Best for
- Developers using Claude Code or other AI coding agents to incorporate real-time information.
- Developers needing to resolve rare errors or lacking documentation.
- Developers needing design review or complex problem-solving support.
O
o3 Search MCP Server
Community
MCP server that enables the use of OpenAI's high-end models and their powerful web search capabilities.
GitHub source repository ↗
34FMRS · D
This server provides a convenient way to integrate OpenAI's advanced search capabilities via MCP, suitable for coding scenarios needing real-time info. However, it requires an OpenAI API key and possibly access permissions.
o3-search-mcp is an MCP server that allows AI coding agents (such as Claude Code) to autonomously consult OpenAI's advanced models for web search, helping solve complex problems. By integrating this server, agents can access real-time information from a wide range of sources, including GitHub issues and Stack Overflow, significantly increasing the chances of resolving niche issues. The server supports specifying OpenAI models (e.g., o3, o4-mini, gpt-5) and offers configurable parameters such as search context size and reasoning effort.
Tools
The tool list has not been reviewed yet.
Setup
Recommended installation via npx: run claude mcp add o3 -s user -e OPENAI_API_KEY=your-api-key -e OPENAI_MODEL=o3 -e SEARCH_CONTEXT_SIZE=medium -e REASONING_EFFORT=medium -e OPENAI_API_TIMEOUT=300000 -e OPENAI_MAX_RETRIES=3 -- npx o3-search-mcp. Alternatively, clone the repo and build locally: git clone [email protected]:yoshiko-pg/o3-search-mcp.git && cd o3-search-mcp && pnpm install && pnpm build, then configure to run node /path/to/o3-search-mcp/build/index.js.
claude_desktop_config.json
{
"mcpServers": {
"o3-search": {
"command": "npx",
"args": [
"o3-search-mcp"
],
"env": {
"OPENAI_API_KEY": "your-api-key",
"OPENAI_MODEL": "o3",
"SEARCH_CONTEXT_SIZE": "medium",
"REASONING_EFFORT": "medium",
"OPENAI_API_TIMEOUT": "300000",
"OPENAI_MAX_RETRIES": "3"
}
}
}
}
Fit and risk
Not for
- Users who don't want to depend on OpenAI API or lack an API key.
- Users needing search capabilities via non-OpenAI models.
- Users needing offline search or local search abilities.
Required permissions
- Requires a valid OpenAI API key, and possibly API tier 4 or organization verification for o3 model access.
- Network access to OpenAI API.
- Write permissions for configuration directory during installation.
Risks and side effects
- API key leakage: ensure key is kept secure and not committed to public repositories.
- API usage may incur costs; monitor usage.
- AI agent may provide inaccurate info; verify critical results.
- Dependency on OpenAI service availability and potential rate limits.
Troubleshooting
- If calls fail, check that OPENAI_API_KEY is correctly set and that your account has permission to access the selected model (e.g., o3).
- Verify network connectivity.
- Adjust OPENAI_MAX_RETRIES and OPENAI_API_TIMEOUT if encountering rate limits or timeouts.
- Ensure MCP configuration command and arguments are correct.
Use cases
When stuck debugging, let o3 search broadly (e.g., GitHub issues, Stack Overflow) to find solutions.
Reference latest library information even without well-organized documentation.
Use as a sounding board for design reviews and complex task discussions.
AI agent autonomously decides to consult o3 when it deems necessary, expanding its problem-solving range.
Supported clients
Claude DesktopFull support