Claude-skill-registry-data mcp-server-stdio
Creates and configures stdio Model Context Protocol (MCP) server connections for OpenAI Agents SDK
install
source · Clone the upstream repo
git clone https://github.com/majiayu000/claude-skill-registry-data
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/majiayu000/claude-skill-registry-data "$T" && mkdir -p ~/.claude/skills && cp -r "$T/data/mcp-server-stdio" ~/.claude/skills/majiayu000-claude-skill-registry-data-mcp-server-stdio && rm -rf "$T"
manifest:
data/mcp-server-stdio/SKILL.mdsource content
Stdio MCP Server Skill
This skill helps create and configure stdio Model Context Protocol (MCP) server connections for OpenAI Agents SDK.
Purpose
- Create MCPServerStdio configurations
- Configure local subprocess parameters
- Connect to MCP servers that run as local processes
- Use stdio transport for local MCP server communication
MCPServerStdio Constructor Parameters
- params (MCPServerStdioParams): Process parameters for the server
- command (str): The executable to run to start the server (e.g.,
orpython
)node - args (list[str], optional): Command line args to pass to the command (e.g.,
or['foo.py']
)['server.js', '--port', '8080'] - env (dict[str, str], optional): The environment variables to set for the server
- cwd (str | Path, optional): The working directory to use when spawning the process
- encoding (str, optional): The text encoding used when sending/receiving messages to the server (default:
)utf-8 - encoding_error_handler (Literal["strict", "ignore", "replace"], optional): The text encoding error handler (default:
)strict
- command (str): The executable to run to start the server (e.g.,
- cache_tools_list (bool): Whether to cache the list of available tools (default: False)
- name (string | None): A readable name for the server (default: None, auto-generated)
- client_session_timeout_seconds (float | None): The read timeout passed to the MCP ClientSession (default: 5)
- tool_filter (ToolFilter): The tool filter to use for filtering tools (default: None)
- use_structured_content (bool): Whether to use tool_result.structured_content when calling an MCP tool (default: False)
- max_retry_attempts (int): Number of times to retry failed list_tools/call_tool calls (default: 0)
- retry_backoff_seconds_base (float): The base delay, in seconds, for exponential backoff between retries (default: 1.0)
- message_handler (MessageHandlerFnT | None): Optional handler invoked for session messages (default: None)
Usage Context
Use this skill when:
- Working with MCP servers that run as local subprocesses
- Needing to communicate with command-line MCP server implementations
- Using stdio-based MCP server implementations
- Running MCP servers in local development environments
- When the server only exposes a command line entry point
Basic Example
import asyncio from pathlib import Path from agents import Agent, Runner from agents.mcp import MCPServerStdio current_dir = Path(__file__).parent samples_dir = current_dir / "sample_files" async def main() -> None: async with MCPServerStdio( name="Filesystem Server via npx", params={ "command": "npx", "args": ["-y", "@modelcontextprotocol/server-filesystem", str(samples_dir)], }, ) as server: agent = Agent( name="Assistant", instructions="Use the files in the sample directory to answer questions.", mcp_servers=[server], ) result = await Runner.run(agent, "List the files available to you.") print(result.final_output) asyncio.run(main())