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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. Kuberneteskubernetes-client/python

  2. GitHubPyGithub

  3. Azure – selected services from azure-sdk-for-python

Quick Start

# 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

-
security - not tested
-
license - not tested
-
quality - not tested

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MCP directory API

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curl -X GET 'https://glama.ai/api/mcp/v1/servers/sarptandoven/generalized-mcp-converter'

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