

Registered in the official MCP registry as ai.statemind/python-code-validator, a name verified against the domain that serves it rather than a GitHub account. Any MCP client adds it with one block:

{
  "mcpServers": {
    "python-code-validator": {
      "type": "http",
      "url": "https://api.statemind.ai/mcp",
      "headers": { "Authorization": "Bearer msvc_free_…" }
    }
  }
}

• Claude Code: claude mcp add --transport http python-code-validator https://api.statemind.ai/mcp --header "Authorization: Bearer msvc_free_…"
• Cursor: ~/.cursor/mcp.json, same block.
• VS Code / Copilot: .vscode/mcp.json under "servers".

A client that only launches a command uses the stdio bridge in this repository instead, which forwards the same tool over HTTPS:

{
  "mcpServers": {
    "python-code-validator": {
      "command": "python3",
      "args": ["/path/to/python-code-validator/mcp_stdio.py"]
    }
  }
}

Or as a container, which the Dockerfile here builds:

docker build -t python-code-validator .
docker run -i --rm -e VALIDATOR_API_KEY python-code-validator

Gemini CLI installs the same bridge as an extension, with the instruction file that makes it get used:

gemini extensions install jkanselaar/python-code-validator

Three tools, named after what they do to the code:

The old single python_code_validator tool, with its mode argument, still answers for clients that already configured it, but is no longer listed.

Saying what the code was supposed to do

Every check above passes on a function that computes the wrong answer. The one thing that catches it is the intent, and the agent that asked for the code is the only one who has it — so pass it along:

{"code": "def bitcount(n): …", "mode": "execute",
 "options": {"examples": "assert bitcount(127) == 7"}}

Doctest lines (>>> bitcount(127) then 7) work the same way, as do >>> examples already written in the source. execute_python runs them in the sandbox: one that does not hold is a python:example-mismatch error, and the repair search returns a fix only when every example passes. On the QuixBugs defect set — real bugs, hidden test inputs deciding correctness — that repairs 41% and refuses 77% as not doing what they say, with no false alarms on the corrected programs.

Repeating a call costs nothing: the same key asking the same question — same mode, same code, same examples — is answered from the answer it already got, marked x-msvc-repeat: 1, so an agent that checks its work at every step is not billed for verdicts that cannot have changed.

Claude Code plugin

An instruction can be ignored; a hook cannot. The plugin checks every Python file Claude Code writes or edits, in the turn it was written, and hands the errors back to the model instead of to you:

/plugin marketplace add jkanselaar/python-code-validator
/plugin install python-code-validator@statemind

Nothing to configure: it mints and keeps its own free key on first use. A file that comes back accepted is silent, a rejected one stops the turn with the offending lines named, and an identical file is not asked about twice. It never ends a session over its own trouble — an unreachable service or a spent allowance lets the turn continue, and the allowance says how to raise it.

Set VALIDATOR_API_KEY to use a paid key instead of the free tier, and VALIDATOR_URL to point at your own deployment. The plugin also carries the validate-python skill, for the part a hook cannot do: stating the intent as examples and running the code against them.

Cursor hook

The same script, wired to Cursor's postToolUse, where the verdict comes back as context on the conversation instead of as an exit code:

mkdir -p .cursor/hooks
base=https://raw.githubusercontent.com/jkanselaar/python-code-validator/main
curl -sf $base/plugin/hooks/validate_written.py -o .cursor/hooks/validate_written.py
curl -sf $base/cursor/hooks.json -o .cursor/hooks.json

Project hooks run from the project root, which is why the command in cursor/hooks.json is a path relative to it. For a hook that applies to every project instead, put the script in ~/.cursor/hooks/ and the same block in ~/.cursor/hooks.json with the command python3 ./hooks/validate_written.py --cursor.

Making the agent use it

Configuring the server is not what gets it called: the instruction file is. AGENTS.md in this repository is that text, written to be dropped into any project under whichever name the client reads:

mkdir -p .github
curl -sf https://raw.githubusercontent.com/jkanselaar/python-code-validator/main/AGENTS.md \
  | tee AGENTS.md CLAUDE.md GEMINI.md .github/copilot-instructions.md >/dev/null

Cursor reads rules with front matter instead, so that one is a separate file — copy .cursor/rules/python-code-validator.mdc into .cursor/rules/ of the project.

The short version, if you would rather add a line to instructions you already have:

Write what the code should do as assert examples before writing the code, and pass them in options.examples. Call validate_python after every edit and execute_python once a function is finished, not again until what it does has changed. When a call returns fixed_code, take it — the service ran it against your examples. Do not present code that came back valid: false.

CI

The service hands out the client, so a workflow needs no checkout of this repository and no secret:

- run: |
    curl -sf https://api.statemind.ai/v1/client -o validate.py
    python3 validate.py --changed-against "origin/${{ github.base_ref }}"

Or as an action, from the Marketplace:

permissions:
  contents: read
  pull-requests: write   # so the run can comment its result on the pull request
steps:
  - uses: jkanselaar/python-code-validator@v1.22.0
    with:
      api-key: ${{ secrets.VALIDATOR_API_KEY }}   # optional; free tier without it

The changed Python is validated and offending lines are annotated on the diff, failing the job on syntax errors and unsafe patterns. Files the service refuses outright (over its 200 kB limit) are skipped with a warning rather than failing the run.

The run also leaves one comment on the pull request, edited in place on later pushes rather than repeated: what was accepted, what was repaired and how much of the day's allowance is left. Without pull-requests: write nothing is written and the job is unaffected; comment: "false" turns it off.

On the free tier the action keeps its key in the workflow cache, one per repository per day, so the allowance belongs to the repository rather than to the run. With api-key set the cache is skipped.

Pre-commit

repos:
  - repo: https://github.com/jkanselaar/python-code-validator
    rev: v1.22.0
    hooks:
      - id: python-code-validator

The client itself

validate.py is standard library only, so it also works as python validate.py file.py in a Makefile, a git hook or a container:

$ python3 validate.py service.py
::error file=service.py,line=88,title=SyntaxError::invalid syntax
FAIL service.py score=0.66

0/1 files accepted

VALIDATOR_API_KEY is used when set; otherwise the client mints a free key — keeping it in VALIDATOR_KEY_FILE when that names a path, which is how a series of runs shares one allowance. VALIDATOR_URL points it at another deployment. VALIDATOR_SOURCE names the caller, which is only ever counted: a run inside a workflow says github-action by itself.

The badge

A repository whose Python is checked on every pull request can say so:

[![Python validated](https://img.shields.io/badge/python-validated-2ea44f?logo=python&logoColor=white)](https://api.statemind.ai/?src=badge)