Awesome MCP Clients, A New Way To Interact With LLMs

The Model Context Protocol (MCP) is rapidly establishing itself as a foundational framework in the AI ecosystem, offering a standardized way for large language models (LLMs) to access external tools and data sources seamlessly. At its core, MCP acts much like a USB-C port for AI applications—it provides a universal, open protocol that enables a wide range of integrations, from local file systems and databases to remote APIs and specialized services. This standardization is particularly crucial as LLMs evolve from simple conversational agents to sophisticated tools capable of orchestrating complex workflows and interacting with diverse data environments.

MCP’s client-server architecture underpins its flexibility: a host application can connect to multiple MCP servers, each exposing specific capabilities through a consistent interface. This design not only allows developers to build modular, interoperable AI agents but also ensures that switching between different LLM providers or data sources can be achieved with minimal friction. By decoupling the model from the tools it uses, MCP empowers developers to focus on innovation and functionality, rather than being locked into proprietary ecosystems.

Furthermore, MCP is designed with security and scalability in mind. It establishes best practices for data handling and context sharing, ensuring that integrations remain secure and robust even as they scale across different infrastructures. As the protocol gains traction, a growing list of pre-built integrations and active community contributions are rapidly expanding its ecosystem, making MCP a pivotal enabler for tool-augmented AI applications.

Below is the list of some of the MCP clients with the most vibrant communities.

5ire

• Project Link: 5ire on GitHub
• GUI or CLI: Cross-platform desktop GUI application (Electron-based).
• Features: Supports multiple LLM providers including OpenAI, Azure OpenAI, Anthropic Claude, Google PaLM, Baidu ERNIE, Mistral AI, Moonshot, Doubao, xAI Grok, DeepSeek, and local models via Ollama. It connects to MCP tool servers, enabling external tools via the Model Context Protocol for system interactions like file access and databases. Includes a MCP server marketplace for one-click tool integration and a local document knowledge base supporting RAG.
• Additional Description: 5ire offers a modern chat assistant interface with bookmarking, prompt library, usage analytics, and multi-theme support. It functions as an all-in-one AI assistant, allowing both casual conversations and advanced tool-augmented workflows via MCP.
• Community Status: Licensed under GNU GPL v3 and actively developed (latest commits on Mar 18, 2025). The project has ~1.6k ⭐ on GitHub with ~116 forks, showing a growing community. Regular updates (500+ commits) and an active issue tracker indicate ongoing development and engagement.

ChatMCP

• Project Link: ChatMCP on GitHub
• GUI or CLI: Cross-platform desktop GUI (built with Flutter/Dart).
• Features: Offers an AI chat interface with full MCP support, connecting to any MCP server for tool-augmented conversations. Supports OpenAI ChatGPT, Anthropic Claude, local models via Ollama, and DeepSeek. Features an MCP Server Marketplace, SSE streaming, chat history, and auto-selection of tools based on context. RAG-supported knowledge base, a prompt library, and light/dark themes.
• Additional Description: ChatMCP prioritizes usability and AI tool integration, allowing one-click installation of MCP tool servers for extended features like web search and database queries.
• Community Status: Open-source under Apache-2.0 and actively developed (latest release v0.0.19-alpha on Mar 17, 2025). Gained ~932 ⭐ and ~58 forks, with ~7 contributors. Frequent updates with ongoing discussions in GitHub issues.

Goose

• Project Link: Goose on GitHub
• GUI or CLI: CLI-based AI agent.
• Features: Goose is an extensible AI agent that installs and uses tools dynamically. It integrates with any LLM API (OpenAI, etc.) and uses the MCP protocol for tool interactions. It can perform code operations, run tests, execute commands, and use multiple MCP tool extensions simultaneously. Notably, it can load multiple MCP tool extensions at once and coordinate them to tackle higher-level goals.
• Additional Description: Targeted at developers, Goose functions as an AI DevOps assistant, invoking tools via MCP to accomplish complex tasks. Built in Rust for high performance and designed for scriptability.
• Community Status: Highly popular, with ~10.3k ⭐ and 700+ forks on GitHub. Active development with regular commits, and strong community engagement.

HyperChat

• Project Link: HyperChat on GitHub
• GUI or CLI: Desktop GUI (Electron app, also supports local web deployment).
• Features: Supports multiple LLM APIs and MCP-based plugins for external tools. Works with OpenAI, Anthropic, Alibaba Qwen, xAI Grok, Tsinghua GLM, DeepSeek, and Ollama. Built-in MCP plugin marketplace for easy tool integration, allowing users to extend AI capabilities with tools like web search, code execution, and database queries.
• Additional Description: Designed for flexibility in AI chat experiences, with an intuitive UI, multi-tab chats, and extensibility via MCP. It can also be used as a local web app via Node.js, providing additional deployment flexibility.
• Community Status: Open-source under Apache-2.0, with ~335 ⭐ and 35 forks. Frequent updates and growing community engagement.

LibreChat

• Project Link: LibreChat on GitHub
• GUI or CLI: Web-based GUI (self-hosted, React/TypeScript).
• Features: LibreChat is a highly feature-rich ChatGPT alternative that supports a broad range of model providers and tooling. It can interface with OpenAI, Anthropic, Google Vertex AI (PaLM2, Gemini), OpenRouter, xAI, Mistral, and community models like GPT4All or oobabooga. Built-in Code Interpreter and OpenAI function calling/OpenAPI Actions, as well as Model Context Protocol support for tools. Users can deploy LibreChat Agents which utilize tools (files, web access, database queries) via MCP or native plugins. Multi-user authentication, model switching, message search, and extensive assistant configuration options are available.
• Additional Description: LibreChat provides a familiar chat UI with powerful customization. Through a clean web interface, users can chat with models from different providers and invoke tools seamlessly. It’s designed for self-hosting, making it a strong choice for those seeking an AI assistant without relying on proprietary cloud services.
• Community Status: Highly active, with ~23.4k ⭐ and nearly 4k forks. Frequent commits, a large contributor base, and ongoing improvements driven by community feedback.

oterm

• Project Link: oterm on GitHub
• GUI or CLI: CLI (text-based terminal client).
• Features: oterm is a terminal UI for Ollama, enabling conversations with local LLMs and extending them with tools via MCP. It connects directly to an Ollama instance to run local models (like Llama-2, etc.) and adds Model Context Protocol support on top. This means you can chat with a local model and have it invoke external tools (through any MCP server you configure) to answer queries that require actions or data beyond its base knowledge.
• Additional Description: The interface is simple and runs in a terminal, which is ideal for developers or power-users who prefer CLI. Despite its simplicity, it effectively turns local/offline models into capable agents by giving them tool-use abilities. Configuration is done via YAML/JSON for MCP endpoints.
• Community Status: Licensed under MIT, oterm has gained ~1.4k ⭐ on GitHub. The project is actively maintained, with rapid support for new MCP integrations and strong engagement from CLI users.