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OpenAI o3 Search

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yoshiko-pg

MCP server for OpenAI o3 web search

Publisheryoshiko-pg
Repositoryo3-search-mcp
LanguageJavaScript
Forks
42
Stars
286
Available tools
0
Transport typestdio
Categories
LicenseMIT
Links
  • Connect tools to AI workflows

    OpenAI o3 Search exposes MCP capabilities that can be used by compatible AI clients and agents.

  • 0 available tools

    Browse the callable actions below, including names and descriptions when provided by the server.

  • Ready-to-copy setup

    Use the installation snippets to configure this server in your preferred MCP client.

  • Open source signals

    286 stars and 42 forks from the linked repository.

o3-search-mcp (gpt-5, o4-mini support)

Verified on MseeP

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.

Use Cases

(Although called o3 to match the MCP name, you can specify gpt-5 or o4-mini via env for the model to use)

🐛 When you're stuck debugging

o3's web search can scan a wide range of sources, including GitHub issues and Stack Overflow, significantly increasing the chances of resolving niche problems. Example prompts:

> I'm getting the following error on startup, please fix it. If it's too difficult, ask o3.
> [Paste error message here]
> The WebSocket connection isn't working. Please debug it. If you don't know how, ask o3.

📚 When you want to reference the latest library information

You can get answers from the powerful web search even when there's no well-organized documentation. Example prompts:

> I want to upgrade this library to v2. Proceed while consulting with o3.
> I was told this option for this library doesn't exist. It might have been removed. Ask o3 what to specify instead and replace it.

🧩 When tackling complex tasks

In addition to search, you can also use it as a sounding board for design. Example prompts:

> I want to create a collaborative editor, so please design it. Also, ask o3 for a design review and discuss if necessary.

Also, since it's provided as an MCP server, the AI agent may decide on its own to talk to o3 when it deems it necessary, without any instructions from you. This will dramatically expand the range of problems it can solve on its own!

Installation

npx (Recommended)

Claude Code:

sh
$ claude mcp add o3 \
	-s user \  # If you omit this line, it will be installed in the project scope
	-e OPENAI_MODEL=o3 \ # o4-mini, gpt-5 also available
	-e OPENAI_API_KEY=your-api-key \
	-e SEARCH_CONTEXT_SIZE=medium \
	-e REASONING_EFFORT=medium \
	-e OPENAI_API_TIMEOUT=300000 \
	-e OPENAI_MAX_RETRIES=3 \
	-- npx o3-search-mcp

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"
      }
    }
  }
}

Local Setup

If you want to download the code and run it locally:

bash
git clone git@github.com:yoshiko-pg/o3-search-mcp.git
cd o3-search-mcp
pnpm install
pnpm build

Claude Code:

sh
$ claude mcp add o3 \
	-s user \  # If you omit this line, it will be installed in the project scope
	-e OPENAI_MODEL=o3 \ # o4-mini, gpt-5 also available
	-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 \
	-- node /path/to/o3-search-mcp/build/index.js

json:

jsonc
{
  "mcpServers": {
    "o3-search": {
      "command": "node",
      "args": ["/path/to/o3-search-mcp/build/index.js"],
      "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"
      }
    }
  }
}

Environment Variables

Environment VariableOptionsDefaultDescription
OPENAI_API_KEYRequired-OpenAI API Key
OPENAI_MODELOptionalo3Model to useValues: o3, o4-mini, gpt-5
SEARCH_CONTEXT_SIZEOptionalmediumControls the search context sizeValues: low, medium, high
REASONING_EFFORTOptionalmediumControls the reasoning effort levelValues: low, medium, high
OPENAI_API_TIMEOUTOptional300000API request timeout in millisecondsExample: 300000 for 5 minutes
OPENAI_MAX_RETRIESOptional3Maximum number of retries for failed requestsThe SDK automatically retries on rate limits (429), server errors (5xx), and connection errors

Notes

To use the o3 model from the OpenAI API, you need to either raise your tier to 4 or verify your organization. If you register an API key that is not yet enabled for o3 with this MCP, calls will result in an error. Reference: https://help.openai.com/en/articles/10362446-api-access-to-o1-o3-and-o4-models

Installation

TypingMind
Prerequisites:

Node.js 18+

{
  "mcpServers": {
    "o3-search": {
      "command": "npx",
      "args": [
        "o3-search-mcp"
      ],
      "env": {
        "OPENAI_API_KEY": "your-api-key",
        "SEARCH_CONTEXT_SIZE": "medium",
        "REASONING_EFFORT": "medium",
        "OPENAI_API_TIMEOUT": "60000",
        "OPENAI_MAX_RETRIES": "3"
      }
    }
  }
}

Use OpenAI o3 Search MCP with multiple AI models

TypingMind connects MCP tools at the workspace level, so once OpenAI o3 Search is connected, you can use it with different AI models in TypingMind instead of setting it up separately for each model. This MCP runs locally through the TypingMind MCP connector on your device.

Setup guide to use the local connector

Use this when the MCP server needs access to local files, apps, or private resources on your computer.

1

Open the MCP settings

In TypingMind, go to Settings, Advanced Settings, then Model Context Protocol and choose Setup Connector.

  1. Open TypingMind in your browser.
  2. Click the Settings icon.
  3. Go to Advanced Settings.
  4. Open the Model Context Protocol section.
  5. Click Setup Connector and choose This Device.
TypingMind MCP connector setup screen with This Device selected
2

Run the connector command

Choose This Device, copy the command from TypingMind, and run it in Terminal. Keep the process running while you use MCP.

  1. Copy the setup command shown by TypingMind.
  2. Open Terminal on macOS or Windows Terminal on Windows.
  3. Paste and run the command.
  4. Approve the package install if Terminal asks you to proceed.
  5. Keep the Terminal window running while using MCP tools.
3

Add OpenAI o3 Search as a server

When the connector status is Ready, click Edit Servers and paste the MCP server configuration.

  1. Wait until the connector status shows Ready.
  2. Click Edit Servers.
  3. Paste the OpenAI o3 Search MCP server configuration.
  4. Save the server list.
  5. Refresh if you want to confirm the connector is still ready.
TypingMind MCP settings showing active server and Edit Servers button
{
  "mcpServers": {
    "openai-o3-search": {
      "command": "npx",
      "args": [
        "-y",
        "o3-search-mcp"
      ]
    }
  }
}
4

Use it across models

Save the server list, open Plugins, enable the OpenAI o3 Search MCP tools, then select any supported AI model in TypingMind and use the tools in chat or assign them to an AI agent.

  1. Open the Plugins page in TypingMind.
  2. Enable the OpenAI o3 Search MCP tools.
  3. Start a chat and choose the AI model you want to use.
  4. Use the MCP tools in chat or assign them to an AI agent.
  5. Switch to another AI model whenever needed without reconnecting MCP.
TypingMind chat using enabled MCP tools with a selected AI model
Can you use OpenAI o3 Search to help me with this task?
OpenAI o3 Search
Sure. I read it.
Here is what I found using OpenAI o3 Search.

Frequently asked questions

What is the OpenAI o3 Search MCP server used for?

OpenAI o3 Search is an MCP server that lets compatible AI clients connect to external tools and context. In TypingMind, you can add this MCP server once and make its tools available in your AI workspace.

Can I use OpenAI o3 Search MCP with multiple AI models in TypingMind?

Yes. TypingMind connects MCP tools at the workspace level, so you can use OpenAI o3 Search with different AI models such as Claude, ChatGPT, Gemini, or other models you have configured in TypingMind without setting up the MCP server separately for each model.

Why use OpenAI o3 Search MCP with TypingMind?

TypingMind is one of the best frontends for LLM chat because it brings multiple AI models, prompts, plugins, AI agents, API keys, and MCP tools into one workspace. With OpenAI o3 Search connected, you can use its MCP tools across your preferred models while keeping your chat workflow organized in TypingMind.

How do I connect OpenAI o3 Search MCP to TypingMind?

OpenAI o3 Search runs through the TypingMind local MCP connector. This is best when the MCP server needs access to local files, desktop apps, command-line tools, or private resources on your computer.

What tools does OpenAI o3 Search MCP provide in TypingMind?

OpenAI o3 Search exposes MCP capabilities that can be enabled from the TypingMind Plugins page and used in chat or assigned to AI agents.

Do I need to share my API keys with TypingMind to use OpenAI o3 Search MCP?

No. TypingMind is local-first and lets you keep your model providers, API keys, prompts, and MCP configuration under your control. If OpenAI o3 Search requires authentication, add the required headers, OAuth settings, or local configuration for that MCP server when you create the connection.

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