OpenAlex MCP Server

by reetp14

204 downloads
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GitHub

About

openalex-mcp is a mcp server which provide AI agents with tools to interact with OpenAlex.

Details

Author
reetp14
Downloads
204
Categories
Other

- Search over 240 million scholarly works
- Retrieve authors with ORCID integration
- Access ~250K sources (journals, conferences, repositories)
- Institutions with ROR matching
- Hierarchical research concepts (levels 0-5)
- Full OpenAlex query grammar for filtering and sorting

Setting up with Highlight

This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:

  1. Download and install Highlight from highlightai.com/download
  2. Navigate to the plugins tab and select "Add Custom Plugin"
  3. Configure the plugin with the settings below
    Plugin Name OpenAlex MCP Server
    Command (node, npx, python, etc.)

    Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.

  4. Enable "Start Automatically" if you want the plugin to start when Highlight launches

From the repository

Install via npm install -g openalex-mcp and add the server to your MCP client configuration. Use tools such as search_works, search_authors, search_sources, search_institutions, search_concepts, search_publishers, search_funders, get_entity, autocomplete, and classify_text with parameters like search, filter, sort, page, cursor, group_by, select, sample, and mailto.

Claude Desktop / Cursor

Paste into your MCP client config file to install this server.

{
    "mcpServers": {
        "openalex mcp server": {
            "openalex-mcp-reetp14": {
                "command": "node",
                "args": [
                    "test-simple.js"
                ]
            }
        }
    }
}

McpServers

{
    "openalex-mcp-reetp14": {
        "command": "node",
        "args": [
            "test-simple.js"
        ]
    }
}

OpenAlex MCP Server

A Model Context Protocol (MCP) server that provides access to the OpenAlex API - a fully open catalog of the global research system covering over 240 million scholarly works.

Features

This MCP server provides tools to search and retrieve:

- Works - Scholarly articles, preprints, datasets, books (240M+ items)
- Authors - Researchers and creators with ORCID integration
- Sources - Journals, conferences, repositories (~250K venues)
- Institutions - Universities, hospitals, labs with ROR matching
- Concepts - Hierarchical research topics (levels 0-5)
- Publishers - Publishing organizations
- Funders - Grant-making bodies
- Autocomplete - Type-ahead search across all entity types
- Text Classification - Concept prediction for arbitrary text

Installation

From npm (Recommended)

npm install -g openalex-mcp

From Source

git clone https://github.com/reetp14/openalex-mcp.git
cd openalex-mcp
npm install
npm run build

Usage

As an MCP Server

Add to your MCP client configuration:

{
  "mcpServers": {
    "openalex": {
      "command": "npx",
      "args": ["openalex-mcp"]
    }
  }
}

json

Or if installed locally:

{
  "mcpServers": {
    "openalex": {
      "command": "node",
      "args": ["./node_modules/openalex-mcp/build/index.js"]
    }
  }
}

Available Tools

Entity Search Tools

All search tools support the full OpenAlex query grammar:

- search_works - Search scholarly works
- search_authors - Search researchers and creators
- search_sources - Search journals, conferences, repositories
- search_institutions - Search universities, hospitals, labs
- search_concepts - Search research topics
- search_publishers - Search publishing organizations
- search_funders - Search grant-making bodies

Common Parameters:

- search - Full-text search query
- filter - Boolean filters (e.g., concept.id:C12345,from_publication_date:2022-01-01)
- sort - Sort field with optional :desc (e.g., cited_by_count:desc)
- page/per_page - Standard pagination (max 10,000 results total)
- cursor - Deep pagination (use for first call)
- group_by - Faceting/aggregation by field
- select - Comma-separated fields to return
- sample - Random sample size with optional seed
- mailto - Your email for higher rate limits

Single Entity Retrieval

- get_entity - Get a single entity by OpenAlex ID
- entity_type - One of: works, authors, sources, institutions, concepts, publishers, funders
- openalex_id - OpenAlex ID (e.g., W2741809807, A1969205038)

Utility Tools

- autocomplete - Type-ahead search across entity types

- search - Search query (required)
- type - Entity type to search within (optional)
- per_page - Number of suggestions (max 50)

- classify_text - Predict research concepts from text
- title - Title text to classify
- abstract - Abstract text to classify

Examples

Search for AI papers from 2023

{
  "tool": "search_works",
  "arguments": {
    "search": "artificial intelligence",
    "filter": "from_publication_date:2023-01-01,to_publication_date:2023-12-31",
    "sort": "cited_by_count:desc",
    "per_page": 10,
    "mailto": "researcher@university.edu"
  }
}

Find authors by institution

{
  "tool": "search_authors",
  "arguments": {
    "filter": "last_known_institution.id:I27837315",
    "sort": "works_count:desc",
    "select": "id,display_name,works_count,cited_by_count"
  }
}

Get publication trends by year

{
  "tool": "search_works",
  "arguments": {
    "filter": "concepts.id:C154945302",
    "group_by": "publication_year"
  }
}

Autocomplete journal names

{
  "tool": "autocomplete",
  "arguments": {
    "search": "nature",
    "type": "sources",
    "per_page": 5
  }
}

Classify research text

{
  "tool": "classify_text",
  "arguments": {
    "title": "Deep Learning for Medical Image Analysis",
    "abstract": "We present a novel approach using convolutional neural networks..."
  }
}

Query Grammar Quick Reference

Filters

- Chain with , for AND: concept.id:C12345,publication_year:2023
- Chain with | for OR: type:journal|type:repository
- Negate with !: authors.id!A12345 (exclude author)
- Date ranges: from_publication_date:2020-01-01,to_publication_date:2023-12-31

Sorting

- Ascending: sort=publication_year
- Descending: sort=cited_by_count:desc
- Multiple: sort=publication_year:desc,cited_by_count:desc

Pagination

- Standard: page=2&per_page=100 (max 10,000 results)
- Deep: cursor=
(first call), then use returned next_cursor

Rate Limits

- Anonymous: 10 requests/second, 100,000/day
- With mailto: 100 requests/second, 1,000,000/day

API Response Format

All tools return the standard OpenAlex JSON envelope:

{
  "meta": {
    "count": 249256387,
    "db_response_time_ms": 12,
    "page": 1,
    "per_page": 25,
    "next_cursor": "ZjEwMD..."
  },
  "results": [
    {
      / entity object /
    }
  ]
}

Development

```bash

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