Diegofornalha MCP Server Tess
MCP-Server-TESS is a server project based on the MCP protocol, used to integrate with the TESS API, providing functions such as agent management, file operations, and message processing, supporting local deployment and installation on the Smithery.ai cloud platform.
rating : 2 points
downloads : 8
What is MCP-Server-TESS?
MCP-Server-TESS is a server based on the Model Context Protocol (MCP), designed to interact with the TESS platform through the API. It allows users to easily manage agents, files, and execute custom tasks.How to use MCP-Server-TESS?
Through simple installation and configuration, you can quickly start using the server to manage and operate the content in the TESS platform. You can complete the setup and start using it in just a few steps.Applicable scenarios
Suitable for enterprises or developers who need to automate the management of TESS platform agents and files, such as AI project development, data analysis, etc.Main features
List agentsGet a list of all available agents on the TESS platform.
Get a specific agentQuery and display detailed information about a specific agent.
Execute an agentRun an agent and pass personalized messages.
List filesBrowse all files associated with an agent.
Bind a file to an agentLink a file to a specific agent.
Advantages and limitations
Advantages
Easy to integrate and use
Support multiple tools and functions
Provide comprehensive API documentation
Limitations
Requires a certain foundation in Node.js
Limited support for high concurrency
How to use
Install the server
Clone the repository and install the dependencies.
Configure environment variables
Create a.env file and add the TESS API key.
Start the server
Use npm to start the development mode or production mode.
Usage examples
Execute an agent taskDemonstrate how to send a request to the TESS platform to execute an agent task.
Upload a new fileShow how to bind a new file to a specific agent.
Frequently Asked Questions
How to install MCP-Server-TESS?
Does it support Docker?
Related resources
GitHub repository
Project source code and documentation.
Smithery.ai page
Use the server directly on Smithery.ai.
Featured MCP Services

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
141
4.5 points

Duckduckgo MCP Server
Certified
The DuckDuckGo Search MCP Server provides web search and content scraping services for LLMs such as Claude.
Python
830
4.3 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
1.7K
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
87
4.3 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
6.7K
4.5 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#
567
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
754
4.8 points

Context7
Context7 MCP is a service that provides real-time, version-specific documentation and code examples for AI programming assistants. It is directly integrated into prompts through the Model Context Protocol to solve the problem of LLMs using outdated information.
TypeScript
5.2K
4.7 points