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MCP Servers
The Model Context Protocol (MCP) provides a standardized way to connect AI models to external tools and data sources. MCP Servers are standalone programs that expose specific capabilities via the MCP protocol.
Official MCP Servers
Server Description Key Features Filesystem Secure file system operations Read, write, list files GitHub GitHub repository integration Code search, file operations Git Git operations and history Commits, diffs, logs PostgreSQL PostgreSQL database access Query execution, schema inspection SQLite SQLite database operations Local database queries Brave Search Web search via Brave API Real-time search results Google Maps Location and mapping services Geocoding, directions
MCP Client Applications
Application Description Key Features Claude Desktop Official Anthropic desktop app Native MCP support Cursor AI-powered IDE MCP integration for coding Zed Collaborative code editor MCP server support Windsurf AI coding assistant Built-in MCP capabilities
MCP Development SDKs
SDK Language Key Features Python SDK Python Server and client implementation TypeScript SDK TypeScript/JavaScript Full MCP protocol support Go SDK Go Lightweight implementation Rust SDK Rust High-performance implementation Java SDK Java Enterprise integration
Development Frameworks
RAG & Agent Frameworks
Tool Description Key Features LangChain General purpose framework for RAG and agentic applications Chains, agents, memory LlamaIndex Framework for RAG and Agentic RAG applications Data connectors, indexing AutoGen Framework for automated agentic applications Multi-agent conversations CrewAI Multi-agent orchestration framework Role-based agents Smolagents Minimalist AI agent framework by Hugging Face Lightweight, simple API
Observability & Monitoring
Tool Description Key Features Arize Phoenix Open-source observability for LlamaIndex and RAG Tracing, evaluation LangFuse Open-source observability for agents and LLM calls Self-hosted, analytics
Utilities & Infrastructure
Tool Description Key Features LiteLLM Universal API for LLM deployments 100+ LLM support ONNX Runtime Cross-platform ML inference Optimized performance Transformers.js JavaScript ML library Browser & Node.js
Open Source Models
Large Language Models
Model Provider Key Features Llama Meta Open weights, commercial use Mistral Mistral AI Efficient, multilingual DeepSeek DeepSeek Deep learning focus Qwen Alibaba Large context windows
Specialized Models
Model Purpose Key Features Whisper Speech recognition Multilingual, robust Stable Diffusion Image generation Open weights, customizable
Model Runners
Tool Description Key Features Ollama Run LLMs locally Easy setup, model library LM Studio Desktop app for local LLMs GUI, model management
Development Environments
Tool Description Key Features Zed High-performance collaborative code editor Rust-based, fast Void Modern AI-first code editor Open source, extensible
Tool Description Key Features Aider Command-line AI coding assistant Git integration, pair programming SWE-Agent Software Engineer Agent Autonomous coding
Infrastructure & Deployment
Tool Description Key Features vLLM High-throughput LLM serving PagedAttention, fast inference Text Generation Inference Production-ready LLM serving Hugging Face models LocalAI Self-hosted OpenAI-compatible API Drop-in replacement
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