Quickchat AI MCP Server (quickchat-ai-mcp) is an open-source server based on the Model Context Protocol (MCP), designed to connect user-created Quickchat AI agents to various AI applications, such as Claude Desktop, Cursor, VS Code, Windsurf, and more. Through this server, AI applications can access the agent's knowledge base and conversation capabilities in real time, enabling smarter interactions.
Purpose The core purpose of this tool is to make Quickchat AI agents available as tools that AI applications can call. Users do not need to write complex code; they only need to configure the agent's knowledge base, capabilities, and settings on the Quickchat AI platform, then activate it through the MCP page and obtain the configuration information to integrate their agent into different AI applications.
Main Capabilities
- Expose Quickchat AI agents as an MCP server for AI applications to call.
- Support custom MCP names, descriptions, and optional commands to help AI applications understand when to contact the agent.
- Provide integration examples with mainstream AI applications such as Claude Desktop and Cursor.
- Support installation via the PyPI package (quickchat-ai-mcp), and can be installed using uv.
- Provide guidance for running from source code, debugging with MCP inspector, and debugging through Claude Desktop, Cursor, or other AI applications.
- Users can control all aspects of MCP from the Quickchat AI dashboard and deploy changes with one click, without requiring users to reconfigure.
- View all conversation records through Quickchat Inbox (what is recorded is the interaction transcript between the AI application and Quickchat AI, not messages sent directly by users).
How to Use
- Create a Quickchat AI account and start the 7-day trial on any plan.
- Set up the AI's knowledge base, capabilities, and settings.
- Go to the MCP page to activate MCP, and fill in the name, description, and optional commands.
- Add the configuration snippet in the target AI application (such as Claude Desktop or Cursor), filling in the MCP name, SCENARIO_ID, and API_KEY (which can be found on the MCP > Integration page of the Quickchat AI app).
- If you want other users to connect to your MCP, you need to, on the MCP page of the Quickchat App,turn off the "Require API key" switch and share the configuration snippet without the API key.
- Install using uv: after installing uv, you can run it via the PyPI package or from source code.
- Debugging: you can use MCP inspector, or debug through AI applications such as Claude Desktop and Cursor.
Applicable Scenarios
- Developers want to integrate their Quickchat AI agents into AI applications such as Claude Desktop and Cursor to extend their functionality.
- Enterprises or individuals want to let other users conveniently connect to their Quickchat AI agents to achieve knowledge sharing or customer service.
- AI application scenarios that require real-time access to the knowledge base and conversation capabilities.
Limitations
- You need to have a Quickchat AI account and have the agent set up.
- The configuration steps for other AI applications may differ, and the official documentation states that instructions will be gradually expanded.
- Conversation records record the interaction transcript between the AI application and Quickchat AI, not messages sent directly by users.
- For the specific list of supported AI applications and detailed steps, please refer to the official documentation and examples.
