MCP Clients

go-mcprotocol is a Go library and tool for accessing Programmable Logic Controllers (PLCs) using the MELSEC Communication Protocol, enabling register data collection and local file dumping. go-mcprotocol is a Go

description: "An MCP server that enables LLMs to 'see' what's happening in browser-based games and applications through vectorized canvas visualization and debug information.

This repository provides a React application for interacting with Model Context Protocol (MCP) servers via Server-Sent Events, featuring a user-friendly interface, real-time communication, and screenshot previews. This repository provides a

The http4k MCP Desktop Client is a command-line tool that acts as a proxy for desktop applications to communicate with MCP servers via StdIO. It supports various remote transport and

The mcp-langchain-ts-client repository provides a LangChain.js client for the Model Context Protocol, porting the original Python implementation to JavaScript/TypeScript, enabling the use of MCP tools within LangChain.js applications.

A standalone agent runner that executes tasks using MCP (Model Context Protocol) tools via Anthropic Claude, AWS BedRock and OpenAI APIs. It enables AI agents to run autonomously in cloud environments

MCPSwiftWrapper is a lightweight wrapper for mcp-swift-sdk, designed to integrate with LLM Swift libraries like SwiftOpenAI and SwiftAnthropic. It simplifies the creation of MCP Clients within macOS applications.

Laravel MCP is a package that implements the Model Context Protocol, enabling communication between AI models and Laravel applications through standardized interfaces with features like tool registration and resource management.

This repository provides a TypeScript implementation of a Model Context Protocol (MCP) client, enabling LLM agents to interact with MCP servers through stdio or HTTP+SSE transports, supporting resources, tools, prompts, and sampling.

This repository provides an MCP server that integrates Ollama with Claude Desktop, enabling users to list models, get model information, and ask questions to specified models using the Model Context Protocol.

MCPX4J is a Java client library for MCP.RUN, enabling developers to easily integrate and invoke installed tools using a simple API with features like installation caching and customizable JSON decoding.

This repository hosts a web-based MCP client for creating and managing advanced chatbot applications, integrating with backend MCP servers via SSE for real-time interaction and Dify for chatbot management.

mcpx-py is a Python library that enables interaction with various Large Language Models (LLMs) using mcp.run tools, supporting models from PydanticAI, OpenAI, Ollama, and Gemini. mcpx-py is a Python library

EasyMCP is a Python rewrite of the Model Context Protocol, offering features like server management, dynamic addition/removal, namespaced tools/resources, and automatic cache invalidation for efficient server interactions. EasyMCP is a

Oneshot is an early-stage macOS client for Anthropic's MCP, allowing users to bring their own API key, discover tools, and install them with a single click. Oneshot is an early-stage