Minimalist examples to provide your own MCP servers to your local llm models.
pydantic-ai-researcher is a research system that orchestrates an asynchronous loop between two specialized agents: a research agent and an evaluator agent. The research agent answers complex queries using external MCP servers, while the evaluator agent assesses and refines these answers, iterating until a satisfactory response is attained.
MCP for Root Signals Evaluation Platform
Repo for demonstrating simple Model Context Protocol (MCP) server with several Agent Frameworks
A lightweight prototype demonstrating how to integrate an LLM (via OpenAI) with a Model Context Protocol (MCP) server to extract real-time weather data by scraping and processing open web content using HTML parsing and caching.
This repo makes use of MCP servers to seamlessly integrate multiple tools for the agent.
Simple MCP Client-Server example
Created sample project for pydantic agent with local ollama model with mcp server integration.
A model-agnostic Message Control Protocol (MCP) server that enables seamless integration with various Large Language Models (LLMs) like GPT, DeepSeek, Claude, and more.
Unlock 650+ MCP servers tools in your favorite agentic framework.
Showcase: Let an agentic coding assistant create a small web search agent with Pydantic AI using MCP server