# Source: https://docs.crewai.com/en/mcp/stdio.md

> ## Documentation Index
> Fetch the complete documentation index at: https://docs.crewai.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Stdio Transport

> Learn how to connect CrewAI to local MCP servers using the Stdio (Standard Input/Output) transport mechanism.

## Overview

The Stdio (Standard Input/Output) transport is designed for connecting `MCPServerAdapter` to local MCP servers that communicate over their standard input and output streams. This is typically used when the MCP server is a script or executable running on the same machine as your CrewAI application.

## Key Concepts

* **Local Execution**: Stdio transport manages a locally running process for the MCP server.
* **`StdioServerParameters`**: This class from the `mcp` library is used to configure the command, arguments, and environment variables for launching the Stdio server.

## Connecting via Stdio

You can connect to an Stdio-based MCP server using two main approaches for managing the connection lifecycle:

### 1. Fully Managed Connection (Recommended)

Using a Python context manager (`with` statement) is the recommended approach. It automatically handles starting the MCP server process and stopping it when the context is exited.

```python  theme={null}
from crewai import Agent, Task, Crew, Process
from crewai_tools import MCPServerAdapter
from mcp import StdioServerParameters
import os

# Create a StdioServerParameters object
server_params=StdioServerParameters(
    command="python3", 
    args=["servers/your_stdio_server.py"],
    env={"UV_PYTHON": "3.12", **os.environ},
)

with MCPServerAdapter(server_params) as tools:
    print(f"Available tools from Stdio MCP server: {[tool.name for tool in tools]}")

    # Example: Using the tools from the Stdio MCP server in a CrewAI Agent
    research_agent = Agent(
        role="Local Data Processor",
        goal="Process data using a local Stdio-based tool.",
        backstory="An AI that leverages local scripts via MCP for specialized tasks.",
        tools=tools,
        reasoning=True,
        verbose=True,
    )
    
    processing_task = Task(
        description="Process the input data file 'data.txt' and summarize its contents.",
        expected_output="A summary of the processed data.",
        agent=research_agent,
        markdown=True
    )
    
    data_crew = Crew(
        agents=[research_agent],
        tasks=[processing_task],
        verbose=True,
        process=Process.sequential 
    )
   
    result = data_crew.kickoff()
    print("\nCrew Task Result (Stdio - Managed):\n", result)

```

### 2. Manual Connection Lifecycle

If you need finer-grained control over when the Stdio MCP server process is started and stopped, you can manage the `MCPServerAdapter` lifecycle manually.

<Info>
  You **MUST** call `mcp_server_adapter.stop()` to ensure the server process is terminated and resources are released. Using a `try...finally` block is highly recommended.
</Info>

```python  theme={null}
from crewai import Agent, Task, Crew, Process
from crewai_tools import MCPServerAdapter
from mcp import StdioServerParameters
import os

# Create a StdioServerParameters object
stdio_params=StdioServerParameters(
    command="python3", 
    args=["servers/your_stdio_server.py"],
    env={"UV_PYTHON": "3.12", **os.environ},
)

mcp_server_adapter = MCPServerAdapter(server_params=stdio_params)
try:
    mcp_server_adapter.start()  # Manually start the connection and server process
    tools = mcp_server_adapter.tools
    print(f"Available tools (manual Stdio): {[tool.name for tool in tools]}")

    # Example: Using the tools with your Agent, Task, Crew setup
    manual_agent = Agent(
        role="Local Task Executor",
        goal="Execute a specific local task using a manually managed Stdio tool.",
        backstory="An AI proficient in controlling local processes via MCP.",
        tools=tools,
        verbose=True
    )
    
    manual_task = Task(
        description="Execute the 'perform_analysis' command via the Stdio tool.",
        expected_output="Results of the analysis.",
        agent=manual_agent
    )
    
    manual_crew = Crew(
        agents=[manual_agent],
        tasks=[manual_task],
        verbose=True,
        process=Process.sequential
    )
        
       
    result = manual_crew.kickoff() # Actual inputs depend on your tool
    print("\nCrew Task Result (Stdio - Manual):\n", result)
            
except Exception as e:
    print(f"An error occurred during manual Stdio MCP integration: {e}")
finally:
    if mcp_server_adapter and mcp_server_adapter.is_connected: # Check if connected before stopping
        print("Stopping Stdio MCP server connection (manual)...")
        mcp_server_adapter.stop()  # **Crucial: Ensure stop is called**
    elif mcp_server_adapter: # If adapter exists but not connected (e.g. start failed)
        print("Stdio MCP server adapter was not connected. No stop needed or start failed.")

```

Remember to replace placeholder paths and commands with your actual Stdio server details. The `env` parameter in `StdioServerParameters` can
be used to set environment variables for the server process, which can be useful for configuring its behavior or providing necessary paths (like `PYTHONPATH`).