Agent skill

mcp-sdk-python-bootstrapper

Bootstrap MCP server with Python SDK, transport configuration, tool/resource handlers, and proper project structure.

Stars 514
Forks 31

Install this agent skill to your Project

npx add-skill https://github.com/a5c-ai/babysitter/tree/main/library/specializations/cli-mcp-development/skills/mcp-sdk-python-bootstrapper

SKILL.md

MCP SDK Python Bootstrapper

Bootstrap a complete MCP server using the Python SDK with proper project structure.

Capabilities

  • Generate Python MCP server project structure
  • Create tool and resource handlers
  • Configure stdio/SSE transport layers
  • Set up proper typing with Pydantic
  • Implement error handling patterns
  • Configure Poetry/pip project

Usage

Invoke this skill when you need to:

  • Bootstrap a new MCP server in Python
  • Create tools and resources for AI consumption
  • Set up MCP transport layer
  • Implement MCP protocol handlers

Inputs

Parameter Type Required Description
projectName string Yes Name of the MCP server project
description string Yes Description of the server
tools array No List of tools to implement
resources array No List of resources to expose
transport string No Transport type: stdio, sse (default: stdio)

Tool Structure

json
{
  "tools": [
    {
      "name": "search_files",
      "description": "Search for files matching a pattern",
      "parameters": {
        "pattern": { "type": "string", "description": "Search pattern" },
        "path": { "type": "string", "description": "Base path", "default": "." }
      }
    }
  ]
}

Output Structure

<projectName>/
├── pyproject.toml
├── README.md
├── .gitignore
├── src/
│   └── <package>/
│       ├── __init__.py
│       ├── __main__.py        # Entry point
│       ├── server.py          # MCP server setup
│       ├── tools/
│       │   ├── __init__.py
│       │   └── search.py      # Tool implementations
│       ├── resources/
│       │   ├── __init__.py
│       │   └── files.py       # Resource providers
│       └── types/
│           ├── __init__.py
│           └── schemas.py     # Pydantic models
└── tests/
    └── test_tools.py

Generated Code Patterns

Server Setup (src//server.py)

python
import asyncio
from mcp.server import Server
from mcp.server.stdio import stdio_server
from mcp.types import Tool, Resource

from .tools import register_tools
from .resources import register_resources

# Create server instance
server = Server("<projectName>")

# Register handlers
register_tools(server)
register_resources(server)

async def main():
    """Run the MCP server."""
    async with stdio_server() as (read_stream, write_stream):
        await server.run(
            read_stream,
            write_stream,
            server.create_initialization_options()
        )

def run():
    """Entry point for the server."""
    asyncio.run(main())

Tool Implementation (src//tools/search.py)

python
from typing import Any
from pydantic import BaseModel, Field
from mcp.server import Server
from mcp.types import Tool, TextContent

class SearchFilesInput(BaseModel):
    """Input schema for search_files tool."""
    pattern: str = Field(description="Search pattern (glob)")
    path: str = Field(default=".", description="Base path to search")

def register(server: Server) -> None:
    """Register the search_files tool."""

    @server.list_tools()
    async def list_tools() -> list[Tool]:
        return [
            Tool(
                name="search_files",
                description="Search for files matching a pattern",
                inputSchema=SearchFilesInput.model_json_schema()
            )
        ]

    @server.call_tool()
    async def call_tool(name: str, arguments: dict[str, Any]) -> list[TextContent]:
        if name != "search_files":
            raise ValueError(f"Unknown tool: {name}")

        # Validate input
        input_data = SearchFilesInput(**arguments)

        # Execute search
        from pathlib import Path
        matches = list(Path(input_data.path).glob(input_data.pattern))

        return [
            TextContent(
                type="text",
                text="\n".join(str(m) for m in matches)
            )
        ]

Resource Provider (src//resources/files.py)

python
from mcp.server import Server
from mcp.types import Resource, TextResourceContents

def register(server: Server) -> None:
    """Register file resources."""

    @server.list_resources()
    async def list_resources() -> list[Resource]:
        return [
            Resource(
                uri="file:///config",
                name="Configuration",
                description="Server configuration",
                mimeType="application/json"
            )
        ]

    @server.read_resource()
    async def read_resource(uri: str) -> TextResourceContents:
        if uri == "file:///config":
            return TextResourceContents(
                uri=uri,
                mimeType="application/json",
                text='{"version": "1.0.0"}'
            )
        raise ValueError(f"Unknown resource: {uri}")

Dependencies

toml
[tool.poetry.dependencies]
python = ">=3.10"
mcp = "^1.0.0"
pydantic = "^2.0.0"

[tool.poetry.group.dev.dependencies]
pytest = "^8.0.0"
pytest-asyncio = "^0.23.0"

Workflow

  1. Create project structure - Set up Python package
  2. Generate server - MCP server with transport
  3. Create tools - Tool handlers with schemas
  4. Create resources - Resource providers
  5. Add types - Pydantic models
  6. Set up tests - Async test fixtures

Target Processes

  • mcp-server-bootstrap
  • mcp-tool-implementation
  • mcp-resource-provider

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