Generalized MCP Server

# Generalized MCP Server This project implements a generalized **Model Control Plane (MCP)** server that dynamically exposes the full surface area of arbitrary Python SDKs via an agent‐friendly gRPC interface. Current reference adapters: 1. **Kubernetes** – `kubernetes-client/python` 2. **GitHub** – `PyGithub` 3. **Azure** – selected services from `azure-sdk-for-python` ## Quick Start ```bash # Clone & enter repo git clone <repo-url> generalized_mcp && cd generalized_mcp # Create virtualenv python -m venv .venv && source .venv/bin/activate # Install deps pip install -r requirements.txt # Generate gRPC stubs (once per proto change) make proto # Run MCP server (listens on :50051 by default) python -m src.server ``` ## Environment Variables | Variable | Description | |----------|-------------| | `OPENAI_API_KEY` | API key for calling OpenAI models | | `OPENAI_MODEL` | (optional) Model name, defaults to `gpt-3.5-turbo-1106` | | `KUBECONFIG` | Path to kubeconfig for Kubernetes adapter | | `GITHUB_TOKEN` | PAT for GitHub adapter | | `AZURE_CLIENT_ID` / `AZURE_TENANT_ID` / `AZURE_CLIENT_SECRET` | Credentials for Azure SDK | ## Roadmap - [ ] Reflective adapter loading for arbitrary SDKs - [ ] Streaming function call extraction via LLM - [ ] Full MCP compliance tests