Minimax Search
MiniMax Search is an MCP (Model Context Protocol) server that provides web search and browsing capabilities.
Installation
npx minimax-searchAsk AI about Minimax Search
Powered by Claude Β· Grounded in docs
I know everything about Minimax Search. Ask me about installation, configuration, usage, or troubleshooting.
0/500
Reviews
Documentation
MiniMax Search MCP Server
MiniMax Search is an MCP (Model Context Protocol) server that provides web search and browsing capabilities.
π§ Version Notes
This project uses the standard MCP Server protocol, compliant with MCP specifications:
- β
Complete
list_tools()implementation - β
Complete
call_tool()implementation - β
Standard
stdio_server()communication
Features
- π Multi-Engine Search: Supports Google search engine
- π Parallel Search: Native support for parallel multi-query search
- π Batch Browsing: Support for batch browsing of multiple URLs
- π€ Intelligent Understanding: Uses MiniMax LLM to understand web content and answer questions
- π― Advanced Search: Supports Google advanced search syntax
- π Auto Fallback: Automatically switches to other engines when search fails
Quick Start
Install via Git (Recommended)
# Run directly from Git repository
uvx --from git+ssh://git@github.com:MiniMax-AI/minimax_search.git minimax-search
Install via Local Path (Development)
# Run from local directory
uvx --from /xxx/minimax_search minimax-search
MCP Client Configuration
Add to your MCP client configuration file (e.g., mcp.json):
{
"mcpServers": {
"minimax_search": {
"command": "uvx",
"args": [
"--from",
"git+ssh://git@github.com:MiniMax-AI/minimax_search.git",
"minimax-search"
],
"env": {
"MINIMAX_API_KEY": "your_minimax_api_key",
"SERPER_API_KEY": "your_serper_api_key",
"JINA_API_KEY": "your_jina_api_key"
}
}
}
}
Available Tools
1. search - Parallel Web Search
Search multiple queries simultaneously, returning brief results (title, URL, snippet).
Parameters:
queries(array of strings, required): List of queries, supports Google advanced search syntax
Supported Search Engines:
- Google Search (via Serper API)
Advanced Search Syntax:
site:example.com- Limit to specific siteintitle:keyword- Title contains keywordinurl:keyword- URL contains keyword"exact match"- Exact phrase match
Example:
{
"queries": ["Python asyncio tutorial", "Python threading vs asyncio"]
}
2. browse - Batch Intelligent Browsing
Visit multiple web pages, use MiniMax LLM to understand content and answer questions.
Parameters:
urls(array of strings, required): List of target web page URLsquery(string, required): Question to be answered
Example:
{
"urls": [
"https://docs.python.org/3/library/asyncio.html",
"https://realpython.com/async-io-python/"
],
"query": "Summarize the main features and use cases of asyncio"
}
Environment Variables Configuration
Required Environment Variables
Basic Search Functionality:
SERPER_API_KEY: Google Search- Get it from: https://serper.dev/
- Free tier: 2,500 requests/month
Web Browsing Functionality:
JINA_API_KEY: Web content reading- Get it from: https://jina.ai/
- Free tier available
Browse Functionality (LLM Understanding):
MINIMAX_API_KEY: MiniMax API Key- Get it from: https://platform.minimax.io/
Usage Examples
Using in an Agent
Once the MCP server is started, the Agent can use the following tools:
Parallel search for multiple queries:
User: Search for "Python asyncio" and "Python threading" differences simultaneously
Agent: [Calls search tool]
β search(queries=["Python asyncio", "Python threading"])
β Returns search results for both queries (executed in parallel)
Batch browse multiple web pages:
User: Visit these links and summarize the main features of asyncio
- https://docs.python.org/3/library/asyncio.html
- https://realpython.com/async-io-python/
Agent: [Calls browse tool]
β browse(
urls=["https://docs.python.org/...", "https://realpython.com/..."],
query="Summarize the main features of asyncio"
)
β Returns comprehensive summary and answer
Technical Implementation
Project Structure
minimax_search/
βββ server.py # MCP Server entry point (2 tools)
βββ minimax_search_browse.py # Core search and browse implementation
βββ pyproject.toml # Project configuration
βββ README.md
Core Features
Parallel Search:
- Native support for queries array
- Concurrent execution using thread pool
- Automatic formatting and grouping of results
Batch Browsing:
- Native support for urls array
- Jina Reader extracts web content (converts to Markdown)
- MiniMax LLM understands content and generates comprehensive answers
License
MIT
This project is based on the MiniMax-M2 Model project
