Browse and discover Model Context Protocol compatible clients.
AWorld facilitates building, evaluating, and running General Multi-Agent Assistance, bridging the gap between theoretical MAS capabilities and real-world applications. It allows users to create agentic prototypes and extend them for practical needs.
A single interface to use and evaluate different agent frameworks
A desktop MCP client designed as a tool unitary utility integration, accelerating AI adoption through the Model Context Protocol (MCP) and enabling cross-vendor LLM API orchestration.
This repository provides a connector, the Obsidian Model Context Protocol, that enables Claude Desktop to read and search Markdown notes within an Obsidian vault, facilitating enhanced context awareness.
Just a Better Chatbot. Powered by MCP Client & Workflows.
Chatmcp is a cross-platform AI chat client for MacOS, Windows, Linux, iOS, and Android, allowing users to chat with an MCP server after configuring their LLM API key and endpoint
Flock is a flexible low-code platform for orchestrating collaborative agents, offering features like MCP tools support, parameter extraction, subgraph nodes, human-in-the-loop interactions, and multimodal chat capabilities. Flock is a flexible
Minima is an open-source RAG platform offering on-premises containerized solutions, integrating with ChatGPT and MCP, or operating fully locally. It enables secure querying of local documents using various LLMs.
The MCP server that turns Claude into the only coding agent hitting 100% on a real benchmark. -77% active tokens, -76% wall time, 0 losses across 96 tasks on Claude Opus 4.7. Structural code navigation + persistent memory. Works with every MCP client.
This repository provides an Arduino library for interfacing with the MCP2515 CAN controller, enabling CAN-BUS communication for Arduino projects. It supports standard and extended frames, along with sending, receiving, and
QGISMCP integrates QGIS with Claude AI via the Model Context Protocol, enabling Claude to control QGIS for tasks like project creation, layer manipulation, and code execution. It uses a QGIS
CLI MCP package manager & registry for all platforms and all clients. Search & configure MCP servers. Advanced Router & Profile features.
Arcade Python SDK, CLI, and toolkits
MCP-Bridge bridges the OpenAI API and MCP tools, enabling developers to use MCP tools through the OpenAI API interface. It supports chat completions, MCP tools, and offers an SSE Bridge
AgentKit enables building multi-agent networks with deterministic routing and rich tooling via MCP, supporting TypeScript AI developers with fault-tolerant cloud deployment. It offers flexible routing, multiple model providers, and built-in tracing.