Compatible with every major AI agent and IDE
What is the DataCite REST MCP Server?
Connect to the DataCite REST API to interact with the global infrastructure for research data. This MCP server allows your AI agent to search, retrieve, and manage DOIs and their associated metadata.
What you can do
- DOI Management — Create, update, and delete DOI records (Draft state) with full JSON:API support.
- Metadata Retrieval — Fetch detailed metadata for any DOI, including affiliations and publisher info.
- Search & Discovery — List DOIs with advanced filtering by client, provider, prefix, or resource type.
- Provenance & Events — Track metadata changes through activities and discover citations or usage via events.
- Infrastructure Overview — List repository accounts (clients), providers, and prefixes within the DataCite network.
How it works
- Subscribe to this server
- Enter your DataCite credentials (Username and Password)
- Start managing research identifiers from Claude, Cursor, or any MCP-compatible client
No more manual searching through web portals to find research citations or metadata. Your AI acts as a dedicated research data manager.
Who is this for?
- Researchers & Academics — instantly retrieve metadata and citations for specific datasets or publications
- Data Librarians — manage DOI records and verify metadata provenance directly from their workflow
- Developers — integrate scholarly metadata and DOI registration into automated research pipelines
Built-in capabilities (12)
Requires Member API authentication (Repository account). Payload must follow JSON:API format. Create a new DOI record
Only DOIs in Draft state can be deleted. Requires Member API authentication. Delete a DOI (Draft state only)
Retrieve metadata for a specific DOI
Check API status
Retrieve metadata provenance (history of changes)
List DataCite Repository accounts
Retrieve a list of DOIs
Retrieve links between DOIs and other resources (citations, usage)
List DOI prefixes
List DataCite Members and Consortium Organizations
List usage reports
Requires Member API authentication. Only included attributes will be updated. Update an existing DOI record
Why Google ADK?
Google ADK natively supports DataCite REST as an MCP tool provider. declare Vinkius Edge URL and the framework handles discovery, validation, and execution automatically. Combine 12 tools with Gemini's long-context reasoning for complex multi-tool workflows, with production-ready session management and evaluation built in.
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Google ADK natively supports MCP tool servers. declare a tool provider and the framework handles discovery, validation, and execution
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Built on Gemini models, ADK provides long-context reasoning ideal for complex multi-tool workflows with DataCite REST
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Production-ready features like session management, evaluation, and deployment come built-in. not bolted on
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Seamless integration with Google Cloud services means you can combine DataCite REST tools with BigQuery, Vertex AI, and Cloud Functions
DataCite REST in Google ADK
DataCite REST and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect DataCite REST to Google ADK through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.
Raw MCP | Vinkius | |
|---|---|---|
| Server catalog | Find and host yourself | 4,000+ managed |
| Infrastructure | Self-hosted | Sandboxed V8 isolates |
| Credential handling | Plaintext in config | Vault + runtime injection |
| Data loss prevention | None | Configurable DLP policies |
| Kill switch | None | Global instant shutdown |
| Financial circuit breakers | None | Per-server limits + alerts |
| Audit trail | None | Ed25519 signed logs |
| SIEM log streaming | None | Splunk, Datadog, Webhook |
| Honeytokens | None | Canary alerts on leak |
| Custom domains | Not applicable | DNS challenge verified |
| GDPR compliance | Manual effort | Automated purge + export |
Why teams choose Vinkius for DataCite REST in Google ADK
The DataCite REST MCP Server runs on Vinkius-managed infrastructure inside AWS — a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts. All 12 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in Google ADK only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
How Vinkius secures
DataCite REST for Google ADK
Every tool call from Google ADK to the DataCite REST MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
Can I search for DOIs using specific metadata queries?
Yes! Use the list_dois tool with the query parameter. You can use OpenSearch query string syntax to search through all metadata fields indexed by DataCite.
How do I see the history of changes for a DOI?
You can use the list_activities tool to retrieve metadata provenance, which shows the history of changes and updates made to records in the DataCite system.
Can I delete any DOI record?
No. According to DataCite rules, only DOIs in the 'Draft' state can be deleted using the delete_doi tool. Registered or Findable DOIs cannot be deleted to ensure the persistence of research citations.
How does Google ADK connect to MCP servers?
Import the MCP toolset class and pass the server URL. ADK discovers and registers all tools automatically, making them available to your agent's tool-use loop.
Can ADK agents use multiple MCP servers?
Yes. Declare multiple MCP tool providers in your agent configuration. ADK merges all tool schemas and the agent can call tools from any server in a single turn.
Which Gemini models work best with MCP tools?
Gemini 2.0 Flash and Pro models both support function calling required for MCP tools. Flash is recommended for latency-sensitive use cases, Pro for complex reasoning.
McpToolset not found
Update: pip install --upgrade google-adk
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