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PopNx MCPMCP servers for people who use AI · explained in plain words

Codereviewbuddy

by detailobsessedversion 0.37.0i★ –iRuns on your computer
Registry nameio.github.detailobsessed/codereviewbuddy

Install

Overview

Description from the maker (original English)

MCP server that helps AI coding agents interact with AI code reviewers on GitHub PRs

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Developer tools

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • The registry lists no key to fill in.

You need

  • PyPIPython’s uv installed (for the uvx command)

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "codereviewbuddy": {
      "command": "uvx",
      "args": [
        "codereviewbuddy"
      ]
    }
  }
}

Run this in your terminal

claude mcp add codereviewbuddy -- uvx codereviewbuddy

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "codereviewbuddy": {
      "command": "uvx",
      "args": [
        "codereviewbuddy"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "codereviewbuddy": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "codereviewbuddy"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account detailobsessed, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Developer toolsi

  • More stars than 0% of the other 1394 servers in this category
  • Published to the registry more recently than 13% of the other 1394 servers in this category
  • Basic checks equal to or better than 100% of the other 1394 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Codereviewbuddy safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.37.0) reached the registry 7 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.

What can I use instead?

In the same category: GitHub, Desktop Commander, Cloudflare MCP

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

GitHub

by github

GitHub’s official server lets AI read and manage code, issues and pull requests in your account. Use GitHub’s hosted version or run it locally with Docker.

Computer or cloud★ 34,245MITUpdated 3 days ago
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Desktop Commander

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MCP server for terminal commands, file operations, and process management

Runs on your computer★ 10,225MITUpdated 15 days ago
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Cloudflare MCP

by cloudflare

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Runs in the cloud★ 4,446Apache-2.0Updated 14 months ago
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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

codereviewbuddy

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_comments filters to only actionable inline threads and includes direct GitHub URLs for each comment
  • Get thread details — get_thread fetches 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_ci collapses 3-5 sequential gh commands into one call: finds the failed run, identifies failed jobs/steps, and extracts actionable error lines
  • Stack activity feed — stack_activity shows a chronological timeline of pushes, reviews, labels, merges across all PRs in a stack with a settled flag for deciding when to proceed
  • Scan merged PRs — list_recent_unresolved catches 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_steps suggestions 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_url so agents can link users directly to the comment on GitHub
  • Tool classification tags — tools are tagged query, command, or discovery for 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 gh CLI, no PAT tokens or .env files
CLI testing (free with FastMCP v3)

FastMCP v3 gives you terminal testing of the server with no extra code:

# List all tools with their signatures

fastmcp list codereviewbuddy.server:mcp

Call a tool directly from the terminal

fastmcp call codereviewbuddy.server:mcp triage_review_comments pr_numbers='[42]'

Inspect server metadata

fastmcp inspect codereviewbuddy.server:mcp

Run with MCP Inspector for interactive debugging

fastmcp dev codereviewbuddy.server:mcp

Prerequisites

Installation

This project uses uv. No install needed — run directly:

uvx codereviewbuddy

Or install permanently:

uv tool install codereviewbuddy

MCP Client Configuration

Quick setup (recommended)

One command configures your MCP client — no manual JSON editing:

uvx codereviewbuddy install claude-desktop

uvx codereviewbuddy install claude-code uvx codereviewbuddy install cursor uvx codereviewbuddy install windsurf uvx codereviewbuddy install windsurf-next

With optional environment variables:

uvx codereviewbuddy install windsurf \

--env CRB_SELF_IMPROVEMENT__ENABLED=true

For any other client, generate the JSON config:

uvx codereviewbuddy install mcp-json          # print to stdout

uvx codereviewbuddy install mcp-json --copy # copy to clipboard

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:

{

"mcpServers": { "codereviewbuddy": { "command": "uvx", "args": ["codereviewbuddy@latest"], "env": { // All CRB_* env vars are optional — zero-config works out of the box. // See Configuration section below for the full list. } } } }

All options enabled:

{

"mcpServers": { "codereviewbuddy": { "command": "uvx", "args": ["codereviewbuddy@latest"], "env": { // GitHub logins considered "ours" for triage filtering (comma-separated) "CRB_OWNER_LOGINS": "alice,bob", // Enable PR description quality checks "CRB_PR_DESCRIPTIONS__ENABLED": "true", // Agents suggest Linear issues when they hit server gaps "CRB_SELF_IMPROVEMENT__ENABLED": "true" } } } }

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, uvx caches 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.

{

"mcpServers": { "codereviewbuddy": { "command": "uv", "args": ["run", "--directory", "/path/to/codereviewbuddy", "codereviewbuddy"], "env": { // Same CRB_* env vars as above, plus dev-specific settings: "CRB_SELF_IMPROVEMENT__ENABLED": "true" } } } }

Troubleshooting

If your MCP client reports No module named 'fastmcp.server.tasks.routing', the runtime has an incompatible FastMCP. Fixes:

  1. Prefer uvx codereviewbuddy@latest in MCP client config.
  2. For local source checkouts, launch with uv run --directory /path/to/codereviewbuddy codereviewbuddy.
  3. Reinstall to refresh cached deps: uv tool install --reinstall codereviewbuddy.

MCP Tools

ToolTagsDescription
summarize_review_statusquery, discoveryLightweight stack-wide overview — start here
triage_review_commentsqueryOnly actionable inline threads needing attention
get_threadqueryFull thread details by node ID — use after triage for conversation history
reply_to_commentcommandReply to inline threads (PRRT_), PR-level reviews (PRR_), or bot comments (IC_)
diagnose_ciqueryDiagnose CI failures — finds the failed run, jobs, steps, and error lines in one call
check_ci_statusqueryLightweight CI pass/fail/pending check for a PR — use before merging
stack_activityqueryChronological activity feed across a PR stack with a settled flag
list_recent_unresolvedqueryScan recently merged PRs for unresolved review threads
review_pr_descriptionsqueryAnalyze PR descriptions for quality issues (empty body, boilerplate, missing linked issues)
show_configdiscoveryShow active configuration with human-readable explanation

MCP Resources

ResourceDescription
pr://{owner}/{repo}/{pr_number}/reviewsRead-only review summary for a single PR

MCP Prompts

PromptDescription
review_stackFull review pass workflow — summarize, triage, fix, reply, verify
pr_review_checklistPre-merge quality checklist (review threads, PR hygiene, CI, tests)
ship_stackPre-merge sanity check workflow before merging a PR stack

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
Env varTypeDefaultDescription
CRB_PR_DESCRIPTIONS__ENABLEDbooltrueWhether review_pr_descriptions tool is available
CRB_SELF_IMPROVEMENT__ENABLEDboolfalseAgents suggest Linear issues when they encounter server gaps
CRB_OWNER_LOGINScomma-separated[]GitHub usernames considered "ours" for triage filtering (e.g. alice,bob)

Typical workflow

1. summarize_review_status()                     # Stack-wide overview — start here
  1. triage_review_comments(pr_numbers=[42, 43]) # Only actionable threads needing attention
  2. # Fix bugs flagged by triage, then:
  3. reply_to_comment(42, thread_id, "Fixed in ...") # Reply explaining the fix
  4. diagnose_ci(pr_number=42) # If CI fails, diagnose in one call

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

git clone https://github.com/detailobsessed/codereviewbuddy.git

cd codereviewbuddy uv sync

Testing
poe test          # Run tests (excludes slow)

poe test-cov # Run with coverage report poe test-all # Run all tests including slow

Quality checks
poe lint          # ruff check

poe typecheck # ty check poe check # lint + typecheck poe prek # run all pre-commit hooks

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 handling
  • `config.py` — Configuration (CRB_* env vars via pydantic-settings)
  • `tools/` — Tool implementations (comments.py, stack.py, ci.py, descriptions.py)
  • `gh.py` — Thin wrapper around the gh CLI for GraphQL and REST calls
  • `models.py` — Pydantic models for typed tool outputs with next_steps and message fields 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:

copier update --trust .
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