#async

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.

🔍 FastMCP-powered documentation search engine that provides unified access to multiple framework docs (Next.js, Tailwind, Framer Motion, etc.) with intelligent name resolution and async processing.

Asynchronous Python library for building Model Context Protocol (MCP) servers and clients over HTTP/SSE, ideal for AI agents, tool integrations, and chatbot ecosystems.

Some examples to build server, client test in model context protocol. Một số ví dụ sử dụng MCP

Compose and generate effortlessly MCP servers from any OpenAPI specifications

MCP Server to get access to Reviews that are posted using the Async Praise Rebuke App

A high-performance, asynchronous Model Context Protocol (MCP) server that integrates with JIRA using stdio transport

A Model Context Protocol (MCP) Gateway. Serves as a central management point for tools, resources, and prompts that can be accessed by MCP-compatible LLM applications. Converts REST API endpoints to MCP, composes virtual MCP servers with added security and observability, and converts between protocols (stdio, SSE).

Revolutionary MCP server with surgical precision editing for Confluence - industry's first XML-aware selective content modification MCP system for AI assistants

Compose and generate effortlessly MCP servers from any OpenAPI specifications