2025-rex _premiers_usages_et_retours_terrain

This MCP server presents the initial MCP usage scenarios and field feedback discussed during the 2025 session. Once started, it exposes a set of tools and data access capabilities that an LLM can discover and invoke through a standardized MCP client. You can connect your MCP client to the server to see the available tools, understand their input/output schemas, and test tool calls in real time. The server is designed to illustrate how tools can be discovered, bound to a context, and invoked dynamically by an AI agent to perform tasks such as data retrieval, reasoning over tool outputs, and orchestrating multiple actions in sequence.

Prerequisites:

• Node.js 18+ and npm (for the npx/npm installation path) or Python with uv/uvx if you prefer the Python transport. Optional Docker usage is supported if you want containerized execution.

Install via npx (Node.js):

• Ensure Node.js and npm are installed
• Run:

npx -y datacraft-mcp-premiers-usages@latest

Install via uvx (Python/uv) if you have the Python MCP client workflow:

• Ensure Python 3.8+ is installed
• Install uvx (if your environment uses uv/uvx tooling):

pipx install uvx

• Start the MCP server (example, depending on your setup):

uvx datacraft-mcp-premiers-usages@latest

Docker (optional):

• Build or pull the server image and run it:

docker run -i --rm datacraft/mcp-premiers-usages:latest

Notes:

• Replace the package name with the exact published MCP server package if the name differs in your environment.
• The server will typically start on localhost:8080 unless overridden by environment variables.

Tips and common considerations:

• Verify network access between the MCP client and the server. If you run locally, ensure MCP_HOST and MCP_PORT match your setup.
• If using npm/npx, you may want to pin the version (instead of latest) to maintain a stable schema.
• The server exposes tools whose schemas (inputs/outputs) may be documented in its API reference or via the MCP Inspector tooling.
• Environment variables like MCP_LOG_LEVEL can help with debugging; set to debug if you hit issues.
• If you encounter tool discovery issues, ensure the server has started correctly and that your MCP client is configured to connect to the same host/port.
• For production, consider running the server in a container and proxying through a secure connection; review the transport layer used by MCP (e.g., WebSocket, HTTP) in your environment.