Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
🚀 GitHub PR Context Tools
This repository provides two ways to leverage your GitHub PR history in your AI workflows. Choose the tool version that matches your architecture.
💎 GitHub PR Context (v0.3.0)
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.
✨ Key Features (v0.3.0):
- Asynchronous Hardening: Built with
tenacityretries and non-blocking I/O for heavy repository indexing. - Optimized for IDE Agents: Prunes redundant metadata and strips useless fields to save token space in your prompt.
- Modern Infrastructure: Uses SQLite-backed cursors for progress tracking and global thread locks for data safety.
- Pure Context: No built-in LLM dependencies; feeds raw, high-quality historical patterns directly to your primary agent.
🛠 Installation (Pre-release Source Install)
[!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:
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1. Fork this repository to your own account on GitHub. 2. Clone and Checkout the release branch: ``bash git clone https://github.com/YOUR_USERNAME/github-pr-context-mcp.git cd github-pr-context-mcp git checkout v0.3.0-hardening`3. **Install via pipx** (the whole command):`bash pipx install -e .`*This links thegithub-pr-context-mcp` command to your local repository folder.*
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4. Verify Version: ``bash github-pr-context-mcp --help ``🏛 Legacy Context Agent (v0.2.9)
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.
✨ Key Features (v0.2.9):
- Internal Inference: Can perform analysis and reviews directly using its own configured LLM provider.
- All-in-One Logic: Includes the legacy
inference/module for direct model interactions. - Proven Stability: The original stable version of the tool.
🛠 Installation
pipx install github-pr-context-mcp==0.2.9🛠️ Configuration (v0.3.0)
The v0.3.0 version only requires a GitHub Token.
Environment Variable: GITHUB_TOKEN=ghp_your_token_here
Overview
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.
Core Value
- Historical Evidence: Tools return raw JSON "historical facts" (what reviewers cared about in the past).
- Team Alignment: Your IDE agent uses this evidence to match your team's specific standards and architectural patterns.
- High Performance: Optimized for fast retrieval and background indexing to prevent tool timeouts.
Key Capabilities
| 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. |
🚀 Quick Start
🚀 Recommended Installation (uvx / pipx)
# Run instantly
uvx github-pr-engine
# OR Install permanently
pipx install github-pr-engine🛠️ Configuration
The only required configuration is your GitHub token.
Environment Variable: GITHUB_TOKEN=ghp_your_token_here
🧰 Tools Reference (Pure Context)
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. |
📖 Documentation
- 🏗️ Architecture & Pipeline — How the Pure Context engine works.
- 🛠️ Quick Start Guide — Detailed setup instructions.
- 🚀 Roadmap — Future development plans.
📣 Community & Feedback
- Feedback: Please open an issue or start a discussion if you have ideas or encounter bugs.
- Star ⭐: If this tool saves you time, give it a star!
⚖️ License
MIT