ROR API (Research Organization Registry) MCP for AI. Standardize academic data with global identifiers.

Q: How do I check if the ROR API is working with getheartbeat?

Call getheartbeat. If it responds with 'OK', the service is operational. This quick check confirms connectivity before you run any complex queries, saving time and preventing failed runs.

Q: If I have an ROR ID, which tool should I use?

Use getorganization. It's designed specifically to take a known identifier (like the full ROR ID) and retrieve the complete, detailed record for that single institution.

Claude

ChatGPT

Cursor

Gemini

Windsurf

VS Code

JetBrains

Vercel

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

Connect to your AI in seconds.

ROR API (Research Organization Registry) connects your AI agent to a global database of over 100,000 research institutions. It lets you search for specific academic entities using keyword filters or advanced syntax.

You can retrieve complete metadata—including official ROR IDs and external identifiers like GRID—for data cleaning and scholarly record verification.

What your AI can do

Get organization

Fetches a single, detailed record for an organization using its full URL, domain name, or ROR ID.

Get heartbeat

Checks the API status to confirm if the Research Organization Registry is currently operational.

List organizations

Searches and retrieves a list of organizations by applying general queries, advanced filters, or affiliation strings.

Check API operational status

Runs the get_heartbeat tool to confirm if the ROR service is currently available.

Retrieve single organization details

Uses get_organization to fetch a complete record for one institution, given its ID, full URL, or domain name.

Search and list multiple organizations

Runs list_organizations by applying specific queries, advanced filters, or affiliation strings to find groups of institutions.

Ask an AI about this

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AI Agent

ROR API: 3 Tools for Academic Data Management

Use these three tools to search, verify, and pull detailed records from the Research Organization Registry (ROR) for scholarly data cleanup.

Make your AI actually useful.

Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.

Start using ROR API (Research Organization Registry) on Vinkius

Get Organization

Fetches a single, detailed record for an organization using its full URL, domain name, or ROR ID.

Get Heartbeat

Checks the API status to confirm if the Research Organization Registry is currently...

List Organizations

Searches and retrieves a list of organizations by applying general queries, advanced...

Security and governance baked right in.

Pick your AI client below to get set up. Just create a Vinkius account, subscribe, and you're instantly up and running. We handle the entire backend infrastructure, delivering out-of-the-box support for HTTPS Streamable, SSE, and OAuth2—zero messy routing required.

Claude AI

Open Claude Settings

Go to claude.ai, click your profile icon, then navigate to Customize → Connectors.

Add Custom Connector

Click the "+" button and select Add custom connector. Paste your Vinkius endpoint URL:

https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp

Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. For OAuth-protected servers, expand Advanced settings to add credentials.

Start a conversation

Open a new chat. The ROR API (Research Organization Registry) integration is available immediately — no restart needed.

Antigravity

Configure Agent Environment

Open your Antigravity agent's workspace configuration or mcp-servers.json file.

Bind the Endpoint

Add the Vinkius endpoint URL to your agent's MCP connections list:

"mcp_servers": {
  "ror-api-research-organization-registry": {
    "serverUrl": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
  }
}

Provide your secure token in place of [YOUR_TOKEN_HERE] to ensure your agent requests are authenticated.

Execute

Start your Antigravity session. The agent will autonomously discover and utilize the ROR API (Research Organization Registry) tools with full Vinkius guardrails applied.

VS Code Copilot

⚡

One-Click Install (Recommended)

In your Vinkius Dashboard, simply click the Add to VS Code button for this server. We'll automatically configure your local workspace.

Or configure manually

Open MCP Settings

Open VS Code, press Ctrl/Cmd + Shift + P, and search for GitHub Copilot: MCP Servers.

Add Server Config

Add the Vinkius endpoint configuration to your mcp-servers.json file:

"ror-api-research-organization-registry": {
  "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
}

Ensure you replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.

LangChain

Install Dependencies

Install the LangChain MCP adapters for your environment:

pip install langchain-mcp-adapters

Connect the Server

Use the SSEClient in LangChain to connect to the Vinkius managed endpoint:

from langchain_mcp_adapters.client import SSEClient

# Connect to Vinkius
client = SSEClient(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
tools = client.get_tools()

CrewAI

Define the Tool

Load the Vinkius MCP tools into your CrewAI agents:

from crewai import Agent
from mcp_crewai import MCPTool

# Connect securely to Vinkius
vinkius_tools = MCPTool(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

# Assign to Agent
researcher = Agent(
    role='Data Researcher',
    tools=vinkius_tools.get_all()
)

Execute Task

Run your CrewAI process. The agent will autonomously route tasks to the Vinkius managed server.

Choose How to Get Started

Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.

Build Your Own

Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.

Import from OpenAPI, Swagger, or YAML specs
Create Agent Skills with progressive disclosure
Deploy to edge with MCPFusion framework
Built in DLP, auth, and compliance on every call
Real time usage dashboard and cost metering
Publish to catalog or keep private

Start building

Make Your AI Do More

Start with ROR API (Research Organization Registry), then connect any of our 5,100+ other servers whenever your AI needs more. One click, no limits.

Use this MCP plus 5,100+ others, all in one place
Add new capabilities to your AI anytime you want
Every connection is secured and compliant automatically
Track usage and costs across all your servers
Works with Claude, ChatGPT, Cursor, and more
New servers added to the catalog every week

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by ROR API. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Works with Claude, ChatGPT, Cursor, and more

The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.

This connection provides 3 powerful capabilities that interface natively with Claude, ChatGPT, Cursor, and other compatible AI platforms. No middleware. No custom integration required.

Cleaning up citation data shouldn't feel like forensic accounting.

Right now, if you're managing academic databases, the process is a nightmare. You find a research paper, and suddenly you have a list of affiliations: 'University of Texas at Austin,' 'UT-Austin Dept of Science,' or sometimes just 'TX U.' You spend hours copy-pasting these variations into an Excel sheet, trying to determine which names map to the same single, authoritative entity.

With this ROR API MCP Server, your agent handles that mess instantly. Instead of manual comparison, you prompt it with a batch of messy strings. The server runs `list_organizations` and returns clean data—the official name and the verified ROR ID—so you can feed directly into your database without any cleanup.

The ROR API (Research Organization Registry) MCP Server: Get standardized IDs.

You no longer have to build complex, fragile mapping tables that break every time an institution changes its name or structure. You simply ask the agent to resolve a string of text against the global ROR registry using `list_organizations`.

It’s immediate and definitive. The data you get back is not just 'a guess'; it's traceable metadata from a major, community-vetted source.

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What your AI can actually do with this

You're hooking your AI agent up to the Research Organization Registry (ROR) API. This isn't just some general database; it connects you directly to a global pool of over 100,000 records for academic institutions. When you pull this server into your workspace, you get immediate access to verified metadata. You don't have to guess if an institution exists or what its official ID is.

It’s essential for cleaning up messy scholarly data.

Checking API Status with get_heartbeat

Before you run any complex query, you gotta check the pipes first. Running get_heartbeat confirms whether the entire ROR service is actually running right now. This tool gives you a simple confirmation that the Research Organization Registry connection is live and operational, so your agent doesn't waste time hitting dead ends.

Finding Specific Institutions with get_organization

You need details on one specific place? Use get_organization. You feed it an identifier—that can be the institution’s full URL, its domain name, or even a known ROR ID. This tool doesn't give you general info; it pulls the complete metadata record for that single entity. When you run this, your agent gets everything: the official ROR ID, external identifiers like GRID and ISNI, location data, and all the associated details needed to confirm an institution’s existence and structure.

Searching and Listing Multiple Institutions with list_organizations

When you're dealing with a bunch of records—say, cleaning up a bibliography that lists twenty different affiliations—you run list_organizations. This tool is your discovery engine. You can search for groups of institutions by applying general keyword queries or advanced filters. These filters let you narrow down the results far beyond simple text matching; they let you use complex syntax to pinpoint exactly what you need.

If you're working with affiliation strings that are a mess, this tool handles it too. You can pass in specific affiliation strings so your agent finds groups of related academic bodies across different domains. It manages the search by applying general queries and advanced filters simultaneously, giving you a comprehensive list of candidates to verify.

When combining these functions, your AI client uses list_organizations to narrow down potential matches based on complex criteria, then it can use get_organization on the resulting IDs or domains to pull the final, verified metadata for each one. It's how you turn sloppy reference data into clean, actionable records.

What You Can Actually Do:

You run get_heartbeat to confirm the API is up and running before anything else.
If you know an institution's exact domain or ID, use get_organization for a definitive data pull.
To find groups of institutions, feed specific queries, advanced filters (like Elasticsearch syntax), or messy affiliation strings into list_organizations. This process allows your agent to identify potential entities across huge datasets. It helps you resolve those unstructured affiliations found in papers and map them to official ROR identifiers.

Built · Hosted · Managed by Vinkius ROR API MCP Server - Research Organization Metadata Lookup

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Here's how it actually works

The bottom line is, your AI client runs these tools against a massive global registry so you don't have to manually cross-reference academic databases.

First, subscribe to the ROR API server. You can optionally input your ROR Client ID for tracking.

Next, prompt your AI client with a request (e.g., 'Find all universities in Texas'). The agent determines it needs list_organizations and executes the query.

Finally, the server returns structured JSON containing lists of institutions or detailed records that you can use to clean up data.

What Changes When You Connect

Stop dealing with vague institutional names. The list_organizations tool lets you search by keyword or use advanced filters to find the exact research entities you need, narrowing thousands of possibilities down to a precise list.

Instantly get full metadata for any institution using get_organization. You don't just get a name; you get official ROR IDs and external identifiers like GRID: grid.5335.0—data essential for data integrity.

It handles the hardest part of academic research data: messy affiliations. Use these tools to resolve unstructured strings from papers into clean, verifiable global standards.

Before running big queries, check in with get_heartbeat. This simple call confirms the API is up and ready to go, preventing failed runs and wasted time on a downed service.

Build better research systems. By automating metadata retrieval via this MCP server, you eliminate manual cross-referencing against multiple academic databases.

See it in action

01 01

Cleaning citation lists from old papers

A librarian receives a grant proposal with dozens of manually typed affiliations. Instead of correcting them one by one, they prompt their agent: 'Clean this list.' The agent uses list_organizations to find all entities and then get_organization to fetch the official ROR ID for each, giving you a clean dataset in minutes.

02 02

Verifying institutional relationships

A policy analyst needs to see if two collaborating institutions are parent/child organizations. They use list_organizations, filtering by location and type, which returns a list that they can then process with get_organization to confirm their official relationship structure.

03 03

Building a new research portal database

A developer needs metadata for every university in a specific state. They run a targeted search using list_organizations with advanced filters (e.g., location codes). The resulting list allows them to systematically pull all necessary identifiers and domain names.

04 04

Quickly checking system uptime

A data scientist starts their morning workflow and needs to make sure the ROR source is stable before running complex queries. They run a quick get_heartbeat check first. If it returns 'OK', they know they can trust the subsequent, more resource-intensive calls.

The honest tradeoffs

Using general search engines for IDs

Anti-pattern

A user searches Google for 'University of Cambridge ROR ID' and gets a mix of links—some are old, some are wrong. They waste time verifying the data manually.

The Fix

Use get_organization directly with the institution's known URL or domain name. This forces the query through the official registry, guaranteeing you get the most current ROR record.

Running a massive list without filters

Anti-pattern

A user calls list_organizations without any parameters and gets a huge dump of irrelevant data, causing rate limits or making it impossible to find what they need.

The Fix

Always start with a targeted query. Use list_organizations with specific criteria—like filtering by location code or type—to limit the result set right away.

Assuming data freshness

Anti-pattern

A user runs an old dataset through the API and assumes that because it worked last month, the data is still current. Institutional data changes often.

The Fix

Always validate against a source of truth. Use get_heartbeat to confirm service health, but remember that while the tool confirms connectivity, you must treat the retrieved metadata as accurate only up to ROR's last update.

When It Fits, When It Doesn't

Use this server if your core data problem involves institutional identity or academic affiliation. You need to map messy, human-generated text (like a citation) into standardized identifiers recognized by global research bodies—that’s the job of ROR.

Don't use it if you just need general contact information or local business details. If you are looking for 'The best plumber in town,' this server won't help; you need a Yelp-style service. The data here is strictly limited to academic and research bodies, which is great—and necessary.

When designing your workflow, think of it as a three-step process: 1) Check get_heartbeat for availability. 2) Use list_organizations to narrow the scope (search). 3) Use get_organization on the results to get the final details.

Questions you might have

How do I check if the ROR API is working with `get_heartbeat`? +

Call get_heartbeat. If it responds with 'OK', the service is operational. This quick check confirms connectivity before you run any complex queries, saving time and preventing failed runs.

What kind of filters can I use in `list_organizations`? +

You can search using keywords, advanced Elasticsearch syntax, or by specific affiliation strings. This lets you narrow down the 100k+ records to a manageable list based on location or type.

If I have an ROR ID, which tool should I use? +

Use get_organization. It's designed specifically to take a known identifier (like the full ROR ID) and retrieve the complete, detailed record for that single institution.

Does this help me match messy names? Using `list_organizations`? +

Yes. The tools are built to resolve unstructured affiliation strings from research papers into official ROR identifiers, which is exactly what you need for data cleaning.

When I run `list_organizations`, do I need a specific API key for my AI client? +

You can optionally supply your ROR Client ID. This helps track the traffic associated with your queries, which is important if you are running high volumes of searches or collaborating on multiple projects.

How flexible is `get_organization` if I don't have the exact ROR ID? +

The tool is highly flexible. You can pass a full URL, just the domain combined with an ID, or simply use the raw ROR identifier. This makes fetching records much more robust than relying on one single input type.

When I use `get_organization`, what specific metadata fields can I expect to receive? +

It retrieves a full record set for the organization, including its ROR ID, location data, website domain, and external identifiers like GRID and ISNI. You get everything needed for comprehensive academic mapping.

For large datasets, how efficient is searching using `list_organizations`? +

The tool supports advanced Elasticsearch syntax along with keyword searches. This mechanism lets you narrow down results quickly and efficiently across tens of thousands of records.

How can I find a ROR ID for a specific university name? +

Use the list_organizations tool with the query parameter. For example, searching for 'University of Cambridge' will return the matching record and its unique ROR ID.

Can I retrieve external identifiers like GRID or ISNI for an organization? +

Yes! When you use get_organization with a ROR ID, the response includes a crosswalk to other identifiers like GRID, ISNI, Crossref Funder ID, and Wikidata.

Is there a way to check if the ROR service is currently available? +

You can use the get_heartbeat tool. It performs a simple check and returns an 'OK' status if the ROR API is operational.

Connect to your AI in seconds.

Get organization

Get heartbeat

List organizations

ROR API: 3 Tools for Academic Data Management

Make your AI actually useful.

Get Organization

Get Heartbeat

List Organizations

Security and governance baked right in.

Claude AI

Open Claude Settings

Add Custom Connector

Start a conversation

Claude Code

Open your terminal

Add the MCP Server

Start coding

Cursor

One-Click Install (Recommended)

Open Cursor Settings

Add New Server

Use in Composer

Antigravity

Configure Agent Environment

Bind the Endpoint

Execute

VS Code Copilot

One-Click Install (Recommended)

Open MCP Settings

Add Server Config

Windsurf

One-Click Install (Recommended)

Open Windsurf Settings

Add Server Endpoint

LangChain

Install Dependencies

Connect the Server

CrewAI

Define the Tool

Execute Task

Choose How to Get Started

Build Your Own

Make Your AI Do More

Works with Claude, ChatGPT, Cursor, and more

Cleaning up citation data shouldn't feel like forensic accounting.

The ROR API (Research Organization Registry) MCP Server: Get standardized IDs.

What your AI can actually do with this

Here's how it actually works

Who is this actually for?

What Changes When You Connect

See it in action

Cleaning citation lists from old papers

Verifying institutional relationships

Building a new research portal database

Quickly checking system uptime

The honest tradeoffs

Using general search engines for IDs

Running a massive list without filters

Assuming data freshness

When It Fits, When It Doesn't

Questions you might have