Bring Researcher Id
to Pydantic AI
Learn how to connect ORCID to Pydantic AI and start using 13 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
GDPR Free for SubscribersCompatible with every major AI agent and IDE
Gemini
What is the ORCID MCP Server?
Connect to the ORCID (Open Researcher and Contributor ID) registry to identify and connect researchers with their professional activities across disciplines and borders.
What you can do
- Record Retrieval — Fetch full summary views or specific biographical sections of any researcher using their 16-digit ORCID iD.
- Activity Tracking — Query summaries of all activities including works, funding, and institutional affiliations.
- Registry Search — Search the global ORCID database using Solr syntax to find researchers by name, email, or keywords.
- Item Management — Deep dive into specific works or funding items using unique put-codes to retrieve full metadata.
- Member API Features — For authorized users, create, update, or delete items within sections to keep researcher profiles synchronized.
How it works
- Subscribe to this server
- Enter your ORCID Access Token (Public or Member API)
- Start querying academic records from Claude, Cursor, or any MCP-compatible client
Who is this for?
- Academic Researchers — quickly verify profile data and manage your own publication list without manual entry
- University Administrators — automate the retrieval of faculty activities and affiliations for reporting
- Data Scientists — search and analyze researcher metadata for bibliometric studies and mapping scientific networks
Built-in capabilities (13)
Requires Member API access and appropriate scopes. Add a new item to a section (Member API only)
Search the ORCID registry and return CSV format
Requires Member API access. Delete an item from a section (Member API only)
Search the ORCID registry and return expanded metadata
Get summary of all activities for an ORCID record
Get a specific item from a section using its put-code
Get biographical section of an ORCID record
Get summary view of the full ORCID record
Get summary of a specific section
Requires Member API access. Get validated and self-asserted summary (Member API only)
Requires Premium Member API. Register a webhook callback URL for an ORCID record (Premium only)
Supports fields like given-names, family-name, email, orcid, etc. Search the ORCID registry using Solr 3.6 syntax
Requires Member API access. Update an existing item in a section (Member API only)
Why Pydantic AI?
Pydantic AI validates every ORCID tool response against typed schemas, catching data inconsistencies at build time. Connect 13 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.
- —
Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application
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Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your ORCID integration code
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Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
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Dependency injection system cleanly separates your ORCID connection logic from agent behavior for testable, maintainable code
ORCID in Pydantic AI
ORCID and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect ORCID to Pydantic AI 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 ORCID in Pydantic AI
The ORCID 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 13 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in Pydantic AI 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
ORCID for Pydantic AI
Every tool call from Pydantic AI to the ORCID 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 researchers by their name or email address?
Yes! Use the search tool with Solr syntax (e.g., family-name:Smith or email:user@example.com) to find matching records in the ORCID registry.
How do I retrieve the full details of a specific publication?
First, use get_section with the section 'works' to find the item's put_code. Then, use the get_item tool with that code to fetch the complete metadata for that specific work.
Do I need a Member API account to add or update records?
Yes. While reading public data works with the Public API, tools like create_item, update_item, and delete_item require Member API access and the useMemberApi configuration set to true.
How does Pydantic AI discover MCP tools?
Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.
Does Pydantic AI validate MCP tool responses?
Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.
Can I switch LLM providers without changing MCP code?
Absolutely. Pydantic AI abstracts the model layer. your ORCID MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.
MCPServerHTTP not found
Update: pip install --upgrade pydantic-ai
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