"Model Context Protocol (MCP) Servers Repository" matching MCP servers:

MCP server enabling real-time weather queries via Tavily API and internet usage data by country via MongoDB.

A production-ready MCP server template that connects LLMs and AI agents to external data, tools, and services with built-in OAuth 2.1 authentication, Redis-backed session management, and a modular tools engine.

A Python-based server for managing and analyzing code context for AI-assisted development. Provides real-time code analysis, project structure analysis, dependency tracking, and secure API endpoints.

Enables AI agents to compose MCP tool calls into Unix-style pipelines, executing complex workflows server-side and returning only the final result.

An MCP server that integrates AI retrievals with NASA's Common Metadata Repository (CMR), allowing users to search NASA's catalog of Earth science datasets through natural language queries.

A production-grade MCP server for managing git projects, offering dynamic tool selection and enterprise-grade security.

MCP server that provides a citation-first memory layer for AI agents, enabling verified search across Git-backed repositories and optional conversation memory. It exposes tools for doctor, sync, search, get, init, and ingest, returning JSON results with verified citations or abstain status.

Enables AI agents to search, read, and traverse a local knowledge base of Markdown files using full-text search and relationship graph, reducing token usage.

Enables AI clients to inspect Python repositories read-only through eight MCP tools that expose symbols, cited source excerpts, import dependencies, and supported static caller relationships without importing or executing the code.

Provides a standardized protocol for tool invocation, enabling an AI system to search the web, retrieve information, and provide relevant answers through integration with LangChain, RAG, and Ollama.

A demonstration server for the Model Context Protocol (MCP) that exposes calculator and Yahoo Finance tools, allowing LLMs to interpret natural language requests and make tool calls via the MCP standard.

A secure multi-tenant server that provides real-time context to LLMs via REST API, using JWT authentication and PostgreSQL row-level security for tenant isolation.

A middleware server that intelligently routes AI model queries to appropriate data sources, providing contextual information to enhance AI responses.

A conversational application server that integrates LLM capabilities via Ollama with vector memory context, supporting multiple users, sessions, automatic history summarization, and a plugin system for executing real actions.

Enables creating Spotify playlists based on text descriptions by connecting Cursor editor to Spotify's API through OAuth authentication.

This server facilitates the invocation of AI models from providers like Anthropic, OpenAI, and Groq, enabling users to manage and configure large language model interactions seamlessly.

A lightweight service that enables AI assistants to execute AWS CLI commands through the Model Context Protocol (MCP), allowing AI tools to retrieve AWS documentation and interact with AWS services.

A server that implements the Model Context Protocol for Schwab API, allowing access to account information, positions, stock quotes, and order/transaction history designed for integration with Large Language Models.

A server implementation demonstrating how AI models can interact with external tools and services through Model Context Protocol, featuring integrations for calculator functions, GitHub repositories, and Google Maps searches.

Enables natural-language analysis of GitHub repositories by exposing repository metadata, source code retrieval, search, and file reading as MCP tools, with answers grounded in the actual repository content.

Enterprise-grade intent routing gateway implementing the Model Context Protocol (MCP) spec, optimizing context by routing queries to specialized sub-nodes to reduce token overhead by 85% with negligible latency overhead.

Implements a secure message communication protocol for handling exchanges between the banking chatbot and Azure OpenAI, providing message queuing, reliability, and detailed logging.

A stateful gateway server for AI applications that solves the memory limitations of Large Language Models by maintaining separate conversation contexts for each user.

A Python implementation of the Model Context Protocol (MCP) server that enables searching and extracting information from arXiv papers, designed to be extensible with additional MCP tools.

A Python implementation of the MCP server that enables AI models to connect with external tools and data sources through a standardized protocol, supporting tool invocation and resource access via JSON-RPC.

A server exposing intelligent tools for enhancing RAG applications with entity extraction, query refinement, and relevance checking capabilities.

An MCP server that seats multiple LLMs as a council, letting your assistant query them in parallel or in sequence, relay answers for cross-critique, and merge conclusions within one conversation.

Local-first shared memory and coordination layer for AI coding agents, with repository evidence, reservations, handoffs, code graph context, and dashboard review backed by PostgreSQL/pgvector.

MCP server that pings 130+ free coding LLM models across 17 providers in real-time, ranks them by latency, and helps AI agents pick the fastest available model.

Trust, identity, and reputation infrastructure for AI agents. Register agents with W3C DID (Ed25519), check EigenTrust reputation scores, submit peer attestations, search agents by capability, and verify IPFS-anchored audit trails. 11 tools.