Provides tools for interacting with GitHub's API, enabling management of repositories, issues, pull requests, and other GitHub resources programmatically through the PyGithub SDK.
Enables management and interaction with Kubernetes clusters, providing access to pods, services, deployments, and other Kubernetes resources through the official Kubernetes Python client.
Integrates with OpenAI's API for calling language models, with configurable model selection and API key authentication for AI-powered operations.
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:
Kubernetes –
kubernetes-client/pythonGitHub –
PyGithubAzure – selected services from
azure-sdk-for-python
Quick Start
Environment Variables
Variable | Description |
| API key for calling OpenAI models |
| (optional) Model name, defaults to
|
| Path to kubeconfig for Kubernetes adapter |
| PAT for GitHub adapter |
/
/
| Credentials for Azure SDK |
Roadmap
Reflective adapter loading for arbitrary SDKs
Streaming function call extraction via LLM
Full MCP compliance tests
This server cannot be installed
remote-capable server
The server can be hosted and run remotely because it primarily relies on remote services or has no dependency on the local environment.
Dynamically exposes Python SDKs (Kubernetes, GitHub, Azure) through an agent-friendly gRPC interface. Enables interaction with cloud services and platforms using natural language by automatically converting SDK functionality into callable functions.