critique-mcp

critique-mcp

Enables an agent to review pull requests by listing changed files, checking test coverage, linting changed Python files with Ruff, and posting a real review to GitHub.

Category
访问服务器

README

critique-mcp

CI

An MCP server that gives an agent the tools to actually review a pull request — not just summarize the diff, but pull it apart, lint the changed code, flag when tests weren't updated, and post a real review back to GitHub.

Python · Model Context Protocol · GitHub REST API


Tools

Tool What it does
list_changed_files Files changed in a PR, with diff stats and patch text
check_test_coverage Flags PRs that change source files without touching any test file
run_linter Runs ruff against every changed Python file at the PR's head commit
post_review Submits a real review (comment / approve / request changes) on the PR

Each tool is a thin, independently testable function — run_linter doesn't know how check_test_coverage works, and neither talks to GitHub except through GitHubClient. The agent decides how to combine them; this server just gives it hands.

check_test_coverage is a PR-level heuristic, not per-file coverage instrumentation: it flags "source files changed, zero test files touched anywhere in this PR," the same coarse signal tools like Danger.js use. A PR that changes five source files and touches one unrelated test won't be flagged — a precise version would need real coverage data, not filenames.

Why this exists

I've found and fixed exactly the kind of bug these tools catch, by hand, in other people's PRs — a vacuous-pass test assertion in chroma-core/chroma, a validator that only checked one element of a list in weaviate-python-client, a float-precision bug in qdrant-client. This turns that review process into tools an agent can call directly, instead of a human doing the same checks by hand every time.

Setup

Requires Python 3.11+, ruff on PATH, and a GitHub personal access token with repo scope (read-only is enough unless you want post_review to work).

cp .env.example .env      # then add your token to .env
python -m venv .venv && source .venv/bin/activate   # Windows: .venv\Scripts\activate
pip install -r requirements.txt

Usage

Add it to Claude Desktop / Claude Code's MCP config:

{
  "mcpServers": {
    "critique": {
      "command": "python",
      "args": ["-m", "critique_mcp.server"],
      "env": { "GITHUB_TOKEN": "ghp_..." }
    }
  }
}

Then ask the agent to use it: "Use critique to review PR #42 on owner/repo — check for lint issues and missing tests, then post a summary review."

Tests

pytest

Every GitHub API call is mocked in tests — nothing here makes a live network call unless you run the server itself.

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选