Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
作者提供的说明(英文原文)
Proves AI-generated Python does what you asked: lint, types, security, sandbox run, exact fixes.
这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。
我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。
选择你使用的 AI 应用,然后复制设置。
Authorization标为机密的值是你账户的钥匙。千万不要分享给别人,也不要粘贴到聊天里。
你需要
你用的是哪个应用?
在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。
这个地址需要在请求的 header 中放入密钥,而添加连接器的菜单无法设置。请改用 Claude Code、Cursor 或 VS Code。
在终端中运行这条命令
claude mcp add --transport http python-code-validator https://api.statemind.ai/mcp --header 'Authorization: your-value'运行前请先填写空着的值。
粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"python-code-validator": {
"url": "https://api.statemind.ai/mcp",
"headers": {
"Authorization": "your-value"
}
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"python-code-validator": {
"type": "http",
"url": "https://api.statemind.ai/mcp",
"headers": {
"Authorization": "your-value"
}
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
这个地址需要在请求的 header 中放入密钥,而添加连接器的菜单无法设置。请改用 Claude Code、Cursor 或 VS Code。
你的选择通过 Cookie 保存在这台设备上,无需账户。
Authorization 机密 必填 HTTP header这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。
我们还没有读取这个服务器的工具列表;我们会轮流检查各个端点。
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月6日
发布者(statemind.ai)不是仓库所有者(jkanselaar);可能是其他人代为上架的
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
尚未检查;我们会轮流检查各个端点
尚未检查;我们会轮流检查各个端点
尚未检查;我们会在检查端点时读取工具列表
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
它在 1 项适用的基础检查中通过了 0 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
你需要填写:Authorization
它在作者的云端运行。通过互联网连接,无需安装,但你发送的内容会经过作者的服务器。
GitHub 仓库最后更新于–,最新版本(1.22.0)于3个月前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。它通过 URL 连接,所以接受远程 MCP 服务器的应用也可以使用,例如开启开发者模式的 ChatGPT。
同一分类中有:Spec Driven Development, Remote Desktop Commander, Usaspending
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
USAspending MCP — Federal spending data from USAspending.gov API
按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。
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.
curl -s -X POST https://api.statemind.ai/v1/keys
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.
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 mcp add --transport http python-code-validator https://api.statemind.ai/mcp --header "Authorization: Bearer msvc_free_…"~/.cursor/mcp.json, same block..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:
| 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.
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.
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.
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 $base/cursor/hooks.json -o .cursor/hooks.json
Project hooks run from the project root, which is why the command in cursor/hooks.json is a path relative to it. For a hook that applies to every project instead, put the script in ~/.cursor/hooks/ and the same block in ~/.cursor/hooks.json with the command python3 ./hooks/validate_written.py --cursor.
Configuring the server is not what gets it called: the instruction file is. AGENTS.md in this repository is that text, written to be dropped into any project under whichever name the client reads:
mkdir -p .github
curl -sf https://raw.githubusercontent.com/jkanselaar/python-code-validator/main/AGENTS.md \ | tee AGENTS.md CLAUDE.md GEMINI.md .github/copilot-instructions.md >/dev/null
Cursor reads rules with front matter instead, so that one is a separate file — copy .cursor/rules/python-code-validator.mdc into .cursor/rules/ of the project.
The short version, if you would rather add a line to instructions you already have:
Write what the code should do as
assertexamples before writing the code,
and pass them in
options.examples. Callvalidate_pythonafter every edit
and
execute_pythononce a function is finished, not again until what it
does has changed. When a call returns
fixed_code, take it — the service ran
it against your examples. Do not present code that came back
valid: false.
The service hands out the client, so a workflow needs no checkout of this repository and no secret:
- run: |
curl -sf https://api.statemind.ai/v1/client -o validate.py python3 validate.py --changed-against "origin/${{ 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:
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.
repos:
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.
A repository whose Python is checked on every pull request can say so:
[](https://api.statemind.ai/?src=badge)
curl -s https://api.statemind.ai/v1/validate \
-H "Authorization: Bearer $VALIDATOR_API_KEY" \ -H 'content-type: application/json' \ -d '{"code": "def f(:\n pass\n", "mode": "static"}'
mode is static, repair or execute; repair and execute need a configured key. Submitted code is not logged.
A refused call says what to do about it, so a caller with no operator to ask can resolve it itself:
{"error": "payment_required",
"remedy": {"action": "upgrade_key", "hint": "A free key covers static only. …"}}
A free key covers 25 static checks a day, and one address gets a few keys a day, so the allowance is a trial rather than a supply. Beyond it a key carries credits: a static check costs 1, a repair 3 and a sandboxed run 10, and an identical call repeated within ten minutes is answered from the first one for free.
Credits are bought with a card, without an invoice or anyone to ask:
curl -s -X POST https://api.statemind.ai/v1/keys/checkout \
-H 'content-type: application/json' \ -d '{"api_key": "'"$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/ 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.
MIT.