Latest MCP Clients

A flexible, lightweight library that connects and optimizes teams of AI agents, enabling seamless integration with various frameworks, tools, and data sources.

Provides a complete AI agent platform that combines the OmniAgent builder, a local tools system, autonomous background agents, multi‑tier memory with vector search, real‑time event streaming, and a universal MCP client usable via CLI or embeddable library.

Integrates Model Context Protocol servers into Neovim, offering an intuitive UI for managing, testing, and using those servers with popular chat plugins.

A Python SDK that simplifies interaction with MCP servers and enables developers to create custom agents with tool‑calling capabilities.

Build effective agents using Model Context Protocol and simple, composable workflow patterns.

Enables natural-language-driven browser automation using Playwright and LLMs, allowing tasks like navigation, data extraction, and multi‑page workflows without writing brittle scripts.

Provides a personal AI assistant that runs directly in the terminal, capable of executing code, manipulating files, browsing the web, using vision, and interfacing with various LLM providers.

Provides a unified SDK to build, test, and deploy AI-powered applications across multiple programming languages and model providers, with built‑in observability, evaluation, and deployment tooling.

A unified platform that manages AI models, MCP servers, and complex workflows, offering secure key storage, visual flow building, and an interactive chat UI.

Enables rapid creation and interaction with sophisticated agents and workflows using a declarative syntax and full MCP support, including multimodal resources and sampling.

Provides a client for interacting with MCP servers directly within Emacs, enabling seamless communication and integration.

Provides a TypeScript‑first generative agent framework with composable contexts, persistent memory, universal model routing, and native Model Context Protocol (MCP) integration for building production‑grade AI agents.

Discover and install open‑source MCP servers within VSCode, enabling integration with GitHub Copilot Chat.

Enables faster shipping of code by integrating continuous AI agents across IDEs, terminals, and CI pipelines, offering chat, edit, autocomplete, and customizable agent workflows.

Provides an agentic chat experience directly in the terminal, enabling developers to build applications using natural language.

Simplifies creation of AI agents with a Rust library that connects to major LLM providers, offers structured output, and includes a flexible ToolBox for custom tool integration.

A cross‑platform desktop AI assistant that connects to major LLM providers, supports a local knowledge base, and enables tool integration via MCP servers.