Ma3u MCP Dust Server
The MCP Dust Server is a server-side implementation of the Model Context Protocol (MCP) for interacting with Dust AI agents. The project consists of an MCP server and a test client, supporting real-time streaming responses, the complete JSON-RPC 2.0 protocol, session management, and other functions. It can be integrated into development environments such as Windsurf IDE and Claude Desktop.
rating : 2 points
downloads : 7.8K
What is the MCP Dust Server?
The MCP Dust Server is a middleware server that implements the Model Context Protocol (MCP) standard and is specifically designed to interact with AI agents on the Dust.tt platform. It allows developers to access various AI capabilities on the Dust platform through a standardized protocol without having to directly handle the underlying API details.How to use the MCP Dust Server?
You can interact with the server through simple HTTP requests or WebSocket connections. The server provides standard interfaces for initializing sessions, sending messages, and terminating sessions, and also supports advanced functions such as direct tool execution.Applicable scenarios
Suitable for scenarios where Dust AI capabilities need to be integrated into existing systems, such as enterprise workflow automation, customer service robots, data analysis assistants, etc. Particularly suitable for multi-round dialogue applications that require long-term context maintenance.Main features
Multi-protocol support
Supports both Server-Sent Events (SSE) and HTTP Stream Transport for real-time communication protocols
Complete MCP lifecycle
Implements the complete session lifecycle management of initialize, message, and terminate
Direct tool execution
Tools can be directly executed through the 'run' method, simplifying client integration
Context maintenance
Automatically maintains session status and context, supporting multi-round complex dialogues
Secure communication
Automatically masks sensitive information such as API keys to ensure log security
Advantages
Standardized protocol: Uses the MCP standard protocol, making it easy to integrate with other systems
Real-time interaction: Supports streaming responses, providing a more natural dialogue experience
Enterprise-level security: Built-in PII protection mechanism, meeting enterprise security requirements
Multi-platform support: Can be seamlessly integrated with tools such as Windsurf IDE and Claude Desktop
Limitations
Requires a Dust.tt platform account and API key
There is a certain learning curve for non-technical personnel to configure
Currently mainly targeted at developers, lacking a graphical configuration interface
How to use
Installation preparation
Ensure that the Node.js environment is installed. It is recommended to use nvm to manage the Node version.
Get the project code
Clone the GitHub repository to the local machine.
Configure the environment
Copy the .env.example file to .env and fill in your Dust API key and other information.
Start the service
Run the development mode server and the test client.
Test the connection
Access http://localhost:6001 to use the test client to verify the connection.
Usage examples
Integrate into an enterprise customer service system
Use the MCP server as middleware to connect the enterprise's existing customer service system and Dust AI agents, realizing intelligent Q&A functions
Data analysis assistant
Connect to the data query agent through the MCP server, allowing business personnel to query enterprise data in natural language
Multi-agent workflow
Coordinate multiple professional agents to complete complex tasks, such as generating a market analysis report
Frequently Asked Questions
How to obtain a Dust API key?
Which AI models does the server support?
How to expand custom functions?
What is the maximum session duration?
How to monitor the server status?
Related resources
GitHub repository
Project source code and the latest version
Dust.tt platform
Official platform website
MCP protocol specification
Official documentation of the Model Context Protocol
Node.js installation guide
Official download and installation instructions for Node.js

Notion Api MCP
Certified
A Python-based MCP Server that provides advanced to-do list management and content organization functions through the Notion API, enabling seamless integration between AI models and Notion.
Python
14.8K
4.5 points

Markdownify MCP
Markdownify is a multi-functional file conversion service that supports converting multiple formats such as PDFs, images, audio, and web page content into Markdown format.
TypeScript
24.8K
5 points

Gitlab MCP Server
Certified
The GitLab MCP server is a project based on the Model Context Protocol that provides a comprehensive toolset for interacting with GitLab accounts, including code review, merge request management, CI/CD configuration, and other functions.
TypeScript
15.6K
4.3 points

Duckduckgo MCP Server
Certified
The DuckDuckGo Search MCP Server provides web search and content scraping services for LLMs such as Claude.
Python
44.6K
4.3 points

Unity
Certified
UnityMCP is a Unity editor plugin that implements the Model Context Protocol (MCP), providing seamless integration between Unity and AI assistants, including real - time state monitoring, remote command execution, and log functions.
C#
20.3K
5 points

Figma Context MCP
Framelink Figma MCP Server is a server that provides access to Figma design data for AI programming tools (such as Cursor). By simplifying the Figma API response, it helps AI more accurately achieve one - click conversion from design to code.
TypeScript
44.6K
4.5 points

Gmail MCP Server
A Gmail automatic authentication MCP server designed for Claude Desktop, supporting Gmail management through natural language interaction, including complete functions such as sending emails, label management, and batch operations.
TypeScript
15.0K
4.5 points

Minimax MCP Server
The MiniMax Model Context Protocol (MCP) is an official server that supports interaction with powerful text-to-speech, video/image generation APIs, and is suitable for various client tools such as Claude Desktop and Cursor.
Python
29.4K
4.8 points

