data.world MCP Server for LlamaIndex 10 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add data.world as an MCP tool provider through the Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
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Vinkius supports streamable HTTP and SSE.
import 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 data.world. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in data.world?"
)
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 data.world MCP Server
Integrate data.world, the enterprise data catalog and collaborative data platform, directly into your AI workflow. Discover datasets, monitor data projects, and explore saved queries and insights using natural language.
LlamaIndex agents combine data.world tool responses with indexed documents for comprehensive, grounded answers. Connect 10 tools through the 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
- Data Discovery — Search the entire data.world catalog for relevant datasets and projects.
- Asset Management — List and retrieve detailed information for datasets and projects you own or manage.
- Collection Oversight — Explore curated collections of data assets within your organization.
- Query & Insight Access — List saved SQL/SPARQL queries and published insights for your data projects.
The data.world MCP Server exposes 10 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect data.world to LlamaIndex via MCP
Follow these steps to integrate the data.world MCP Server with LlamaIndex.
Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 10 tools from data.world
Why Use LlamaIndex with the data.world MCP Server
LlamaIndex provides unique advantages when paired with data.world through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine data.world tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain data.world tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query data.world, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what data.world tools were called, what data was returned, and how it influenced the final answer
data.world + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the data.world MCP Server delivers measurable value.
Hybrid search: combine data.world real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query data.world 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 data.world for fresh data
Analytical workflows: chain data.world queries with LlamaIndex's data connectors to build multi-source analytical reports
data.world MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect data.world to LlamaIndex via MCP:
get_dataset_details
Includes field definitions, file listings, tags, and license information. Get detailed information for a specific dataset
get_my_profile
world. Returns profile attributes including username, display name, and account-level permissions. Retrieve metadata for the current authenticated user
get_project_details
Resolves project members, associated objective, and the current status of linked resources. Get detailed information for a specific project
list_dataset_queries
Returns a list of saved query definitions, including their language (SQL/SPARQL) and creator metadata. List all saved SQL or SPARQL queries for a dataset
list_my_collections
Returns collection identifiers, descriptions, and item counts. List all collections you own or manage
list_my_datasets
world catalog for datasets owned by the authenticated user. Returns a list of dataset metadata including title, visibility (public/private), and timestamp of last modification. List all datasets you own on data.world
list_my_projects
Returns project summaries including role (owner/contributor), creation date, and linked datasets. List all projects you own on data.world
list_project_insights
Insights represent documented findings and data visualizations attached to the project workspace. List all insights published within a project
list_recent_activity
Returns a stream of activity logs including dataset updates, project contributions, and new collection entries. List recent activities in your data.world account
search_catalog
world index. Supports full-text search across titles, descriptions, and tags. Returns a ranked list of matching resources. Search for datasets and projects across data.world
Example Prompts for data.world in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with data.world immediately.
"Search for datasets related to 'Global Climate Change'."
"List all SQL queries saved in my project 'Sales Analysis 2024'."
"Show me the insights published in dataset 'Retail Trends'."
Troubleshooting data.world MCP Server with LlamaIndex
Common issues when connecting data.world to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpdata.world + LlamaIndex FAQ
Common questions about integrating data.world 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?
Connect data.world with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect data.world to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.