ORCID MCP Server for LlamaIndexGive LlamaIndex instant access to 13 tools to Create Item, Csv Search, Delete Item, and more
GDPR Free for SubscribersLlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add ORCID as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
Ask AI about this MCP Server for LlamaIndex
The ORCID MCP Server for LlamaIndex is a standout in the Knowledge Management category — giving your AI agent 13 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
Geminiimport asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to ORCID. "
"You have 13 tools available."
),
)
response = await agent.run(
"What tools are available in ORCID?"
)
print(response)
asyncio.run(main())
* 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
About 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.
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.
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.
The ORCID MCP Server exposes 13 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
All 13 ORCID tools available for LlamaIndex
When LlamaIndex connects to ORCID through Vinkius, your AI agent gets direct access to every tool listed below — spanning researcher-id, academic-publishing, data-attribution, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.
Create item on ORCID
Requires Member API access and appropriate scopes. Add a new item to a section (Member API only)
Csv search on ORCID
Search the ORCID registry and return CSV format
Delete item on ORCID
Requires Member API access. Delete an item from a section (Member API only)
Expanded search on ORCID
Search the ORCID registry and return expanded metadata
Get activities on ORCID
Get summary of all activities for an ORCID record
Get item on ORCID
Get a specific item from a section using its put-code
Get person on ORCID
Get biographical section of an ORCID record
Get record on ORCID
Get summary view of the full ORCID record
Get section on ORCID
Get summary of a specific section
Get summary on ORCID
Requires Member API access. Get validated and self-asserted summary (Member API only)
Register webhook on ORCID
Requires Premium Member API. Register a webhook callback URL for an ORCID record (Premium only)
Search on ORCID
Supports fields like given-names, family-name, email, orcid, etc. Search the ORCID registry using Solr 3.6 syntax
Update item on ORCID
Requires Member API access. Update an existing item in a section (Member API only)
Connect ORCID to LlamaIndex via MCP
Follow these steps to wire ORCID into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.
Install dependencies
pip install llama-index-tools-mcp llama-index-llms-openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
Why Use LlamaIndex with the ORCID MCP Server
LlamaIndex provides unique advantages when paired with ORCID through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine ORCID tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain ORCID tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query ORCID, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what ORCID tools were called, what data was returned, and how it influenced the final answer
ORCID + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the ORCID MCP Server delivers measurable value.
Hybrid search: combine ORCID real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query ORCID to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying ORCID for fresh data
Analytical workflows: chain ORCID queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for ORCID in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with ORCID immediately.
"Search the ORCID registry for researchers with the family name 'Einstein'."
"Get the biographical details for ORCID iD 0000-0002-1825-0097."
"List all the works associated with ORCID 0000-0002-1825-0097."
Troubleshooting ORCID MCP Server with LlamaIndex
Common issues when connecting ORCID to LlamaIndex through Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpORCID + LlamaIndex FAQ
Common questions about integrating ORCID MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
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