PubTator MCP Server

The PubTator MCP Server bridges the gap between AI assistants and the rich, curated biomedical literature available through PubTator 3. By exposing PubTator’s annotation and relationship mining capabilities via the Model Context Protocol, developers can give their models instant access to high‑quality entity annotations, standard identifiers, and curated relationships without needing to build their own parsing pipelines. This is especially valuable for researchers, clinicians, and bioinformatics tools that rely on up‑to‑date literature insights to drive hypothesis generation or clinical decision support.

At its core, the server offers a set of declarative actions that translate natural‑language queries into structured requests. A user can ask an AI to “search for papers on BRCA1 interactions” or “retrieve the Gene Ontology ID for TP53”, and the server will query PubTator, return annotations in JSON or other user‑chosen formats, and even surface the inferred relationships between entities. This reduces latency compared to scraping or manual curation, ensures consistency across queries, and provides a single, reliable endpoint for all literature‑based tasks.

Key capabilities include:

• Literature Annotation Export – Pull full PubTator annotation sets in multiple formats (JSON, TSV, etc.), enabling downstream analytics or visualization.
• Entity ID Lookup – Convert free‑text mentions into standardized identifiers (HGNC, UniProt, MeSH), which is essential for cross‑reference and integration with other databases.
• Relationship Mining – Discover co‑occurrence or curated relationships between genes, diseases, chemicals, and more, supporting network analysis and pathway construction.
• Literature Search – Retrieve papers by keyword or entity ID, returning metadata and annotations in a single response.
• Batch Processing – Export annotations for large query results, facilitating high‑throughput literature reviews or cohort studies.

In practice, the server is ideal for building AI‑driven literature review assistants, clinical decision support systems that pull evidence from recent studies, or bioinformatics pipelines that need to annotate gene‑disease associations on the fly. Because it conforms to MCP, any client that understands the protocol—Claude, Cursor, Windsurf, or custom tools—can integrate PubTator’s data with minimal effort. The server’s lazy initialization and graceful shutdown handling make it robust for production deployments, while Docker support allows rapid scaling in cloud or on‑prem environments.

Overall, the PubTator MCP Server provides a unified, programmatic interface to one of the most comprehensive biomedical annotation resources, empowering developers to embed literature intelligence directly into AI workflows and accelerate discovery.