What are the prerequisites to run the agent?
Python 3.9 or higher, Git, a virtual environment (recommended), and Node.js for MCP.
@gokborayilmaz
Basic information
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!
No standard config provided
This server doesn't expose a parseable MCP config block in its README. See the repository for install instructions.
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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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