AMiner MCP Server
💡 Core Advantage: Free Academic Data Access Currently, AMiner's core search interfaces (Scholar, Paper, and Patent Search) are free to use. This allows you to integrate massive global research data into your AI workflow with zero API costs, making it the most cost-effective solution for academic automation.
This directory provides a Model Context Protocol (MCP) server for accessing AMiner's open platform API.
Quick Install
Installation
pip install -e .Configuration
Set your AMiner API token as an environment variable:
Windows (PowerShell):
$env:AMINER_TOKEN="your_token_here"Linux/Mac:
export AMINER_TOKEN="your_token_here"Or create a .env file in your project root:
AMINER_TOKEN=your_token_hereUsage
Run the server:
python -m aminer_mcpOr use the command-line shortcut:
aminer-mcpFeatures
- Scholar Search: Find researchers by name or organization.
- Paper Search: Find papers by title.
- Patent Search: Search patents by keywords.
Setup
- Install Dependencies:
pip install "mcp[cli]" requests- Get API Token:
- Register at AMiner Open Platform. - Generate your API Key/Token.
- Configure Environment:
You can either set the AMINER_TOKEN environment variable manually or use the provided .env file.
Option A: Using .env (Recommended) A .env file has been created for you with your token. The server will automatically load it.
Option B: Manual Environment Variable
Windows (PowerShell):
$env:AMINER_TOKEN="your_token_here"Linux/Mac:
export AMINER_TOKEN="your_token_here"Running the Server
You can run the server directly or use it with an MCP client (like Claude Desktop or generic IDEs).
Quick Start (Recommended)
For a guided startup experience with environment and dependency checks:
Windows:
.\start_server.ps1Linux/Mac:
chmod +x start_server.sh
./start_server.shDirect Run (stdio)
python server.pyInspecting with MCP CLI
You can use the MCP CLI to inspect and test the server.
mcp dev server.pyTools Available
- search_scholar:
* name: Scholar name. * org: Organization. * offset: Pagination offset. * size: Result count.
- search_paper:
* title: Paper title. * page: Page number. * size: Result count.
- search_patent:
* query: Search query. * page: Page number. * size: Result count.
- get_papers_by_ids:
* ids: Comma-separated list of paper IDs.
- search_paper_pro (0.01 CNY/call):
* Fallback Tool: Use only when strictly necessary. * title, keyword, author, page, size.
API References
Configuration for Cursor IDE
To use this MCP server in Cursor editor, add the following configuration:
Windows (Cursor config path: %APPDATA%\Cursor\User\globalStorage\saoudrizwan.claude-dev\settings\cline_mcp_settings.json):
{
"mcpServers": {
"aminer": {
"command": "python",
"args": ["-m", "aminer_mcp"],
"env": {
"AMINER_TOKEN": ""
}
}
}
}Linux/Mac:
{
"mcpServers": {
"aminer": {
"command": "python3",
"args": ["-m", "aminer_mcp"],
"env": {
"AMINER_TOKEN": ""
}
}
}
}Note: Replace `` with your actual AMiner API token from AMiner Open Platform.
Contributing
Issues and Pull Requests are welcome!
Usage as an Agent Skill
This repository also includes an Agent Skill definition, allowing AI agents (like Cursor's Agent) to use AMiner search capabilities directly without a full MCP server setup for local tasks.
Skill Location: .agent/skills/aminer-search/
How it works
The skill wraps the AMiner client code into a simple CLI tool that agents can invoke to perform searches.
Prerequisite
Ensure the AMINER_TOKEN environment variable is set in your terminal or .env file.
Skill Capabilities
- Paper Search:
python .agent/skills/aminer-search/scripts/search_tool.py paper --title "..." - Scholar Search:
python .agent/skills/aminer-search/scripts/search_tool.py scholar --name "..." - Patent Search:
python .agent/skills/aminer-search/scripts/search_tool.py patent --query "..."
Agents detecting this skill will automatically know how to use these commands to fetch academic data for you.
License
MIT License
