Minimal MCP server implementation in pure Python.
A lightweight, handcrafted implementation of the Model Context Protocol focused on what most users actually need: exposing tools with clean Python type annotations.
- ✨ Zero dependencies - Pure Python, standard library only
- 🎯 Type-safe - Native Python type annotations for everything
- 🚀 Fast - Minimal overhead, maximum performance
- 🛠️ Handcrafted - Written by a human1, verified against the spec
- 🌐 HTTP/SSE transport - Streamable responses
- 📡 Stdio transport - For legacy clients
- 📦 Tiny - Less than 1,000 lines of code
pip install zeromcpOr with uv:
uv add zeromcpfrom typing import Annotated
from zeromcp import McpServer
mcp = McpServer("my-server")
@mcp.tool
def greet(
name: Annotated[str, "Name to greet"],
age: Annotated[int | None, "Age of person"] = None
) -> str:
"""Generate a greeting message"""
if age:
return f"Hello, {name}! You are {age} years old."
return f"Hello, {name}!"
if __name__ == "__main__":
mcp.serve("127.0.0.1", 8000)Then manually test your MCP server with the inspector:
npx -y @modelcontextprotocol/inspectorOnce things are working you can configure the mcp.json:
{
"mcpServers": {
"my-server": {
"type": "http",
"url": "http://127.0.0.1/mcp"
}
}
}For MCP clients that only support stdio transport:
from zeromcp import McpServer
mcp = McpServer("my-server")
@mcp.tool
def greet(name: str) -> str:
"""Generate a greeting"""
return f"Hello, {name}!"
if __name__ == "__main__":
mcp.stdio()Then configure in mcp.json (different for every client):
{
"mcpServers": {
"my-server": {
"command": "python",
"args": ["path/to/server.py"]
}
}
}zeromcp uses native Python Annotated types for schema generation:
from typing import Annotated, Optional, TypedDict, NotRequired
class GreetingResponse(TypedDict):
message: Annotated[str, "Greeting message"]
name: Annotated[str, "Name that was greeted"]
age: Annotated[NotRequired[int], "Age if provided"]
@mcp.tool
def greet(
name: Annotated[str, "Name to greet"],
age: Annotated[Optional[int], "Age of person"] = None
) -> GreetingResponse:
"""Generate a greeting message"""
if age is not None:
return {
"message": f"Hello, {name}! You are {age} years old.",
"name": name,
"age": age
}
return {
"message": f"Hello, {name}!",
"name": name
}Tools can accept multiple input types:
from typing import Annotated, TypedDict
class StructInfo(TypedDict):
name: Annotated[str, "Structure name"]
size: Annotated[int, "Structure size in bytes"]
fields: Annotated[list[str], "List of field names"]
@mcp.tool
def struct_get(
names: Annotated[list[str], "Array of structure names"]
| Annotated[str, "Single structure name"]
) -> list[StructInfo]:
"""Retrieve structure information by names"""
return [
{
"name": name,
"size": 128,
"fields": ["field1", "field2", "field3"]
}
for name in (names if isinstance(names, list) else [names])
]from zeromcp import McpToolError
@mcp.tool
def divide(
numerator: Annotated[float, "Numerator"],
denominator: Annotated[float, "Denominator"]
) -> float:
"""Divide two numbers"""
if denominator == 0:
raise McpToolError("Division by zero")
return numerator / denominatorExpose read-only data via URI patterns. Resources are serialized as JSON.
from typing import Annotated
@mcp.resource("file://data.txt")
def read_file() -> dict:
"""Get information about data.txt"""
return {"name": "data.txt", "size": 1024}
@mcp.resource("file://{filename}")
def read_any_file(
filename: Annotated[str, "Name of file to read"]
) -> dict:
"""Get information about any file"""
return {"name": filename, "size": 2048}The following clients have been tested:
- Claude Code
- Claude Desktop (stdio only)
- Visual Studio Code
- Roo Code / Cline / Kilo Code
- LM Studio
- Jan
- Gemini CLI
- Cursor
- Windsurf
- Zed (stdio only)
- Warp
Note: generally the /mcp endpoint is preferred, but not all clients support it correctly.