Mcp-server
Verified Safeby dvy246
Overview
A Streamlit and CLI-based chat interface leveraging the Model Context Protocol (MCP) to connect Google's Gemini LLM with various tools and servers for tool-augmented conversational AI.
Installation
streamlit run app.pyEnvironment Variables
- GEMINI_API_KEY
- UV_PATH
- PYTHON_PATH
- MANIM_EXECUTABLE
- MATH_SERVER_PATH
- MANIM_SERVER_PATH
Security Notes
The core application code appears secure, utilizing `yaml.safe_load` for configuration and loading API keys from environment variables. There are no obvious 'eval' or malicious patterns. However, the Model Context Protocol (MCP) design inherently involves executing external processes (local or remote) as 'tools' configured by the user (e.g., `MATH_SERVER_PATH`, `MANIM_SERVER_PATH`, or the remote `expense` server). While this is the intended functionality, it means the overall security depends heavily on the trustworthiness and proper securing of these external tools/servers that the application interacts with. Users must ensure that the configured server paths point to safe executables/scripts.
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