IBGE Pesquisas — Brasil Cidades MCP Server for LlamaIndex 4 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add IBGE Pesquisas — Brasil Cidades as an MCP tool provider through 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 IBGE Pesquisas — Brasil Cidades. "
"You have 4 tools available."
),
)
response = await agent.run(
"What tools are available in IBGE Pesquisas — Brasil Cidades?"
)
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 IBGE Pesquisas — Brasil Cidades MCP Server
Access the same data engine powering the official Brasil Cidades portal — the IBGE's most comprehensive municipal indicator database.
LlamaIndex agents combine IBGE Pesquisas — Brasil Cidades tool responses with indexed documents for comprehensive, grounded answers. Connect 4 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
- List All Surveys — Browse the complete IBGE research catalog (Census, PNAD, POF, Agricultural Census, etc.)
- Municipal Indicators — Health, education, income, sanitation, and infrastructure data per city
- Cross-Survey Results — Query any indicator across any survey and time period
- City Rankings — Rank municipalities by any indicator (best HDI, highest GDP per capita, etc.)
The IBGE Pesquisas — Brasil Cidades MCP Server exposes 4 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 IBGE Pesquisas — Brasil Cidades to LlamaIndex via MCP
Follow these steps to integrate the IBGE Pesquisas — Brasil Cidades 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 4 tools from IBGE Pesquisas — Brasil Cidades
Why Use LlamaIndex with the IBGE Pesquisas — Brasil Cidades MCP Server
LlamaIndex provides unique advantages when paired with IBGE Pesquisas — Brasil Cidades through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine IBGE Pesquisas — Brasil Cidades tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain IBGE Pesquisas — Brasil Cidades tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query IBGE Pesquisas — Brasil Cidades, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what IBGE Pesquisas — Brasil Cidades tools were called, what data was returned, and how it influenced the final answer
IBGE Pesquisas — Brasil Cidades + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the IBGE Pesquisas — Brasil Cidades MCP Server delivers measurable value.
Hybrid search: combine IBGE Pesquisas — Brasil Cidades real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query IBGE Pesquisas — Brasil Cidades 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 IBGE Pesquisas — Brasil Cidades for fresh data
Analytical workflows: chain IBGE Pesquisas — Brasil Cidades queries with LlamaIndex's data connectors to build multi-source analytical reports
IBGE Pesquisas — Brasil Cidades MCP Tools for LlamaIndex (4)
These 4 tools become available when you connect IBGE Pesquisas — Brasil Cidades to LlamaIndex via MCP:
get_indicadores
Use survey ID (e.g., 33 for Censo Demográfico, 38 for Produção Agrícola Municipal). Get indicators from a specific IBGE survey
get_ranking_indicador
Rank municipalities by a specific indicator
get_resultados
Localities can be: BR (Brazil), UF code (e.g., 33 for RJ), or municipality IBGE code. Get survey results for specific municipalities
list_pesquisas
List all IBGE surveys and research programs
Example Prompts for IBGE Pesquisas — Brasil Cidades in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with IBGE Pesquisas — Brasil Cidades immediately.
"What are the education indicators for the city of Curitiba?"
"Which Brazilian cities have the highest GDP per capita?"
"Compare health indicators between São Paulo and Salvador"
Troubleshooting IBGE Pesquisas — Brasil Cidades MCP Server with LlamaIndex
Common issues when connecting IBGE Pesquisas — Brasil Cidades to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpIBGE Pesquisas — Brasil Cidades + LlamaIndex FAQ
Common questions about integrating IBGE Pesquisas — Brasil Cidades 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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Connect IBGE Pesquisas — Brasil Cidades to LlamaIndex
Get your token, paste the configuration, and start using 4 tools in under 2 minutes. No API key management needed.