MCP-X Agent 🤿 🤖
@TimeCyber
About MCP-X Agent 🤿 🤖
这是一个MCP客户端，让你轻松配置各个大模型，对接各种MCP Server而开发。This is an MCP client that allows you to easily configure various large models and develop interfaces with various MCP servers.
Config
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"MCP_SERVER_NAME": {
"enabled": true,
"transport": "sse",
"url": "YOUR_SSE_SERVER_URL"
}
}
}Tools
No tools detected
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
Overview
What is MCP-X Agent?
MCP-X Agent is an open-source MCP Host Desktop Application that seamlessly integrates with any LLMs supporting function calling capabilities. It is designed for users who want a unified interface to manage AI agents, knowledge bases, and MCP tools across Windows, macOS, and Linux.
How to use MCP-X Agent?
Download the latest release from GitHub, then install the appropriate package for your OS. Windows users get pre‑installed Python and Node.js; macOS and Linux users must install those environments separately. After installation, manage agents via the sidebar, upload documents to the knowledge base, and add MCP servers by editing the JSON configuration in the MCP settings.
Key features of MCP-X Agent
- Universal LLM support (ChatGPT, Anthropic, Ollama, OpenAI‑compatible)
- Cross‑platform (Windows, macOS, Linux)
- Knowledge base management with file upload and search
- Model Context Protocol (MCP) integration via stdio and SSE
- AI agent system with specialized, categorized agents
- Multi‑language support (English, Chinese, Spanish, and more)
- Advanced API key and model switching
- Automatic application updates
Use cases of MCP-X Agent
- Analyze food content and generate nutritional insights with AI agents
- Build and query a knowledge base from uploaded documents
- Integrate external MCP tools (e.g., Fetch, YouTube‑dl) for extended capabilities
- Switch between different LLMs and custom system prompts per task
FAQ from MCP-X Agent
What LLMs does MCP-X Agent support?
It supports ChatGPT, Anthropic, Ollama, and any OpenAI‑compatible model, provided the LLM has function calling capabilities.
What are the runtime dependencies for MCP-X Agent?
Windows builds include Python and Node.js. macOS and Linux users need to install Python and Node.js (with npx and uvx) themselves.
How can I add custom MCP tools to MCP-X Agent?
Edit the MCP settings JSON to add a new mcpServers entry with either a local command (stdio) or an SSE URL. The README provides examples for Fetch, Filesystem, and YouTube‑dl.
Where are my knowledge documents stored?
Documents are uploaded into the application’s internal knowledge base, searchable by filename and content. The README does not specify the physical storage location.
Does MCP-X Agent support authentication or transport beyond stdio?
Yes, it supports SSE (Server‑Sent Events) transport for external MCP servers. No authentication details are mentioned in the README.
Frequently asked questions
What LLMs does MCP-X Agent support?
It supports ChatGPT, Anthropic, Ollama, and any OpenAI‑compatible model, provided the LLM has function calling capabilities.
What are the runtime dependencies for MCP-X Agent?
Windows builds include Python and Node.js. macOS and Linux users need to install Python and Node.js (with npx and uvx) themselves.
How can I add custom MCP tools to MCP-X Agent?
Edit the MCP settings JSON to add a new `mcpServers` entry with either a local command (stdio) or an SSE URL. The README provides examples for Fetch, Filesystem, and YouTube‑dl.
Where are my knowledge documents stored?
Documents are uploaded into the application’s internal knowledge base, searchable by filename and content. The README does not specify the physical storage location.
Does MCP-X Agent support authentication or transport beyond stdio?
Yes, it supports SSE (Server‑Sent Events) transport for external MCP servers. No authentication details are mentioned in the README.
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