MCP-Server-TESS
Enables containerized deployment of the MCP-Server-TESS with environment variable configuration for the TESS API key
Supports configuration management for storing TESS API credentials and server settings
Used for version control and installation of the MCP server via repository cloning
Provides runtime environment for the MCP server, with version 18+ required for executing the TESS API integration
Handles package management and provides scripts for building, starting, and development of the MCP server
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@MCP-Server-TESSlist all available agents"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
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
Related MCP server: SupaUI MCP Server
Requirements
Node.js 18+
A TESS platform API key
Installation
Via Smithery.ai (Recommended)
You can use this server directly in Smithery.ai:
Visit https://smithery.ai/server/@diegofornalha/mcp-server-tess
Click "Install"
Configure your TESS API key when prompted
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 installSettings
Create a
.envfile based on.env.exampleAdd your TESS API key:
TESS_API_KEY=sua_chave_api_aqui
PORT=3000Compilation
npm run buildExecution
To start the server in production mode:
npm startFor development with automatic reloading:
npm run devAvailable tools
The server exposes the following tools via HTTP API:
listar_agentes_tess- List all available agentsobter_agente_tess- Gets details of a specific agentexecutar_agente_tess- Runs an agent with custom messageslistar_arquivos_agente_tess- List files associated with an agentvincular_arquivo_agente_tess- Links a file to an agentremover_arquivo_agente_tess- Removes the link between a file and an agentlistar_arquivos_tess- List all available filesobter_arquivo_tess- Gets details of a specific fileenviar_arquivo_tess- Sends a new file to the TESS platformexcluir_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-tessAPI Endpoints
GET /health- Server health check endpointGET /capabilities- Lists all available tools with their descriptions and parametersPOST /tools/:toolName- Runs a specific tool (replace:toolNamewith 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:
Select the
@diegofornalha/mcp-server-tessserver in your LLM settingsTESS 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
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
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