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AI code review grounded in your repo history. Supports Test Gen and Security Audits.
AI code review grounded in your repo history. Supports Test Gen and Security Audits.
This MCP server has reasonable structure but exhibits several concerning patterns: unauthenticated telemetry collection with user fingerprinting, network calls that bypass normal MCP channels, overly broad LLM provider dependencies, and insufficient input validation in critical inference paths. While no malicious code is evident, the telemetry mechanism and external network pinging raise privacy concerns, and the inference layer's reliance on environment variables for API keys without secure storage guidance creates security gaps. The code quality is fair, but permissions exceed what a pure context retrieval tool should require. Supply chain analysis found 11 known vulnerabilities in dependencies (0 critical, 3 high severity).
6 files analyzed ยท 21 issues found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
This plugin requests these system permissions. Most are normal for its category.
Add this to your MCP configuration file:
{
"mcpServers": {
"io-github-paarths-collab-github-pr-context-mcp": {
"args": [
"github-pr-context-mcp"
],
"command": "uvx"
}
}
}From the project's GitHub README.
This repository provides two ways to leverage your GitHub PR history in your AI workflows. Choose the tool version that matches your architecture.
The Hardened Pure Context Retrieval Engine.
Designed for users who want maximum speed and reliability by offloading reasoning to their IDE agent (Cursor, Claude Desktop, Windsurf). It focuses exclusively on high-performance retrieval and data pruning.
tenacity retries and non-blocking I/O for heavy repository indexing.[!NOTE] v0.3.0 is currently in pre-release and is not yet live on PyPI. To use the hardened v0.3.0 engine today, you must install it from source:
Fork this repository to your own account on GitHub.
Clone and Checkout the release branch:
git clone https://github.com/YOUR_USERNAME/github-pr-context-mcp.git cd github-pr-context-mcp git checkout v0.3.0-hardeningInstall via pipx (the whole command):
pipx install -e .This links the
github-pr-context-mcpcommand to your local repository folder.Verify Version:
github-pr-context-mcp --help
The Integrated Reasoning Agent.
Designed for users who prefer the server to handle LLM inference internally. This version includes the legacy inference layer and supports direct configuration of OpenAI and Anthropic API keys.
inference/ module for direct model interactions.pipx install github-pr-context-mcp==0.2.9
The v0.3.0 version only requires a GitHub Token.
Environment Variable:
GITHUB_TOKEN=ghp_your_token_here
GitHub PR Review Context MCP gives AI assistants institutional review memory.
It fetches your repository's PR history (descriptions, review threads, comments), transforms them into searchable documents, and provides high-density Context Materials to your IDE agent.
| Capability | What It Delivers |
|---|---|
| Historical Retrieval | Semantic search across prior PR comments and review summaries. |
| Code Review Material | Raw JSON context for the agent to perform grounded code reviews. |
| Rules Material | High-density data for the agent to synthesize .cursorrules or CLAUDE.md. |
| Grounded Generation | Context materials for generating code that matches team style. |
| Namespace Isolation | Strict isolation between users/teams using Gmail-based identity. |
# Run instantly
uvx github-pr-engine
# OR Install permanently
pipx install github-pr-engine
The only required configuration is your GitHub token.
Environment Variable:
GITHUB_TOKEN=ghp_your_token_here
The server provides tools that return raw JSON context objects. The IDE agent then uses its own intelligence to process this data.
| Tool | Action | typical Use Case |
|---|---|---|
ensure_repo_ready | Index a repo and ensure it's ready. | Onboarding a new repository. |
review_code_with_history | Get historical review material for a snippet. | "Review this code based on team history." |
get_repo_rules_material | Get material to write .cursorrules. | "Write a rules file for this repo." |
get_team_review_patterns | Get raw patterns for summarization. | "What are the common review themes?" |
generate_code_from_history | Get context for grounded generation. | "Write this feature in our team's style." |
semantic_search_reviews | Search past PR comments by meaning. | Manual history lookup. |
list_indexed_repos | View all currently indexed repositories. | Storage management. |
MIT
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