Compatible with every major AI agent and IDE
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 LlamaIndex?
LlamaIndex agents combine ORCID tool responses with indexed documents for comprehensive, grounded answers. Connect 13 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.
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Data-first architecture: LlamaIndex agents combine ORCID tool responses with indexed documents for comprehensive, grounded answers
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Query pipeline framework lets you chain ORCID tool calls with transformations, filters, and re-rankers in a typed pipeline
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Multi-source reasoning: agents can query ORCID, a vector store, and a SQL database in a single turn and synthesize results
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Observability integrations show exactly what ORCID tools were called, what data was returned, and how it influenced the final answer
ORCID in LlamaIndex
ORCID and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect ORCID to LlamaIndex 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 LlamaIndex
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 LlamaIndex 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 LlamaIndex
Every tool call from LlamaIndex 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 LlamaIndex connect to MCP servers?
Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.
Can I combine MCP tools with vector stores?
Yes. LlamaIndex agents can query ORCID tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.
Does LlamaIndex support async MCP calls?
Yes. LlamaIndex's async agent framework supports concurrent MCP tool calls for high-throughput data processing pipelines.
BasicMCPClient not found
Install: pip install llama-index-tools-mcp
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