MCP server that enables AI agents to perform intelligent web searches using OpenAI's o3 model with natural language queries
If you want an AI assistant working directly with O3 Search MCP, the o3 search mcp mcp server is the bridge. MCP server that enables AI agents to perform intelligent web searches using OpenAI's o3 model with natural language queries.
MCP server that enables the use of OpenAI's high-end models and their powerful web search capabilities. By registering it with any AI coding agent, the agent can autonomously consult with OpenAI models to solve complex problems.
Once connected, the assistant can call these 6 tools directly:
OPENAI_API_KEY — RequiredOPENAI_MODEL — OptionalSEARCH_CONTEXT_SIZE — OptionalREASONING_EFFORT — OptionalOPENAI_API_TIMEOUT — OptionalOPENAI_MAX_RETRIES — OptionalThe server is distributed via npm as o3-search-mcp, so most clients can run it without a manual build step. Add it to your MCP client's configuration and restart the client to pick it up — the copy-paste configs for Claude Desktop, Claude Code and Cursor are on this page.
Before the server will start you need to supply 6 environment variables: OPENAI_API_KEY, OPENAI_MODEL, SEARCH_CONTEXT_SIZE, REASONING_EFFORT, OPENAI_API_TIMEOUT, OPENAI_MAX_RETRIES. Keep credentials in your client's env block or a secrets manager rather than committing them.
AI-service servers chain other models into your assistant, turning a single chat into a small production pipeline. O3 Search MCP sits in that group, and the shape of its toolset — OPENAI_API_KEY, OPENAI_MODEL, SEARCH_CONTEXT_SIZE among others — tells you what it is really for. Worth comparing against the other ai services servers in this directory before you commit to one, since several overlap in scope but differ sharply in setup cost and permissions.
| Tool | What it does |
|---|---|
| OPENAI_API_KEY | Required |
| OPENAI_MODEL | Optional |
| SEARCH_CONTEXT_SIZE | Optional |
| REASONING_EFFORT | Optional |
| OPENAI_API_TIMEOUT | Optional |
| OPENAI_MAX_RETRIES | Optional |
json:
```jsonc
{
"mcpServers": {
"o3-search": {
"command": "npx",
"args": ["o3-search-mcp"],
"env": {
"OPENAI_API_KEY": "your-api-key",
// Optional: o3, o4-mini, gpt-5 (default: o3)
"OPENAI_MODEL": "o3",
// Optional: low, medium, high (default: medium)
"SEARCH_CONTEXT_SIZE": "medium",
"REASONING_EFFORT": "medium",
// Optional: API timeout in milliseconds (default: 300000)
"OPENAI_API_TIMEOUT": "300000",
// Optional: Maximum number of retries (default: 3)
"OPENAI_MAX_RETRIES": "3"
}
}
}
}Configuration as documented by the project. Restart the client after saving.
| Variable | Description | Required |
|---|---|---|
| OPENAI_API_KEY | Credential the server authenticates with. | Yes |
| OPENAI_MODEL | Configuration value read at startup. | Optional |
| SEARCH_CONTEXT_SIZE | Configuration value read at startup. | Optional |
| REASONING_EFFORT | Configuration value read at startup. | Optional |
| OPENAI_API_TIMEOUT | Configuration value read at startup. | Optional |
| OPENAI_MAX_RETRIES | Configuration value read at startup. | Optional |
Build a programmable telecommunications stack for connecting telephony services with the Internet via a cloud-based utility.
Search built for AI, not humans — semantic web search that returns model-ready content, plus code context.
Answers, not links — delegate questions to Perplexity's search-grounded models and get cited responses back.
Give your assistant a voice — text-to-speech, voice cloning and audio tools from the ElevenLabs API.
Give your assistant a real code sandbox — isolated cloud VMs for actually running the code it writes.
The ML hub in your context window — search models, datasets, papers and run Spaces from the official server.