DataCite MCP Server for Claude

The DataCite MCP server bridges AI assistants and the vast research metadata ecosystem maintained by DataCite. By exposing a GraphQL interface through the Model Context Protocol, it lets Claude and other AI clients query for DOIs, datasets, publications, software packages, and the intricate relationships between authors, funders, institutions, and research outputs. This capability is essential for developers who need to surface up‑to‑date scholarly information within conversational agents, automated literature reviews, or research discovery tools.

Developers benefit from a single, cloud‑hosted endpoint that abstracts away the complexity of authentication, rate limiting, and API pagination. The server runs on Cloudflare Workers, ensuring low latency and global availability while automatically scaling with demand. It also enforces MCP transport security by validating the header, giving teams control over which clients can access the service. Because it speaks GraphQL, callers can request exactly the fields they need, reducing payload size and network cost—a critical advantage when building responsive AI workflows.

Key features include:

• Rich metadata retrieval: Access detailed descriptors for works, datasets, and software, including titles, creators, publication dates, and licensing information.
• Relationship exploration: Query connections such as author affiliations, funding sources, citation links, and institutional collaborations.
• Search by criteria: Filter results by topic, keyword, publication year, or funding agency, enabling targeted data discovery.
• Cloudflare Workers deployment: Reliable hosting with built‑in edge caching and automatic scaling, simplifying operational overhead.
• Secure origin validation: Protect the API by allowing only trusted origins or specifying custom allowed lists.

Typical use cases span academia, research administration, and data science. For instance, a research assistant could ask Claude to “find recent datasets about climate change” and receive a curated list of DOIs along with access details. A grant office might query for “publications funded by the European Research Council” to track impact metrics. In data curation pipelines, developers can programmatically harvest metadata for new datasets and ingest them into internal catalogues. By integrating this MCP server into AI‑driven workflows, teams can automate literature scanning, compliance reporting, and scholarly analytics without writing bespoke API clients.