mcputil
A lightweight library that converts MCP tools into Python tools (function-like objects).
Installation
pip install mcputil
Quickstart
(Check out the examples directory for runnable examples.)
Basic Usage
Given the following MCP server:
from mcp.server.fastmcp import FastMCP
mcp = FastMCP(name="Basic", log_level="ERROR")
@mcp.tool()
def add(a: int, b: int) -> int:
"""Add two numbers"""
return a + b
if __name__ == "__main__":
mcp.run(transport="stdio")
We can use mcputil to call the add tool easily:
import inspect
import mcputil
async def main():
async with mcputil.Client(
mcputil.Stdio(
command="python",
args=["/path/to/server.py"],
),
) as client:
tool: mcputil.Tool = (await client.get_tools())[0]
print(f"tool signature: {tool.name}{inspect.signature(tool)}")
output = await tool(a=1, b=2)
print(f"tool output: {output}")
# Output:
# tool signature: add(a: int, b: int) -> int
# tool output: 3
Progress Tracking
Given the following MCP server (see here):
from mcp.server.fastmcp import Context, FastMCP
from mcp.server.session import ServerSession
mcp = FastMCP(name="Progress")
@mcp.tool()
async def long_running_task(
task_name: str, ctx: Context[ServerSession, None], steps: int = 5
) -> str:
"""Execute a task with progress updates."""
for i in range(steps):
progress = (i + 1) / steps
await ctx.report_progress(
progress=progress,
total=1.0,
message=f"Step {i + 1}/{steps}",
)
return f"Task '{task_name}' completed"
if __name__ == "__main__":
mcp.run(transport="streamable-http")
python server.py
We can use mcputil to track the progress of the long_running_task tool:
import inspect
import mcputil
async def main():
async with mcputil.Client(
mcputil.StreamableHTTP(url="http://localhost:8000"),
) as client:
tool: mcputil.Tool = (await client.get_tools())[0]
print(f"tool signature: {tool.name}{inspect.signature(tool)}")
result: mcputil.Result = await tool.call(
"call_id_0", task_name="example-task", steps=5
)
async for event in result.events():
if isinstance(event, mcputil.ProgressEvent):
print(f"tool progress: {event}")
elif isinstance(event, mcputil.OutputEvent):
print(f"tool output: {event.output}")
# Output:
# tool signature: long_running_task(task_name: str, steps: int = 5) -> str
# tool progress: ProgressEvent(progress=0.2, total=1.0, message='Step 1/5')
# tool progress: ProgressEvent(progress=0.4, total=1.0, message='Step 2/5')
# tool progress: ProgressEvent(progress=0.6, total=1.0, message='Step 3/5')
# tool progress: ProgressEvent(progress=0.8, total=1.0, message='Step 4/5')
# tool progress: ProgressEvent(progress=1.0, total=1.0, message='Step 5/5')
# tool output: Task 'example-task' completed
Multiple MCP Servers
mcputil also supports managing multiple MCP servers using the Group class:
import inspect
import mcputil
async def main():
async with mcputil.Group(
math=mcputil.Stdio(
command="python",
args=["/path/to/server.py"],
),
progress=mcputil.StreamableHTTP(url="http://localhost:8000"),
) as group:
tools: list[mcputil.Tool] = await group.get_tools()
for tool in tools:
print(f"tool signature: {tool.name}{inspect.signature(tool)}")
if tool.name == "add":
output = await tool(a=1, b=2)
print(f"tool output: {output}\n")
elif tool.name == "long_running_task":
result: mcputil.Result = await tool.call(
"call_id_0", # non-empty call ID for tracking progress
task_name="example-task",
steps=5,
)
async for event in result.events():
if isinstance(event, mcputil.ProgressEvent):
print(f"tool progress: {event}")
elif isinstance(event, mcputil.OutputEvent):
print(f"tool output: {event.output}")
# Output:
# tool signature: add(a: int, b: int) -> int
# tool output: 3
#
# tool signature: long_running_task(task_name: str, steps: int = 5) -> str
# tool progress: ProgressEvent(progress=0.2, total=1.0, message='Step 1/5')
# tool progress: ProgressEvent(progress=0.4, total=1.0, message='Step 2/5')
# tool progress: ProgressEvent(progress=0.6, total=1.0, message='Step 3/5')
# tool progress: ProgressEvent(progress=0.8, total=1.0, message='Step 4/5')
# tool progress: ProgressEvent(progress=1.0, total=1.0, message='Step 5/5')
# tool output: Task 'example-task' completed
Additionally, you can also call tools by their names without fetching them first:
import inspect
import mcputil
async def main():
async with mcputil.Group(
math=mcputil.Stdio(
command="python",
args=["/path/to/server.py"],
),
progress=mcputil.StreamableHTTP(url="http://localhost:8000"),
) as group:
result: mcputil.Result = await group.call_tool("math", "add", a=1, b=2)
output = await result.output()
print(f"tool output: {output}\n")
result: mcputil.Result = await group.call_tool(
"progress",
"long_running_task",
call_id="call_id_0", # non-empty call ID for tracking progress
task_name="example-task",
steps=5,
)
async for event in result.events():
if isinstance(event, mcputil.ProgressEvent):
print(f"tool progress: {event}")
elif isinstance(event, mcputil.OutputEvent):
print(f"tool output: {event.output}")
# Output:
# tool output: 3
#
# tool progress: ProgressEvent(progress=0.2, total=1.0, message='Step 1/5')
# tool progress: ProgressEvent(progress=0.4, total=1.0, message='Step 2/5')
# tool progress: ProgressEvent(progress=0.6, total=1.0, message='Step 3/5')
# tool progress: ProgressEvent(progress=0.8, total=1.0, message='Step 4/5')
# tool progress: ProgressEvent(progress=1.0, total=1.0, message='Step 5/5')
# tool output: Task 'example-task' completed
Agent Framework Integration
Given the following MCP Server:
from mcp.server.fastmcp import FastMCP
mcp = FastMCP(name="Basic")
@mcp.tool()
def get_weather(city: str) -> str:
"""Get the weather for a given city."""
return f"The weather in {city} is sunny."
if __name__ == "__main__":
mcp.run(transport="streamable-http")
LangChain
from langchain.tools import tool
from langchain.agents import create_agent
import mcputil
async def main():
async with mcputil.Client(
mcputil.StreamableHTTP(url="http://localhost:8000"),
) as client:
mcp_tools: list[mcputil.Tool] = await client.get_tools()
agent = create_agent(
"openai:gpt-5",
tools=[tool(t) for t in mcp_tools],
)
OpenAI Agents SDK
from agents import Agent, function_tool
import mcputil
async def main():
async with mcputil.Client(
mcputil.StreamableHTTP(url="http://localhost:8000"),
) as client:
mcp_tools: list[mcputil.Tool] = await client.get_tools()
agent = Agent(
name="Hello world",
instructions="You are a helpful agent.",
tools=[function_tool(t) for t in mcp_tools],
)
Pydantic AI
import mcputil
from pydantic_ai import Agent
async def main():
async with mcputil.Client(
mcputil.StreamableHTTP(url="http://localhost:8000"),
) as client:
mcp_tools: list[mcputil.Tool] = await client.get_tools()
agent = Agent(
"google-gla:gemini-2.5-flash",
deps_type=str,
tools=mcp_tools,
system_prompt="You are a helpful agent.",
)
CLI
mcputil also comes with a CLI for generating a file tree of all available tools from connected MCP servers, which helps with Code execution with MCP. Checkout out the example.
Usage:
$ mcputil -h
usage: mcputil [-h] [-s SERVER] [-c CONFIG] [-o OUTPUT]
mcputil - Generate Python functions from MCP server tools
options:
-h, --help show this help message and exit
-s SERVER, --server SERVER
Server configuration as JSON. Format: {"name": "server_name", "url": "server_url",
"headers": {...}, "timeout": 30}
-c CONFIG, --config CONFIG
Path to MCP configuration file (mcp.json format)
-o OUTPUT, --output OUTPUT
Output directory path. Default: 'servers'
Examples:
# Single server via --server
mcputil --server='{"name": "math", "url": "http://localhost:8000"}'
# Multiple servers via --server
mcputil --server='{"name": "math", "url": "http://localhost:8000"}' \
--server='{"name": "weather", "url": "http://localhost:8001"}'
# With custom headers and timeout via --server
mcputil --server='{"name": "api", "url": "http://api.example.com", "headers": {"Authorization": "Bearer token"}, "timeout": 60}'
# Using configuration file
mcputil --config mcp.json
# Configuration file with custom output directory
mcputil --config mcp.json --output my_servers
[!NOTE] Example
mcp.json:{ "mcpServers": { "local-server": { "command": "python", "args": ["mcp-server.py"], "env": { "API_KEY": "value" } }, "remote-server": { "url": "http://localhost:3000/mcp", "headers": { "API_KEY": "value" } } } }