
Codereviewbuddy
io.github.detailobsessed由 GitHub 账号 detailobsessed 发布v0.37.0更新于 Oct 27, 2026
MCP server that helps AI coding agents interact with AI code reviewers on GitHub PRs
概览
让 AI 编程助手整理、阅读并回复 GitHub PR 上 AI 代码审查意见,并诊断 CI 失败的 MCP 服务器。
- 可以做什么
- 汇总审查状态,筛选出 PR 栈中真正需要处理的评论线程
- 读取完整线程历史,并回复行内线程、PR 级审查和机器人评论
- 检查 CI 状态,一次调用定位失败的运行、作业、步骤和错误行
- 查看 PR 栈活动时间线,扫描已合并 PR 的未解决评论,检查 PR 描述质量
- 显示当前配置,并提供只读的单 PR 审查资源和审查流程提示词
- 适用场景
- 适合助手处理由 AI 审查者评审的 GitHub 拉取请求时使用:找出仍需处理的评论、逐条回复,并在合并前查明 CI 失败原因。对堆叠 PR 也很有用,可判断整个栈何时稳定。
- 运行要求
- 以 Python 包形式通过 uvx 在本机运行,需要 Python 3.14 及以上。需要安装并已通过 gh auth login 登录的 GitHub CLI,无需个人访问令牌或配置文件。可选 CRB_* 环境变量用于调整行为。仅支持桌面 MCP 客户端。
安装
在 SourceWeft 中
- 打开 控制台中的 Codereviewbuddy,将其添加到工作区。
- 为需要使用其工具的对话启用该服务。
Desktop only,通过 STDIO。 STDIO 服务会启动本地进程,因此需要 SourceWeft 桌面宿主。
其他 MCP 客户端
参照 仓库 中的启动说明。
README
codereviewbuddy
[ci] [release] [documentation] [Python 3.14+] [FastMCP v3]
An MCP server that helps your AI coding agent manage PR review comments from any AI reviewer that uses GitHub's PR review infrastructure.
Features
Review comment management
- Triage review comments —
triage_review_commentsfilters to only actionable inline threads and includes direct GitHub URLs for each comment - Get thread details —
get_threadfetches full conversation history for any thread by node ID - Reply to anything — inline review threads (
PRRT_), PR-level reviews (PRR_), and bot issue comments (IC_) all routed to the correct GitHub API
CI & stack diagnosis
- Diagnose CI failures —
diagnose_cicollapses 3-5 sequentialghcommands into one call: finds the failed run, identifies failed jobs/steps, and extracts actionable error lines - Stack activity feed —
stack_activityshows a chronological timeline of pushes, reviews, labels, merges across all PRs in a stack with asettledflag for deciding when to proceed - Scan merged PRs —
list_recent_unresolvedcatches late review comments on already-merged PRs
Agent experience
- Recovery-guided errors — every tool handler classifies errors (auth, rate limit, not found, workspace, GraphQL, config) and returns actionable recovery hints so agents self-correct instead of retrying blindly
- Next-action hints — tool responses include
next_stepssuggestions guiding agents to the right follow-up tool call - Empty result messages — when results are empty, responses explain why and suggest what to try next
- GUI URLs — triage items include
comment_urlso agents can link users directly to the comment on GitHub - Tool classification tags — tools are tagged
query,command, ordiscoveryfor MCP clients that support filtering
Server features (FastMCP v3)
- Typed output schemas — all tools return Pydantic models with JSON Schema, giving MCP clients structured data instead of raw strings
- Progress reporting — long-running operations report progress via FastMCP context (visible in MCP clients that support it)
- Production middleware — ErrorHandling (transforms exceptions to clean MCP errors with tracebacks), Timing (logs execution duration for every tool call), and Logging (request/response payloads for debugging)
- Zero config auth — uses
ghCLI, no PAT tokens or.envfiles
CLI testing (free with FastMCP v3)
FastMCP v3 gives you terminal testing of the server with no extra code:
Prerequisites
- GitHub CLI (
gh) installed and authenticated (gh auth login) - Python 3.14+
Installation
This project uses uv. No install needed — run directly:
Or install permanently:
MCP Client Configuration
Quick setup (recommended)
One command configures your MCP client — no manual JSON editing:
With optional environment variables:
For any other client, generate the JSON config:
Restart your MCP client after installing. See uvx codereviewbuddy install --help for all options.
Manual configuration
If you prefer manual setup, add the following to your MCP client's config JSON:
All options enabled:
The server auto-detects your project from MCP roots (sent per-window by your client). This works correctly with multiple windows open on different projects — no env vars needed.
Why
@latest? Without it,uvxcaches the first resolved version and never upgrades automatically.
From source (development)
For local development, use uv run --directory to run the server from your checkout instead of the PyPI-published version. Changes to the source take effect immediately — just restart the MCP server in your client.
Troubleshooting
If your MCP client reports No module named 'fastmcp.server.tasks.routing', the runtime has an incompatible FastMCP. Fixes:
- Prefer
uvx codereviewbuddy@latestin MCP client config. - For local source checkouts, launch with
uv run --directory /path/to/codereviewbuddy codereviewbuddy. - Reinstall to refresh cached deps:
uv tool install --reinstall codereviewbuddy.
MCP Tools
MCP Resources
MCP Prompts
Configuration
codereviewbuddy works zero-config with sensible defaults. All configuration is via CRB_* environment variables in the "env" block of your MCP client config — no config files needed. Nested settings use __ (double underscore) as a delimiter. See the dev setup above for a fully-commented example.
All settings
Typical workflow
Each tool response includes next_steps hints guiding the agent to the right follow-up call. For stacked PRs, all query tools auto-discover the stack when pr_numbers is omitted.
Development
Testing
Quality checks
Architecture
The server is built on FastMCP v3 with a clean separation:
server.py— FastMCP server with tool registration, middleware, instructions, and recovery-guided error handlingconfig.py— Configuration (CRB_*env vars via pydantic-settings)tools/— Tool implementations (comments.py,stack.py,ci.py,descriptions.py)gh.py— Thin wrapper around theghCLI for GraphQL and REST callsmodels.py— Pydantic models for typed tool outputs withnext_stepsandmessagefields for agent guidance
All blocking gh CLI calls are wrapped with call_sync_fn_in_threadpool to avoid blocking the async event loop.
Template Updates
This project was generated with copier-uv-bleeding. To pull the latest template changes:
来源:README.md,提交 4790956
工具
0版本历史
1- v0.37.0最新Sep 16, 2026
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