Diegofornalha MCP Server Tess
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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.
2 points
6.9K

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 agents
Get a list of all available agents on the TESS platform.
Get a specific agent
Query and display detailed information about a specific agent.
Execute an agent
Run an agent and pass personalized messages.
List files
Browse all files associated with an agent.
Bind a file to an agent
Link a file to a specific agent.
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 task
Demonstrate how to send a request to the TESS platform to execute an agent task.
Upload a new file
Show 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.

Installation

Copy the following command to your Client for configuration
Note: Your key is sensitive information, do not share it with anyone.

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