What are the prerequisites to run the agent?
Python 3.9 or higher, Git, a virtual environment (recommended), and Node.js for MCP.
@gokborayilmaz
基本情報
This AI agent analyzes code repositories, detects potential security vulnerabilities, reviews code quality, and suggests fixes based on Sentry error logs using Sentry and GitHub MCP servers!
ツール一覧はまだありません
この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。
ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。
This AI agent analyzes code repositories, detects potential security vulnerabilities, reviews code quality, and suggests fixes based on Sentry error logs. It integrates with GitHub and Sentry MCP servers, and is part of the "A New AI Agent Every Day!" series.
Install prerequisites (Python 3.9+, Git, virtual environment, Node.js for MCP), clone the repository, install dependencies with pip install -r requirements.txt, and create a .env file with Azure OpenAI, GitHub, and Sentry tokens. Start the FastAPI server with uvicorn upsonicai:app --reload and open the UI at http://127.0.0.1:8000/. Configure MCP servers by adding GitHub and Sentry entries to your MCP configuration file.
Python 3.9 or higher, Git, a virtual environment (recommended), and Node.js for MCP.
You need to set `AZURE_OPENAI_ENDPOINT`, `AZURE_OPENAI_API_VERSION`, `AZURE_OPENAI_API_KEY`, `GITHUB_PERSONAL_ACCESS_TOKEN`, and `SENTRY_AUTH_TOKEN` in a `.env` file.
Run `uvicorn upsonicai:app --reload` in the project root, then open `http://127.0.0.1:8000/` in your browser.
Modify your MCP configuration to include a `github` server using `npx` and a `sentry` server using `python -m mcp_server_sentry`, each with the appropriate token.

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