DOI Citation Verifier MCP Server

A Model Context Protocol (MCP) server that prevents citation hallucination by verifying academic citations against 9 authoritative databases. This server enables AI assistants to verify every citation against real publications before citing them.

The Problem This Solves

Large language models sometimes "hallucinate" academic citations - citing papers that don't exist, misattributing real titles to wrong authors, or mixing up publication details. This MCP server eliminates that problem by:

1. 9-database verification: Checks citations across CrossRef, OpenAlex, PubMed, zbMATH, ERIC, HAL, INSPIRE-HEP, Semantic Scholar, and DBLP

2. Parallel search: Queries all databases simultaneously for fast results (~1 second)

3. Comprehensive coverage: 600+ million publications across all disciplines including STEM, humanities, social sciences, and education

4. DOI-backed citations: Every verified citation includes a valid, clickable DOI

Features

• 9 Database Search: CrossRef, OpenAlex, PubMed, zbMATH, ERIC, HAL, INSPIRE-HEP, Semantic Scholar, DBLP

• Verify Citations: Check if a paper with specific details actually exists across all databases

• Find Verified Papers: Search for real papers on a topic and get only verified citations

• Parallel Processing: All database queries run simultaneously for maximum speed

• Performance Optimized: Smart caching and early exit strategies for 25-35% faster verification

• Source Selection: Search all databases or target specific sources

• Citation Formatting: Returns properly formatted citations with DOIs

• Zero Configuration: All databases work out-of-the-box with no API keys required

How It Works

When an AI assistant is asked about research or for citations:

1. Without this MCP: The assistant might cite "According to Smith et al. (2023) in Nature..." referencing a paper that doesn't exist

2. With this MCP: The assistant uses verifyCitation first, which searches across 9 databases in parallel and returns:

   • Verified match with full DOI → Can be cited

   • No match found → Cannot cite; must search for real papers instead

Tools

verifyCitation

Primary anti-hallucination tool - Verifies a citation exists across multiple databases before it can be mentioned.

Input:

• title (string, optional): Paper title (partial matches accepted)

• authors (array, optional): Author names (last names sufficient)

• year (number, optional): Publication year

• doi (string, optional): DOI if known

• journal (string, optional): Journal name

Returns JSON with:

• verified: true/false

• If verified=true: DOI, title, authors, year, journal, URL, source database

• If verified=false: Warning message that no matching publication was found

• Match quality indicators for transparency

Example successful verification:

findVerifiedPapers

Search for real papers on a topic and return only verified citations with DOIs from multiple databases.

Input:

• query (string): Search query (topic, keywords, author names)

• source (string, optional): Which database to search - "all" (default), "crossref", "openalex", "pubmed", "zbmath", "eric", "hal", "inspirehep", "semanticscholar", or "dblp"

• limit (number, optional): Number of results per source (1-20, default: 5)

• yearFrom (number, optional): Minimum publication year

• yearTo (number, optional): Maximum publication year

Returns: Array of verified papers from the specified database(s) with complete citation information including source

Example:

Installation

Installing via Smithery

To install DOI Citation Verifier automatically via Smithery:

Manual Installation

1. Clone the repository

2. Install dependencies: npm install

3. Build the project: npm run build

4. Add to your MCP client configuration

Development

Example Usage

Before this MCP (citation hallucination):

After this MCP (verified citations only):

Verification catches fake citations:

Database Coverage

All databases are queried in parallel for maximum speed (~1 second total):

General Databases

• CrossRef: 150+ million scholarly publications across all disciplines

• OpenAlex: 250+ million scholarly works across all disciplines

• Semantic Scholar: 200+ million papers with AI-powered search

Specialized Databases

• PubMed: 35+ million biomedical and life sciences publications

• zbMATH: 4+ million mathematics publications

• DBLP: Comprehensive computer science bibliography (journals and conferences)

• ERIC: 1.7+ million education research publications

• HAL: 4.4+ million French/European scholarly documents (2.5M English)

• INSPIRE-HEP: 1.7+ million high-energy physics publications

Total Coverage

600+ million publications across all academic disciplines with specialized depth in STEM, computer science, biomedical sciences, mathematics, and education research.

License

MIT

Contributing

Contributions are welcome! Please feel free to submit issues or pull requests.

Related

API Documentation

• CrossRef API

• OpenAlex API

• PubMed API

• zbMATH API

• ERIC API

• HAL API

• INSPIRE-HEP API

• Semantic Scholar API

• DBLP API

Resources

• DOI Handbook

• Model Context Protocol