Python Code Validator
This server validates Python code through static and security analyses, with optional repair and execution (both require a paid key).
Validate: Syntax & lint analysis, AST security scan (including dynamic imports and runtime attribute lookups), Bandit security pass, credential scan.
Repair (paid key): Deterministic repair returns fixed code.
Execute (paid key): Sandboxed execution to observe behavior.
Verdict: Scored verdict for code quality/safety.
Integration: MCP (HTTP/stdio), HTTP API, CI/CD, pre-commit hooks, CLI.
Extras: Filename-aware diagnostics, large file support (up to 200,000 characters), privacy-respecting (code not logged).
Provides a GitHub Action and CI script to validate Python files in workflows, annotating offending lines on the diff and failing on errors.
Provides a pre-commit hook to run Python code validation before each commit.
Provides syntax and lint diagnostics, AST security policy checks, bandit pass, credential scanning, and deterministic repair for Python code.
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.
Related MCP server: code-quality-mcp
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.jsonunder"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-validatorGemini CLI installs the same bridge as an extension, with the instruction file that makes it get used:
gemini extensions install jkanselaar/python-code-validatorThree tools, named after what they do to the code:
tool | runs the code | key |
| no | free |
| no | paid |
| yes | paid |
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@statemindNothing 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 $base/cursor/hooks.json -o .cursor/hooks.jsonProject hooks run from the project root, which is why the command in
cursor/hooks.json is a path relative to it. For a hook
that applies to every project instead, put the script in ~/.cursor/hooks/ and
the same block in ~/.cursor/hooks.json with the command
python3 ./hooks/validate_written.py --cursor.
Making the agent use it
Configuring the server is not what gets it called: the instruction file is.
AGENTS.md in this repository is that text, written to be dropped
into any project under whichever name the client reads:
mkdir -p .github
curl -sf https://raw.githubusercontent.com/jkanselaar/python-code-validator/main/AGENTS.md \
| tee AGENTS.md CLAUDE.md GEMINI.md .github/copilot-instructions.md >/dev/nullCursor reads rules with front matter instead, so that one is a separate file —
copy .cursor/rules/python-code-validator.mdc
into .cursor/rules/ of the project.
The short version, if you would rather add a line to instructions you already have:
Write what the code should do as
assertexamples before writing the code, and pass them inoptions.examples. Callvalidate_pythonafter every edit andexecute_pythononce a function is finished, not again until what it does has changed. When a call returnsfixed_code, take it — the service ran it against your examples. Do not present code that came backvalid: false.
CI
The service hands out the client, so a workflow needs no checkout of this repository and no secret:
- run: |
curl -sf https://api.statemind.ai/v1/client -o validate.py
python3 validate.py --changed-against "origin/${{ 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 itThe 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-validatorThe 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 acceptedVALIDATOR_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:
[](https://api.statemind.ai/?src=badge)HTTP
curl -s https://api.statemind.ai/v1/validate \
-H "Authorization: Bearer $VALIDATOR_API_KEY" \
-H 'content-type: application/json' \
-d '{"code": "def f(:\n pass\n", "mode": "static"}'mode is static, repair or execute; repair and execute need a
configured key. Submitted code is not logged.
A refused call says what to do about it, so a caller with no operator to ask can resolve it itself:
{"error": "payment_required",
"remedy": {"action": "upgrade_key", "hint": "A free key covers static only. …"}}Paying for calls
A free key covers 25 static checks a day, and one address gets a few keys a day, so the allowance is a trial rather than a supply. Beyond it a key carries credits: a static check costs 1, a repair 3 and a sandboxed run 10, and an identical call repeated within ten minutes is answered from the first one for free.
Credits are bought with a card, without an invoice or anyone to ask:
curl -s -X POST https://api.statemind.ai/v1/keys/checkout \
-H 'content-type: application/json' \
-d '{"api_key": "'"$VALIDATOR_API_KEY"'", "credits": 500}'That answers with a Stripe Checkout page; the credits are on the key seconds
after the card clears (500 credits is €10). An agent with a Gnosis wallet can
instead pay in xDAI without a browser — GET /v1/pricing states both routes.
Examples
examples/ holds three files and the client to send them with: one
that passes every check and still returns the wrong number, one the security
policy refuses, and one that comes back accepted from the sandbox.
Licence
MIT.
Maintenance
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