What is the Model Context Protocol (MCP)?
MCP is a protocol that allows AI models to access external tools and prompts. The template provides an easy way to build an MCP‑compliant server.
@Nisarg38
Basic information
No overview available yet
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"mcp-server-template-nisarg38": {
"command": "python",
"args": [
"-m",
"src.main"
]
}
}
}Tool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
A ready‑to‑use template for building Model Context Protocol (MCP) servers in Python. It helps developers quickly create servers that register and expose tools and prompts for AI models to use.
Install with pip install -e ".[dev]" inside a cloned copy of the repository, then start the server with python -m src.main or the mcp-server-template CLI. Command‑line options let you change the port (--port), enable debug mode (--debug), switch transport (--transport stdio), or set the logging level (--log-level).
Dockerfile.MCP is a protocol that allows AI models to access external tools and prompts. The template provides an easy way to build an MCP‑compliant server.
Python 3.10 or newer.
Define a function in `src/main.py` and decorate it with `@mcp.tool()`. The function’s docstring serves as the description shown to the AI.
Build a Docker image with `docker build -t my-mcp-server .` and run it, or deploy the container to any cloud platform that supports containerised apps.
The server supports HTTP (default on port 8080) and stdio. Use `--transport stdio` to switch to the stdio transport.
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