Python Code Validator
Proves AI-generated Python does what you asked: state the intent as assertions and the server runs the code in a locked-down container, returning a fix only when every example passes.
Documentation
Python Code Validator
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.
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": 100, "modes": ["static"]}
100 validations a day, metered per UTC day. 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.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-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:
| tool | runs the code | key |
|---|---|---|
validate_python | no | free |
repair_python — also returns fixed_code | no | paid |
execute_python — also runs it in a sandbox | 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.
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
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:
- uses: jkanselaar/python-code-validator@v1.21.0
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.
Pre-commit
repos:
- repo: https://github.com/jkanselaar/python-code-validator
rev: v1.21.0
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.
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.
Licence
MIT.