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MCP-Server-TESS

by diegofornalha
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TypeScript
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MCP-Server-TESS

MCP (Model Context Protocol) server for integration with the TESS API.

On

This project implements a server that follows the MCP protocol to interact with the TESS API. The server exposes tools that allow:

  • Listing and Managing Agents
  • Running agents with custom messages
  • Managing files and their associations with agents
  • And much more

Requirements

  • Node.js 18+
  • A TESS platform API key

Installation

You can use this server directly in Smithery.ai:

  1. Visit https://smithery.ai/server/@diegofornalha/mcp-server-tess
  2. Click "Install"
  3. Configure your TESS API key when prompted
  4. Ready! The server is available for use with your favorite LLM

Local Installation

Clone the repository and install the dependencies:

git clone https://github.com/seu-usuario/mcp-server-tess.git cd mcp-server-tess npm install

Settings

  1. Create a .env file based on .env.example
  2. Add your TESS API key:
TESS_API_KEY=sua_chave_api_aqui PORT=3000

Compilation

npm run build

Execution

To start the server in production mode:

npm start

For development with automatic reloading:

npm run dev

Available tools

The server exposes the following tools via HTTP API:

  1. listar_agentes_tess - List all available agents
  2. obter_agente_tess - Gets details of a specific agent
  3. executar_agente_tess - Runs an agent with custom messages
  4. listar_arquivos_agente_tess - List files associated with an agent
  5. vincular_arquivo_agente_tess - Links a file to an agent
  6. remover_arquivo_agente_tess - Removes the link between a file and an agent
  7. listar_arquivos_tess - List all available files
  8. obter_arquivo_tess - Gets details of a specific file
  9. enviar_arquivo_tess - Sends a new file to the TESS platform
  10. excluir_arquivo_tess - Deletes a file from the TESS platform

Usage with Docker

To run the server using Docker:

# Construir a imagem docker build -t mcp-server-tess . # Executar o container docker run -p 3000:3000 -e TESS_API_KEY=sua_chave_api_aqui mcp-server-tess

API Endpoints

  • GET /health - Server health check endpoint
  • GET /capabilities - Lists all available tools with their descriptions and parameters
  • POST /tools/:toolName - Runs a specific tool (replace :toolName with the name of the tool)

Usage example

With Smithery.ai

Once installed on Smithery.ai, you can use the server with any MCP-compatible LLM:

  1. Select the @diegofornalha/mcp-server-tess server in your LLM settings
  2. TESS API tools will automatically be available for your model

Via HTTP API

To run an agent:

curl -X POST http://localhost:3000/tools/executar_agente_tess \ -H "Content-Type: application/json" \ -d '{ "agent_id": "seu_agent_id", "model": "tess-ai-light", "messages": [ {"role": "user", "content": "Olá, como você está?"} ] }'

License

MIT

This server cannot be installed

-
security - not tested
F
license - not found
-
quality - not tested

How are these scores calculated?

hybrid server

The server is able to function both locally and remotely, depending on the configuration or use case.

A Model Context Protocol server that enables integration with the TESS API, allowing users to list and manage agents, execute agents with custom messages, and manage files through natural language interfaces.

  1. On
    1. Requirements
      1. Installation
        1. Via Smithery.ai (Recommended)
        2. Local Installation
      2. Settings
        1. Compilation
          1. Execution
            1. Available tools
              1. Usage with Docker
                1. API Endpoints
                  1. Usage example
                    1. With Smithery.ai
                    2. Via HTTP API
                  2. License

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