This project provides support for Model Context Protocol (MCP) tool calls for LangChain, enabling interaction with AI models through the MCP toolkit, such as file reading and summary generation.

MCP2Lambda is an MCP protocol server that runs AWS Lambda functions as tools for large language models (LLMs). AI models can call Lambda functions to access private resources and AWS services without code modification.

This project is a bridging tool that connects Claude Desktop to remote servers. It uses Node.js to convert protocols from stdio to HTTP SSE, supporting service discovery and tool calls of the MCP protocol.

This project demonstrates a real-time multi-tool agent architecture based on LangGraph and the MCP protocol. By decoupling agent orchestration and tool execution, it realizes a modular and scalable AI system. The MCP service supports multiple transport protocols (SSE/STDIO), allows AI agents to dynamically call remote tools, and has cross-language and cloud deployment capabilities.

The Linkup MCP Server is a tool used to integrate Linkup's web search functionality with AI models supporting function calls through the MCP protocol.

Janee is an AI agent key management tool based on the MCP protocol. It securely stores and injects API keys as an intermediary, enabling agents to call services without touching the original keys. It also provides complete audit logs, access policy control, and session management functions.

The Infisical Model Context Protocol (MCP) is a service protocol that integrates with the Infisical API through function calls. It supports multiple tool operations such as creating, deleting, and updating keys, and provides a debugging tool called MCP Inspector.

A minimalist MCP server implemented in bash script, supporting the call of a mathematical addition tool and capable of interacting with LLM through the JSON - RPC protocol.

Magic-API MCP Server is a model context protocol server designed specifically for Magic-API development, providing a complete development toolchain, including documentation query, API call, resource management, debugging, and backup functions, to help developers efficiently build and manage Magic-API interfaces.

This project is a Python - based implementation of the MCP (Model Context Protocol) server and client, aiming to provide standardized interfaces for AI models, unify the tool call formats of different large - model vendors, and integrate document search functions for multiple AI frameworks.

DiffuGen is an advanced local image generation tool that integrates the MCP protocol, supports multiple AI models (including the Flux and Stable Diffusion series), and can directly generate high-quality images in the development environment. It provides flexible configuration options, multi-GPU support, and can be integrated with multiple IDEs through the MCP protocol. It also provides an OpenAPI interface for external calls.

This project provides code analysis and editing capabilities through the LSP protocol, supports MCP tool calls for TypeScript/JavaScript, includes functions such as file operations, symbol lookup, and error checking, and has security features such as path restrictions.

The Flutter MCP Server is an open - source implementation of the Model Context Protocol (MCP) for the Dart/Flutter ecosystem. It provides a unified API interface for AI assistants and developer tools, supports remote calls to the Dart/Flutter development toolchain, and enables secure and programmable automated development processes.

Yingdao RPA MCP Server is an implementation based on the Model Context Protocol (MCP), providing a service for Yingdao AI Power and other MCP Host tools to call RPA capabilities. It supports the local mode and the open API mode, and can query and run RPA applications, upload files, manage jobs, etc.

A reference project implementing the Model Context Protocol (MCP), providing a standard for tool calls between LLMs and applications, including local and remote call implementations, and integrating AWS Bedrock and Claude 3.7.

A general - purpose MCP protocol API encapsulation server that can quickly wrap REST APIs into MCP tools for clients such as Claude to call.

The Feishu MCP Server is a service that implements the Model Context Protocol, supporting interaction with the Feishu API through tool calls and mainly providing Bitable operation functions.

This project demonstrates how to use Google's Gemini 2.5 Pro model to interact with the flight search tool under the MCP protocol through the function call feature, enabling natural language queries for flight information and returning formatted results.

MCP Client SSE is a Spring Boot - based Java application for synchronous interaction with the Model Context Protocol (MCP) server, supporting OpenAI API integration and tool callback configuration.

A command - line client tool for interacting with the Model Context Protocol (MCP) server, supporting listing available tools and calling specific tools.

An MCP protocol test server implemented in Rust, supporting basic commands and tool calls.

A Java source code vulnerability auditing tool based on function-level taint analysis. It provides security analysis capabilities for AI assistants through the MCP protocol, supporting the detection of multiple vulnerability types and call chain tracing.

A demonstration project showcasing the combination of the Model Context Protocol (MCP) with Pokemon data, including an MCP server, a client, and an HTTP server that allows LLMs to call Pokemon tools via OpenRouter.

The KubeBlocks Cloud MCP Server is a service based on the Model Context Protocol (MCP) that provides seamless integration with the KubeBlocks Cloud API, enabling AI assistants to manage cloud resources through standardized tools by calling interfaces.

A Java implementation of a weather service based on the Model Context Protocol, including a fast proxy client, supporting interaction with local and remote MCP servers, and demonstrating the completion of weather query tasks through LLM - called toolchains.

impart-mcp is an agent orchestration server based on the MCP protocol. It encapsulates multiple expert agents with professional capabilities as standard tools, enabling the host environment to uniformly call these agents to handle complex engineering tasks.

The Infisical Model Context Protocol (MCP) Server provides a set of tools for integrating with the Infisical API through function calls, supporting operations such as creating, deleting, updating, and querying keys. It is suitable for key management and project collaboration.

The MCP test client is a tool for testing Model Context Protocol servers, providing simple interfaces for tool calls and response validation.

The Model Context Protocol (MCP) is an open - source protocol released by Anthropic, aiming to solve the standardization problem of connecting large language models (LLMs) with external data sources and systems. It provides a structured framework that enables models to integrate and utilize external context, thereby expanding their capabilities and improving response accuracy. MCP supports functions such as knowledge expansion, external tool calls, and pre - written prompts.

A memory bank server based on the MCP protocol, supporting multi - project isolation and Markdown document management, providing tool call interfaces for large language models.

An experimental chat project based on the MCP protocol, implementing long polling chat functions in a two-person room by abusing the MCP tool call mechanism.

The GoldRush MCP Server is a service based on the Model Context Protocol (MCP) that exposes Covalent's GoldRush API as MCP resources and tools, enabling LLM clients to call blockchain data query and analysis functions.

The MCP server for ROS2 enables AI tools to connect to ROS2 nodes, topics, and services through the standard MCP protocol. It provides functions such as topic subscription and publishing, service calls, and action control, supports nested fields and automatic type discovery, and simplifies the integrated development of AI and ROS2.

Cloudera AI Agent Studio MCP Server is a lightweight model context protocol bridge service that can expose Agent Studio instances as a set of callable tools, supporting dynamic creation and management of workflows.

An MCP (Model Context Protocol) server project implemented in Go language, aiming to provide standardized tool call and resource access interfaces for AI models.

NCP is an intelligent orchestrator for the MCP protocol that manages multiple MCP servers in a unified manner. It automatically routes tool calls through semantic understanding, significantly reducing the cognitive burden and token consumption of AI tools, and improving the work efficiency and response speed of AI assistants.

SuperAgent is an MCP server that uniformly calls the Codex, Gemini, and Continue CLI agents. It supports parallel task execution, manages preset system prompts, and provides structured tool calls to clients through the MCP protocol.

This project is an MCP server integrated with the Stable Diffusion image generation function, providing image generation services for AI agents. It supports generating images through the MCP protocol or direct API calls and includes development and debugging tools.

The MCP Git tool library provides a series of Git operation functions called through the model context protocol

Intellistant is a high-performance multi-agent AI framework built on C++23, supporting MCP protocol tool calls and agent collaboration, designed for software development automation.