Clients
389 editors, desktop apps, agents and frameworks that support MCP.
Frameworks & SDKs
Built on Spring AI with encapsulated MCP client service to enable web page agents to interact with MCP servers through stdio and HTTP SSE (Server-Sent Events). The project implements automated connection management mechanisms including auto initialization, health checks, timeout closure, and connection reuse
Elemental is a multi-agent framework designed with a focus on the modularity of agent workflow stages. It enables the creation and management of single-agent or multi-agent systems with ease. The core functionality revolves around dynamically planning how to solve assigned tasks.
SlashMCP is a production-grade AI workspace that connects LLMs to real-world data and tools through an intuitive chat interface. Built on the Model Context Protocol (MCP), it enables seamless interaction with multiple AI providers (OpenAI, Claude, Gemini).
A powerful and extensible multi-agent workflow engine supporting Multi-Agent systems, auto-workflows, MCP server integration, and more. Supports multiple tools and resources, providing intelligent agents and automated service execution.
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.
