Ai Smart Search

Name: Ai Smart Search
Author: asdqwsadq

@asdqwsadq

Repository

About Ai Smart Search

AI Smart Search MCP Tool - 深度搜索+AI智能分析，基于小米MiMo大模型和Tavily搜索

Basic information

Config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "mcp-ai-search": {
      "command": "python",
      "args": [
        "entry.py"
      ]
    }
  }
}

Tools

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Overview

What is Ai Smart Search?

Ai Smart Search is an MCP (Model Context Protocol) server that combines Tavily web search with Xiaomi MiMo AI (mimo-v2.5-pro) for deep analysis. It is designed for users who need structured search results with AI‑generated summaries and source references.

How to use Ai Smart Search?

Set the environment variables MIMO_API_KEY and TAVILY_API_KEY (and optionally MIMO_BASE_URL and MIMO_MODEL). Install dependencies with pip install -r requirements.txt, then run python entry.py in stdio mode, or add the server configuration to your MCP client. The single tool is deep_search(query, max_results=5, language="中文").

Key features of Ai Smart Search

Single MCP tool deep_search for combined web search and AI analysis
Integration with Tavily Search API
Deep analysis by Xiaomi MiMo AI model mimo-v2.5-pro
Structured output: AI analysis summary plus reference list
Configurable maximum results and language parameter
Uses stdio transport protocol

Use cases of Ai Smart Search

Researching a topic with web search followed by AI summarization
Getting answers with verified source references
Using Chinese‑language queries for localized results
Integrating deep search capabilities into MCP‑compatible tools or workflows

FAQ from Ai Smart Search

What API keys are required?

You need a valid Tavily API key and a valid Xiaomi MiMo API key.

What Python version is required?

Python 3.10 or higher.

What transport protocol does it use?

It uses stdio transport.

Can I use a different MiMo API endpoint or model?

Yes, the MIMO_BASE_URL and MIMO_MODEL environment variables allow you to change the API base URL and model name.

What does the `deep_search` tool return?

It returns a structured result containing an AI analysis summary and a list of reference sources.

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