Awesome GitHub RepositoriesModel Context Protocol Servers

This project is a curated library of community-driven prompt templates and personas designed to improve interactions with large language models. It functions as a prompt engineering guide, providing interactive tutorials and examples to teach advanced design and reasoning techniques. The library can operate as a Model Context Protocol server, providing a standardized interface for AI tools and agents to access prompt data as a service. For organizations, it offers a self-hosted repository option that allows for private deployment on internal infrastructure with custom authentication and data

This platform serves as a centralized management system for organizing, refining, and versioning AI instructions and agent skills. It functions as a repository that enables users to store, categorize, and retrieve structured prompts, ensuring consistent performance across various artificial intelligence models. By integrating with the Model Context Protocol, the system allows external AI assistants and development environments to discover and access these instruction libraries directly. The platform distinguishes itself through its focus on prompt engineering and automated refinement, utilizi

Dify is an open-source platform for building, orchestrating, and deploying generative AI applications and autonomous agents. It provides a visual development environment that allows users to design complex, multi-step logic chains and conversational flows, which can then be published as APIs, web interfaces, or embedded widgets. The platform acts as a centralized infrastructure layer, managing model connections, prompt templates, and knowledge retrieval to support scalable AI-powered services. What distinguishes the platform is its focus on stateful application design and workflow orchestrati

Odysseus is a self-hosted AI workspace and autonomous agent framework designed for deploying and managing large language models. It serves as a centralized platform for orchestrating agentic tasks, utilizing a model context protocol server to connect AI models to external system utilities, browser automation, and local hardware. The system distinguishes itself through a combination of retrieval-augmented generation and a RAG knowledge base, using vector stores and local embeddings to provide persistent semantic memory. It further integrates AI-driven communication management to triage email i

Mempalace is a long-term memory management system for large language models that orchestrates the storage and retrieval of conversation history and entity relationships. It functions as a memory orchestrator and Model Context Protocol server, providing AI clients with read and write access to structured knowledge. The system utilizes a temporal knowledge graph to track evolving entity relationships and timelines with validity windows. It employs a hierarchical memory partitioning strategy, organizing data into wings and rooms to isolate specialist agent contexts and restrict semantic searches

Playwright MCP is a browser automation server that provides a standardized interface for connecting large language models to web navigation and interaction capabilities. By operating as a Model Context Protocol server, it enables external AI agents to execute browser-based tasks, extract data, and perform complex web sequences through a unified communication protocol. The project distinguishes itself by acting as a remote controller that manages headless browser lifecycles and isolated automation contexts. It maintains session-based state isolation, allowing for distinct user profiles and per

PageIndex is an agent-ready knowledge engine that processes documents into hierarchical tree structures to enable reasoning-based information retrieval. By organizing content into logical trees rather than relying on traditional vector database chunking, the platform preserves the original structure and flow of complex documents. It functions as a Model Context Protocol server, allowing external AI agents to connect to and query indexed knowledge bases through standardized communication protocols. The platform distinguishes itself by using vision-language models to process raw document images

This project is a high-performance headless browser engine designed for scalable web automation, data extraction, and AI agent integration. It provides a specialized environment that allows autonomous agents and testing frameworks to interact with web content through standardized remote control protocols. By executing pages in a lightweight, headless state, the engine minimizes resource consumption while maintaining the ability to perform complex navigation and dynamic content rendering. The platform distinguishes itself through deep integration with AI-centric communication layers and advanc

This project is a Model Context Protocol server that provides a standardized interface for connecting host applications to external data sources and service APIs. It functions as a middleware component, exposing repository-related functionality as a set of discoverable tools that can be invoked dynamically by large language models to facilitate context-aware reasoning and task execution. By bridging host environments with external platforms, the server enables artificial intelligence models to access real-time repository information, supporting automated workflows and improved accuracy in gen

Headroom is an AI gateway proxy and token optimizer designed to reduce the cost and latency of large language model interactions. It functions as an intermediary that intercepts traffic between clients and providers to apply context compression, request routing, and format translation. The system differentiates itself through a Model Context Protocol server implementation that delivers compression and retrieval tools to compatible AI hosts. It employs a content-aware compression pipeline and tiered importance scoring to trim redundant data from logs and tool outputs while preserving essential

Repomix is an AI-focused development utility designed to prepare local and remote codebases for analysis, review, and automated interaction. It functions as a codebase context bundler and a Model Context Protocol server, aggregating project files into structured documents that are optimized for ingestion by large language models. By serving as a bridge between local repositories and external intelligence agents, the tool facilitates real-time codebase inspection and automated development workflows. The system distinguishes itself through rigorous repository token management and security-consc

fastmcp is a Python library and framework for building servers and clients that implement the Model Context Protocol. It serves as a tool integration library designed to connect large language models to external tools and data sources. The framework features an interactive tool user interface renderer, which allows for the display of visual interfaces for tools directly within a conversational flow. It also provides a library for automatically generating schemas and validation for tools used by language models. The project covers server and client development, including tool and resource exp

Deepagents is an LLM agent orchestration platform and stateful application server designed for deploying and managing AI agents built with computational graphs. It provides a containerized runtime environment that handles agent execution, state persistence, and the versioning of AI assistants. The platform distinguishes itself through deep integration with the Model Context Protocol, allowing agents to function as servers that expose tools and capabilities to external clients. It features a sophisticated observability suite for capturing execution traces, performing LLM-based evaluations agai

FastMCP is a Python framework designed for building servers that expose functions, resources, and prompts to AI models using the Model Context Protocol. It simplifies the development process by automatically deriving tool metadata, input schemas, and documentation directly from Python function signatures and type hints. The framework provides a unified container for managing these components, allowing developers to build modular applications that integrate seamlessly with AI assistants. The project distinguishes itself through its support for interactive, server-defined user interface compone

Opcode is a desktop interface designed for managing AI-assisted software development workflows. It provides a centralized workspace to organize interactive programming sessions, configure specialized automated agents, and maintain oversight of development tasks through a visual environment. The platform distinguishes itself by integrating version control for AI conversations, allowing developers to create checkpoints and branches to navigate, compare, and revert between different interaction states. It also functions as a client for standardized context protocols, enabling the connection of e

This project provides a Model Context Protocol server that enables autonomous agents to interact with and manage automation workflows. It functions as an integration layer, allowing language models to discover, build, test, and deploy complex automation sequences through natural language instructions and structured schema-based communication. The platform distinguishes itself by offering granular control over automation logic, including the ability to perform surgical, incremental patches to specific workflow nodes rather than replacing entire structures. It supports multi-instance connectivi

The Model Context Protocol SDK is a framework for building clients and servers that connect AI models to external data, tools, and resources using a standardized communication protocol. It provides the foundational libraries and interfaces necessary to establish reliable, transport-agnostic connections between AI agents and external systems, enabling seamless information retrieval and task automation. The SDK distinguishes itself through a robust capability negotiation handshake that ensures compatibility between connected parties before exchanging messages. It supports a pluggable transport

Screenpipe is a local screen and audio recorder that captures and indexes digital activity to create a searchable archive of computer usage. It functions as an AI context engine, providing a local database of visual and auditory history to ground large language models. The system serves as a Model Context Protocol server, delivering screen history and meeting transcriptions to external AI assistants. It utilizes an OCR screen search tool to extract text from visual data and a speech-to-text transcription tool for identifying speakers in system and microphone audio. The software includes capa

omlx is a local inference server designed to run large language models, vision models, and embedding models on Apple Silicon. It provides a private alternative to industry-standard AI endpoints by hosting a local API gateway that mirrors OpenAI and Anthropic specifications. The system distinguishes itself through specialized hardware optimizations, including continuous batching for high throughput and a tiered caching system that offloads memory blocks to SSD. It also functions as a Model Context Protocol host, enabling the integration of local models with external tools, agents, and structur

This project is a Model Context Protocol server that functions as an automation tool for 3D design software. It acts as a bridge between creative applications and external intelligence agents, enabling users to manipulate geometry, materials, and lighting through natural language instructions. The tool distinguishes itself by providing a standardized interface for remote command execution and scene data exchange. By utilizing a protocol-based communication layer, it allows external models to query viewport status and object properties, facilitating automated decision-making and real-time scen