Klavis AI is an open-source project that provides a simple and easy-to-use MCP (Model Context Protocol) service on Slack, Discord, and Web platforms. It includes various functions such as report generation, YouTube tools, and document conversion, supporting non-technical users and developers to use AI workflows.

This project is a collection of learning resources about Model Context Protocol (MCP), including guides, tools, and server implementations, aiming to help developers understand and apply the MCP standard. The project provides multiple example implementations of MCP servers, such as file system operations, Git management, GitHub integration, etc., as well as development guides and practical tools.

The MCP Game Helper is a custom model context protocol server that provides AI - assisted tools for game developers, focusing on tasks such as combat balance, skill analysis, level rhythm, and simulation.

A production-ready MCP server template for hosting custom AI tools and prompt templates, supporting remote deployment and local operation, helping developers quickly build AI model interaction tools.

The Last9 MCP Server is a server implementing the Model Context Protocol, providing local integration of real - time production environment data (logs, metrics, traces) for AI developers to help quickly and automatically fix code.

The Plane MCP Server is a model context protocol server that provides seamless integration with the Plane API, supporting functions such as project management, work item operations, and automation processes. It is suitable for developers and AI tool integration.

The Nodit MCP Server is a middleware that connects AI agents and developers to multi - chain structured blockchain data, providing simplified Web3 data access through the standardized Model Context Protocol.

The OpenFGA MCP Server is an experimental Model Context Protocol service that enables large language models to read from and write to the OpenFGA authorization store, providing fine-grained permission management capabilities for AI agents and developers.

CereBro.Unity is a model-agnostic AI agent wrapper based on CereBro, supporting the Model Context Protocol (MCP), allowing developers to write tools that can be used across AI models.

Payload MCP is an AI - assisted tool server developed specifically for Payload CMS. It provides code generation, validation, project building, and query analysis functions through the standardized Model Context Protocol (MCP) to help developers more efficiently build and manage Payload CMS projects.

This project is a collection of resources related to the security of the Model Context Protocol (MCP), including research papers, security vulnerability analyses, tools, articles, and other relevant resources. It aims to help developers and security experts understand and address security challenges in the MCP protocol.

Nexus is an AI search server based on the Model Context Protocol (MCP), providing zero-configuration installation, intelligent web search, and source citation functions, designed specifically for developers.

GUARDRAIL is a security framework specifically designed for the large language model (LLM) application ecosystem, providing comprehensive protection especially for the Model Context Protocol (MCP). It uses a multi - layer architecture, including an information gateway layer, a context verification layer, a request control layer, an execution isolation layer, and an audit monitoring layer, aiming to prevent data leakage, unauthorized access, and resource abuse. This framework emphasizes progressive adoption, allowing developers to gradually enhance security while maintaining high performance and ease of use.

Lspace is an open-source API backend and server that implements the Model Context Protocol (MCP), helping developers transform insights from AI conversations into a searchable and persistent knowledge base and integrate it into various tools.

Jira Context MCP is a model context protocol implementation that integrates Jira with the Cursor IDE, allowing developers to directly obtain Jira ticket information, filter issue types, and automatically fix issues through an AI assistant, thereby improving development efficiency.

Azure MCP Hub is a platform that helps developers quickly build, run, or reuse Model Context Protocol (MCP) servers. It supports multiple programming languages and AI frameworks, enabling AI agents to call real APIs.

OmniMind is an open - source Python library designed to simplify Model Context Protocol (MCP) integration and support the development of AI agents, workflows, and automation. It offers plug - and - play functionality, has built - in multiple tools, and provides intelligent responses based on Google Gemini, making it suitable for developers and beginners to quickly build AI applications.

Model Context Protocol (MCP) is an open standard that allows developers to establish a secure two-way connection between data sources and AI tools. This project provides a gem package implemented in Ruby, including full development process support and type checking functions.

This document categorizes and organizes various Model Context Protocol (MCP) servers to help developers integrate AI models with resources such as databases, file systems, APIs, cloud services, and automation tools.

CodeRide MCP is an AI - native task management system that deeply integrates AI development tools (such as Cursor, Cline, etc.) with the CodeRide platform through the Model Context Protocol standard, enabling AI assistants to understand the project context, manage tasks, and collaborate seamlessly with developers.

This project demonstrates how to integrate Model Context Protocol (MCP) tools with Microsoft Semantic Kernel to achieve seamless interaction between AI models and external data sources or tools. By standardizing the interaction between applications and AI models through the MCP protocol and combining the powerful functions of Semantic Kernel, developers can expand AI capabilities, dynamically call external functions, and simplify the orchestration of complex workflows.

A well - organized collection of Model Context Protocol (MCP) servers, covering enterprise support implementation, demonstration implementation, integration tools, community contributions, and development frameworks, aiming to provide developers with rich resources and tools.

The GitHub MCP Server is a service based on the Model Context Protocol that provides seamless integration with the GitHub API, enabling developers to build automated workflows and AI tools.

Overview: MCP is a standard protocol, similar to the Type C protocol of electronic devices (which can both charge and transmit data), enabling AI models to interact with different APIs and data sources. It aims to replace fragmented Agent code integration and improve the reliability and efficiency of AI systems. By establishing a common standard, service providers can offer their own AI capabilities according to the protocol, supporting developers to build more powerful AI applications more quickly. MCP maintains the context between different applications and services, enhancing the overall ability of autonomous task execution.

This is a list of multiple open - source AI projects, covering multiple fields such as automated agents, large - language models, image generation, and AI development frameworks. These projects aim to help developers make money using AI technology, including building intelligent assistants, automating workflows, and content generation applications.

This project is an example of an MCP server based on Spring Boot, implementing the Model Context Protocol standard. It allows developers to expose data through the MCP server or build AI applications that connect to these servers. In the example, a simple information service is created to provide developer information to the Claude desktop application through the MCP protocol.

The GitHub MCP Server is a server based on the Model Context Protocol, providing seamless integration with the GitHub API and supporting developers to build automated workflows and AI - driven tool applications.

GitLab MCP Server is a service based on the Model Context Protocol (MCP) that provides seamless integration with the GitLab API and supports developers and AI tools to achieve advanced automation and interactive functions in the GitLab ecosystem.

Pro MCP is a community-driven directory of Model Context Protocol (MCP) servers, aiming to provide a comprehensive list of MCP servers for developers and AI enthusiasts and promote the development of intelligent applications.

The Edge Delta MCP Server is a server based on the Model Context Protocol, used for seamless integration with the Edge Delta API, enabling developers to build automation tools and AI applications to analyze observational data.

Lspace is an open - source API backend and server that implements the Model Context Protocol (MCP), helping developers transform insights from AI conversations into a searchable and persistent knowledge base and share them across tools.

MCPLab is a collection project of server-client examples, code snippets, design patterns, and tutorials focused on the Model Context Protocol (MCP), aiming to help developers quickly build MCP-driven applications.

This project is a collection of multiple Model Context Protocol (MCP) servers, aiming to provide dedicated interfaces for large language models. These servers are created by non - professional developers with the help of AI tools and currently include two functional modules: Perplexity search integration and keyword analysis.

The GitHub MCP Server is a service based on the Model Context Protocol that provides seamless integration with the GitHub API, supporting developers in building automated workflows and AI tools.

The GitHub MCP Server is a server based on the Model Context Protocol that provides seamless integration with the GitHub API, supporting developers to build automated workflows, data analysis, and AI tools.