Skip to main content

MCP server for OpenAI agents and agents tools.

Project description

OpenAI Agents MCP Server

smithery badge

A Model Context Protocol (MCP) server that exposes OpenAI agents through the MCP protocol.

Features

This server exposes both individual agents and a multi-agent orchestrator using the OpenAI Agents SDK:

Individual Specialized Agents

  • Web Search Agent: A specialized agent for searching the web for real-time information
  • File Search Agent: A specialized agent for searching and analyzing files in OpenAI's vector store
  • Computer Action Agent: A specialized agent for performing actions on your computer safely

Multi-Agent Orchestrator

  • Orchestrator Agent: A powerful agent that can coordinate between the specialized agents, choosing the right one(s) for each task

Each agent is accessed through the MCP protocol, making them available to any MCP client, including the Claude desktop app.

Installation

Prerequisites

  • Python 3.11 or higher
  • uv package manager (recommended)
  • OpenAI API key

Installing via Smithery

To install openai-agents-mcp-server for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install @lroolle/openai-agents-mcp-server --client claude

Claude Desktop

"mcpServers": {
  "openai-agents-mcp-server": {
    "command": "uvx",
    "args": ["openai-agents-mcp-server"],
    "env": {
        "OPENAI_API_KEY": "your-api-key-here"
    }
  }
}

Implementation Details

Tool Requirements

  • WebSearchTool: No required parameters, but can accept optional location context
  • FileSearchTool: Requires vector_store_ids (IDs from your OpenAI vector stores)
  • ComputerTool: Requires an AsyncComputer implementation (currently simulated)

Customization

You can customize this server by:

  1. Implementing a full AsyncComputer interface to enable real computer interactions
  2. Adding additional specialized agents for other OpenAI tools
  3. Enhancing the orchestrator agent to handle more complex workflows

Configuration

You can configure the server using environment variables:

  • OPENAI_API_KEY: Your OpenAI API key (required)
  • MCP_TRANSPORT: Transport protocol to use (default: "stdio", can be "sse")

Development

Setup development environment

# Clone the repository
git clone https://github.com/lroolle/openai-agents-mcp-server.git
cd openai-agents-mcp-server

# Create a virtual environment
uv venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate

# Install dependencies
uv sync --dev

Testing with MCP Inspector

You can test the server using the MCP Inspector:

# In one terminal, run the server with SSE transport
export OPENAI_API_KEY=your-api-key
export MCP_TRANSPORT=sse

uv run mcp dev src/agents_mcp_server/server.py

Then open a web browser and navigate to http://localhost:5173.

License

MIT

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

iflow_mcp_lroolle_agents_mcp_server-0.1.0.tar.gz (36.0 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

File details

Details for the file iflow_mcp_lroolle_agents_mcp_server-0.1.0.tar.gz.

File metadata

  • Download URL: iflow_mcp_lroolle_agents_mcp_server-0.1.0.tar.gz
  • Upload date:
  • Size: 36.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.10.0 {"installer":{"name":"uv","version":"0.10.0","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Debian GNU/Linux","version":"13","id":"trixie","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":null}

File hashes

Hashes for iflow_mcp_lroolle_agents_mcp_server-0.1.0.tar.gz
Algorithm Hash digest
SHA256 b219cab9343d69f1ee08f7c6e8c18031238e8bfbf67a6a2abdbf1c55ea75b852
MD5 cf2e0b3b49838bed4407e2f08355f306
BLAKE2b-256 3c1b2457e63291dd445560663a9aeec0f8a60e53583c8c95e9ee5afa72fd45b9

See more details on using hashes here.

File details

Details for the file iflow_mcp_lroolle_agents_mcp_server-0.1.0-py3-none-any.whl.

File metadata

  • Download URL: iflow_mcp_lroolle_agents_mcp_server-0.1.0-py3-none-any.whl
  • Upload date:
  • Size: 9.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.10.0 {"installer":{"name":"uv","version":"0.10.0","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Debian GNU/Linux","version":"13","id":"trixie","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":null}

File hashes

Hashes for iflow_mcp_lroolle_agents_mcp_server-0.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 c69be9f1830b07a75ce2d1c73f727c2a655dad1490ad3aebaabba9ee708bb24e
MD5 20ac5b6e2ae14306e7f2b3ee7cf46f5e
BLAKE2b-256 80d3f186f589d8c58cc32280bc8f39fb2ec0320167ce190bbbb1ab93e0138af0

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page