
Codereviewbuddy
io.github.detailobsessedPublished by GitHub account detailobsessedv0.37.0Updated Oct 27, 2026
MCP server that helps AI coding agents interact with AI code reviewers on GitHub PRs
Overview
MCP server that lets an AI coding agent triage, read and reply to GitHub PR review comments from AI reviewers, and diagnose CI failures.
- What you can do
- Summarize review status and triage actionable inline review threads across a PR stack
- Read full thread history and reply to inline threads, PR-level reviews and bot comments
- Check CI status and diagnose failed runs, jobs, steps and error lines
- Track stack activity, scan recently merged PRs for unresolved threads, and review PR description quality
- Show active configuration and expose a read-only per-PR review resource plus review workflow prompts
- When to use it
- Useful when an agent works on GitHub pull requests reviewed by AI reviewers and needs to find which comments still need action, answer them, and check why CI failed before merging. Also handy for stacked PRs where the agent must decide when a stack has settled.
- Requirements
- Runs locally as a Python package via uvx (Python 3.14+). Requires the GitHub CLI (gh) installed and authenticated with gh auth login; no personal access tokens or config files. Optional CRB_* environment variables tune behavior. Desktop MCP client only.
Installation
In SourceWeft
- Open Codereviewbuddy in the dashboard and add it to a workspace.
- Enable the server for the chats that should use its tools.
Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.
Other MCP clients
Follow the launch instructions in the repository.
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:
Source: README.md at commit 4790956
Tools
0Version history
1- v0.37.0LatestSep 16, 2026
Score
50% of the applicable checks met
How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.
- Reached in the last 30 days25 pts
Keep the endpoint answering the MCP handshake; SourceWeft probes it every 30 days.
- Auth declared10 pts
Declare the credential headers in the registry entry, or keep the endpoint answering the probe so its auth can be classified.
- Tools listed15 pts
Answer tools/list without a credential, or ship a package that starts in a sandbox without one.
- DescriptionRequired15 pts
- Logo10 pts
- Documentation15 pts
- License10 pts