data.world MCP for AI Agents. Discover and Govern Enterprise Data Assets Using the Catalog
data.world connects your AI agent directly to an enterprise data catalog, letting you discover and govern organizational data assets through conversation. You can search across all available datasets and projects, retrieve detailed metadata, track project progress, and list saved SQL or SPARQL queries without ever leaving your chat interface.
Give Claude and any AI agent real-world access
Find datasets or projects by searching titles, descriptions, or tags across the whole organization’s assets.
Get specific details for any asset, including field definitions, associated tags, and licensing information.
Generate lists of all data assets or active projects you manage on the platform.
List documented findings, visualizations, or specific SQL/SPARQL query definitions linked to a project or dataset.
Review recent platform activity logs, including updates to datasets or changes in collection membership.
Ask an AI about this
Waiting for input…
What AI agents can do with data.world: 10 Tools for Metadata Management and Data Discovery
Use these tools to search the data catalog, retrieve project details, list datasets you own, and access technical metadata like field definitions and saved queries.
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 data.world MCPGet Dataset Details
Retrieves comprehensive details for one dataset, including its field definitions, tags, and license information.
Get My Profile
Fetches metadata about the currently authenticated user, showing your display name...
Get Project Details
Gets detailed information on a specific project, including its members, objective...
List Recent Activity
Returns a log of recent actions across your data.world account, such as dataset...
List My Collections
Lists all organizational collections you manage, providing their descriptions and...
List Dataset Queries
Generates a list of saved SQL or SPARQL query definitions associated with a specific dataset.
List My Datasets
Provides a catalog listing of all datasets owned by your account, showing visibility and last modification dates.
List Project Insights
Lists documented findings, visualizations, or insights that have been published...
List My Projects
Returns a summary of all data projects you own, including the linked datasets and...
Search Catalog
Searches across the entire data.world platform for relevant datasets or projects...
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.
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 each call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with data.world, then connect any of our 5,200+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 5,200+ others, all in one place
- Add new capabilities to your AI anytime you want
- Connections are secured and governed automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog weekly
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by data.world. 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.
VINKIUS CLOUD
Cloud Hosted
Managed infra
V8 Isolated
Sandboxed per request
Zero-Trust Proxy
No stored credentials
DLP Enforced
Policy on each call
GDPR Compliant
EU data residency
Token Compression
~60% cost reduction
data.world MCP: Solving Data Discovery Pain Points in Metadata Management
Today, finding a single piece of data is a manual nightmare. You open the internal wiki, then check the project dashboard, then log into the asset catalog, searching by vague keywords and hoping you remember which department owns the correct version. This process wastes hours just confirming metadata.
With this MCP, your agent handles that entire sequence. You simply ask, 'What is the most current dataset for Q3 revenue?' The agent uses the `search_catalog` tool to query across all available sources and provides a ranked list of options instantly, letting you proceed with confidence.
data.world MCP: Improving Data Governance in Collaborative Platforms
Manual governance is reactive. You only realize data is missing or outdated when a report breaks. Tracking ownership, monitoring changes, and validating permissions requires constant manual checks across multiple dashboards.
This MCP shifts you to being proactive. You can ask the agent to run `list_recent_activity` or check project membership via `get_project_details`. This gives you an immediate, conversational view of who's involved and what has changed, turning governance from a chore into part of your daily workflow.
What data.world MCP for AI Agents MCP does for your AI
Need to find a dataset but don't know where it lives? This MCP connects your AI agent straight into data.world, the enterprise catalog platform. You stop clicking through dozens of dashboards just to check if that metric exists. Instead, you ask your agent directly: 'What datasets track global emissions?' The agent searches the entire index for relevant assets and projects across your organization’s data landscape.
It's more than just searching; it lets you manage governance too. You can review project status, list who owns an asset, or check historical activity logs to see when a dataset was last updated. When working with Vinkius, connecting this MCP gives your agent instant access to the full data catalog, making data discovery part of the conversation itself.
It means you spend zero time on manual metadata gathering and all your time analyzing what the data actually says.
019d7582-8029-733d-b83b-f2998aa0d5ff How to set up data.world MCP for AI Agents MCP
The bottom line is that your AI client uses this MCP to treat data discovery and governance tasks as simple conversations, not multi-step UI workflows.
Connect the data.world MCP to your AI client and authorize it using your API token.
Tell your agent what you need—for example, 'Show me all datasets related to Q3 sales' or 'What is the status of Project Phoenix?'
The agent executes the necessary lookup tools, returning structured metadata like field definitions, project members, and asset lists directly in the chat.
Who uses data.world MCP for AI Agents MCP
This tool is for anyone drowning in metadata. If you spend time clicking between spreadsheets, project dashboards, and the asset catalog just to confirm who owns a column or if that data exists, this MCP saves your day. It's built for people whose job requires knowing where the right data lives.
You use it constantly to quickly find datasets and retrieve query definitions needed for a new analysis, saving hours of searching.
You monitor project status and audit data assets via chat commands, ensuring compliance and tracking ownership without manual dashboard checks.
You explore organizational collections and documented insights during the initial stages of a new data planning effort.
Benefits of connecting data.world MCP for AI Agents MCP
Instead of digging through UIs, you can use the search_catalog tool to instantly find data assets by title or tag. Your agent handles the index search so you don't.
The MCP lets your agent get detailed metadata using get_dataset_details. You immediately see field definitions and licensing info without navigating to a separate asset page.
Need to know project status? Calling list_project_insights means your AI client pulls all documented findings right into the chat, keeping your context clear.
You can track governance history by running list_recent_activity. This gives you an immediate audit trail of who changed what and when.
The agent supports structured queries. You don't just get a list; using list_dataset_queries provides the actual SQL or SPARQL code definitions, ready for review.
data.world MCP for AI Agents MCP use cases
Figuring out who owns that weird dataset
A data steward needs to audit an asset. Instead of guessing which department owns it, they ask their agent to run get_project_details or check the resource owners via the API call for project information.
Comparing multiple datasets across projects
A data scientist wants to see if 'Sales' data is tracked in three different places. They ask their agent to use search_catalog and then run list_my_datasets to compare the metadata of all available versions.
Building a report based on old findings
A knowledge manager needs to understand historical data patterns. They prompt their agent to use list_project_insights for a specific project, instantly surfacing documented findings from previous teams.
data.world MCP for AI Agents MCP tradeoffs
What to watch out for, and the recommended way to handle each one.
Trying to copy/paste metadata manually
A user opens the dataset dashboard, copies the license type, then has to open a separate project page and paste it into an email. It's slow and error-prone.
Use your agent to call get_dataset_details within this MCP. The agent retrieves all necessary fields, licenses, tags, and definitions in one step, letting you copy the final output directly.
Only searching by keywords
The user types 'sales' but misses that the relevant dataset is tagged as 'revenue metrics'. The search fails because it was too vague.
Use search_catalog with specific criteria. Your agent lets you combine natural language intent ('all sales data') with structured filters (by tag or owner) to ensure precision.
Confusing project scope with dataset scope
The user sees a list of datasets and assumes they are all connected, but forgets that the project needs specific inputs. They don't know what resources are required.
Use get_project_details to see exactly which datasets are linked to a project. This confirms the boundaries and dependencies before you start building.
When to use data.world MCP for AI Agents MCP
Use this MCP if your workflow relies on knowing where data lives, who owns it, or what its specific definitions are. If you need an agent to confirm compliance details (license type, tags) or track the lineage of a metric across multiple projects, this is essential. Don't use it if all you need is simple text generation based on external knowledge; then your AI client’s native capabilities suffice. You should also look at dedicated data visualization tools for actual graphing, but this MCP is perfect for the metadata work—for listing datasets (list_my_datasets), checking project scope (get_project_details), or retrieving code definitions (list_dataset_queries).
Frequently asked questions about data.world MCP for AI Agents MCP
How does the data.world MCP help me find specific datasets? +
The data.world MCP allows your agent to search across all assets using full-text search, letting you pinpoint exactly which dataset exists without knowing its exact location or owner. It’s like having a map of every piece of data in the company.
Can I use this MCP to check project status and ownership? +
Yes. The agent can run tools to get detailed information on any specific project, showing who is a member, what the objective is, and which resources are linked. This saves you from having to open multiple dashboards.
Is this data.world MCP good for data governance? +
It's excellent for governance because it lets your agent list recent activity logs, showing who modified an asset or project and when. You get a clear audit trail without doing manual checks.
What if I need to see the code used in saved queries? +
The MCP can list all saved SQL or SPARQL query definitions for any dataset you specify. It retrieves the actual language and metadata, so you know exactly how the data is being processed.
Do I need to be a data scientist to use data.world with this MCP? +
No. While it's powerful for analysts, any role that needs to find or manage corporate information can benefit. It simplifies the process of discovery and validation regardless of your job title.