Model Context Protocol (MCP)
The Model Context Protocol (MCP) is an open standard for connecting AI applications to external data sources, tools, and workflows. It defines a consistent way for clients and servers to exchange context and capabilities, reducing the need for custom integrations between every model application and service. MCP can help make information and actions available to AI systems while keeping connections structured and explicit.
Open source tools in this area include server and client libraries, integrations for databases and services, development and debugging utilities, and gateways that coordinate multiple connections. When choosing a tool, consider its protocol support, maturity, maintenance activity, license, security model, runtime requirements, and compatibility with your existing AI applications. This area is useful to developers building AI agents, organizations integrating models with internal systems, and contributors creating reusable connections.
16 repositories · updated October 3, 2026
Inference Gateway: Unifying LLM Providers with a High-Performance API
Inference Gateway is an open-source, cloud-native, high-performance proxy server designed to unify access to various language model APIs. It provides a single OpenAI-compatible endpoint, simplifying interactions with multiple LLM providers, from local solutions like Ollama to major cloud platforms. This gateway enables seamless integration and management of diverse AI models, enhancing portability and data privacy.
dcc-mcp-blender: AI-Driven 3D Workflows with an Embedded MCP Server
dcc-mcp-blender is a powerful Blender addon that integrates an embedded Streamable HTTP MCP server directly into Blender. This allows any MCP-compatible AI client to seamlessly control and automate your 3D modeling, animation, and rendering workflows. It offers over 200 pre-built tools and an extensible skill system for robust production environments.
DeclarAgent: Declarative Runbook Executor for Safe AI Agent Workflows
DeclarAgent is an innovative declarative runbook executor specifically designed for AI agents. It enables agents to validate, dry-run, and safely execute multi-step YAML workflows. This tool provides a structured, auditable, and secure way for LLM agents to interact with real CLI workflows, enhancing their operational safety and reliability.
AgenticSchema: Empowering AI Agents with Structured Web Data
AgenticSchema is an innovative open-source library that transforms existing Schema.org markup, including JSON-LD, Microdata, and RDFa, into callable tools for AI agents. This library operates entirely client-side, requiring no backend infrastructure, and significantly enhances an agent's ability to interact with web content. By leveraging structured data already present on millions of websites, AgenticSchema bridges the gap between web content and AI agent capabilities.
Best of Agent Harnesses: A Curated List for AI Agent Development
RyanAlberts' Best of Agent Harnesses is a comprehensive, curated, and ranked list of over 100 AI agent harnesses and orchestration frameworks. It provides valuable insights for building reliable agentic systems, offering both human-readable guides and machine-readable formats for agents themselves. The repository is rescored weekly to ensure up-to-date recommendations.
SandBase CLI: Connect Your AI Agent to 2,000+ Models and APIs
SandBase CLI is an open-source command-line interface and local MCP server that supercharges AI agents. It connects 25 popular AI clients, such as Claude Code, Cursor, and ChatGPT, to over 2,000 AI models and APIs, simplifying complex integrations. This powerful tool streamlines AI agent development by offering a unified gateway, removing the hassle of API key management and configuration.
MetaMCP: Unifying Model Context Protocol Servers with an All-in-One Gateway
MetaMCP is a powerful, self-hosted solution that acts as an aggregator, orchestrator, middleware, and gateway for Model Context Protocol (MCP) servers. It allows developers to dynamically combine multiple MCP servers into a single, unified endpoint, enhancing tool management and agent development. This TypeScript-based project simplifies the deployment and management of AI tools within a Dockerized environment.
FastMCP: The Pythonic Framework for Model Context Protocol Applications
FastMCP is a robust, Pythonic framework developed by PrefectHQ, designed to simplify the creation of Model Context Protocol (MCP) servers and clients. It provides a comprehensive application framework for connecting Large Language Models (LLMs) to tools and data, handling complexities like schema generation, validation, and protocol lifecycle. As the standard framework for MCP, FastMCP empowers developers to build powerful LLM-integrated applications efficiently.
mcp-grafana: An MCP Server for Seamless Grafana Integration
mcp-grafana is a Model Context Protocol (MCP) server designed to provide comprehensive access to your Grafana instance and its surrounding ecosystem. It enables powerful programmatic interaction with Grafana dashboards, datasources, alerting, and more, facilitating advanced automation and integration with AI assistants.
Inspector: The Ultimate Tool for Developing MCP and ChatGPT Apps
MCPJam Inspector is a powerful local development client designed for testing and debugging MCP servers, ChatGPT apps, and MCP ext-apps. It provides a comprehensive suite of tools, including a widget emulator, OAuth debugger, and LLM playground, enabling developers to rapidly iterate on their projects without needing external services like ngrok or a ChatGPT subscription.
Cloudflare MCP Server: Connect LLMs to Cloudflare Services
The Cloudflare MCP Server repository provides a suite of servers implementing the Model Context Protocol (MCP), enabling large language models (LLMs) to interact seamlessly with various Cloudflare services. This allows LLMs to read configurations, process information, make suggestions, and even enact changes across Cloudflare's extensive ecosystem, from security and performance to application development. It streamlines the integration of AI capabilities with your Cloudflare account through natural language.
java-sdk: Build MCP Clients and Servers in Java
The official Java SDK for building Model Context Protocol clients and servers. It provides transport and JSON integration options for Java applications that need to exchange requests, notifications, and streaming data with MCP services.