Browse and discover Model Context Protocol compatible clients.
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.
practical patterns for agentic coding: hooks, agents, automation. built from hundreds of claude code sessions
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
A Unity MCP server that allows MCP clients like Claude Desktop or Cursor to perform Unity Editor actions.
Desktop4mistral is a Python-based desktop application offering a user-friendly interface for interacting with Mistral AI models, featuring model selection, chat history, command support, and Markdown support. Desktop4mistral is a Python-based
Video editing MCP server for AI agents. 82 tools, 690+ tests, 3 interfaces. Works with Claude Code, Cursor, and any MCP client. Local, fast, free.
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
arXiv MCP Server Client 🐙 enables AI assistants to search, retrieve, analyze, and summarize arXiv papers with features like author/category browsing, trends, and citation insights.
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
Salesforce MCP Library is a local stdio bridge for Salesforce MCP endpoints using OAuth client credentials, featuring a reusable Apex MCP library and JSON-RPC 2.0 core.
MCP server for analyzing Perfetto traces with LLMs — query .pftrace files in PerfettoSQL via Claude Code or any MCP client
This React-based demo showcases an MCP client interacting with SSE servers, enabling tool calls and text completion, though it's still under development and has limitations regarding tool naming and concurrent calls.
This repository provides a TypeScript-based Model Context Protocol (MCP) client that integrates with LangChain ReAct Agent, enabling interaction with LLMs like Anthropic, OpenAI, and Groq through MCP servers.
This repository provides a Python-based Model Context Protocol (MCP) client using LangChain, enabling interaction with MCP servers through LangChain ReAct Agent and supporting LLMs from Anthropic, OpenAI, and Groq.