Brasil.io MCP Server for LlamaIndexGive LlamaIndex instant access to 3 tools to Get Table Metadata, List Datasets, Query Table Data
GDPR Free for SubscribersLlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Brasil.io 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 Brasil.io MCP Server for LlamaIndex is a standout in the Data Analytics category — giving your AI agent 3 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 Brasil.io. "
"You have 3 tools available."
),
)
response = await agent.run(
"What tools are available in Brasil.io?"
)
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 Brasil.io MCP Server
Connect to Brasil.io, the leading platform for accessible Brazilian public data, and empower your AI agent to analyze real-world datasets through natural conversation.
LlamaIndex agents combine Brasil.io tool responses with indexed documents for comprehensive, grounded answers. Connect 3 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
- Dataset Discovery — List all available public datasets hosted on the platform, from health data to judicial salaries.
- Metadata Inspection — Fetch detailed schemas and metadata for specific tables to understand available columns and data types.
- Advanced Querying — Retrieve actual data records with powerful filtering capabilities (by state, city, date, etc.) using simple JSON filters.
- Pagination Support — Navigate through large datasets efficiently using built-in pagination controls.
The Brasil.io MCP Server exposes 3 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 3 Brasil.io tools available for LlamaIndex
When LlamaIndex connects to Brasil.io through Vinkius, your AI agent gets direct access to every tool listed below — spanning brazil-data, public-datasets, open-data, 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.
Get table metadata on Brasil.io
Get metadata for a specific table in a dataset
List datasets on Brasil.io
io platform. Supports pagination. List available datasets on Brasil.io
Query table data on Brasil.io
You can pass arbitrary filters as a JSON string to filter by column names (e.g., {"state": "PR"}). Query data records from a specific table
Connect Brasil.io to LlamaIndex via MCP
Follow these steps to wire Brasil.io 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 Brasil.io MCP Server
LlamaIndex provides unique advantages when paired with Brasil.io through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Brasil.io tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Brasil.io tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Brasil.io, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Brasil.io tools were called, what data was returned, and how it influenced the final answer
Brasil.io + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Brasil.io MCP Server delivers measurable value.
Hybrid search: combine Brasil.io real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Brasil.io 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 Brasil.io for fresh data
Analytical workflows: chain Brasil.io queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for Brasil.io in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Brasil.io immediately.
"List all available datasets on Brasil.io."
"Show me the metadata for the 'caso' table in the 'covid19' dataset."
"Query the 'caso' table in 'covid19' for the state of 'PR' and city 'Curitiba'."
Troubleshooting Brasil.io MCP Server with LlamaIndex
Common issues when connecting Brasil.io to LlamaIndex through Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpBrasil.io + LlamaIndex FAQ
Common questions about integrating Brasil.io 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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