How to Use the Cuiabá Transparency MCP in LlamaIndex

Q: How do I handle asynchronous tool calls?

The framework provides an await mcptoolspec.totoollistasync() method. This ensures your agent doesn't block the main thread while waiting for the MCP server to respond.

Index live municipal financial records straight into your LlamaIndex RAG applications.

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Connect Cuiabá Transparency MCP to LlamaIndex

Create your Vinkius account to connect Cuiabá Transparency to LlamaIndex and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Cuiabá Transparency with LlamaIndex

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Vectorize Cuiabá Transparency MCP Server

LlamaIndex treats tool outputs as raw material for your knowledge base. When your agent runs `list_expenses`, the engine doesn't just read the response. It embeds those municipal expenditure records directly into your vector store for semantic search. This turns static MCP tool calls into a queryable history. You ask about road repair costs, and the system retrieves the exact spending data pulled during previous sessions without needing a fresh API hit.

Grounded Answers on Public Tenders

Hallucinations destroy trust in public sector analysis. By connecting `list_contracts` via the tool adapter, your FunctionAgent bases its answers strictly on actual bidding documents returned by the city. If a user asks which company won the sanitation bid, the agent retrieves the live data. You get factual, verifiable outputs backed by the actual municipal database.

Combine Civic Data with Local Docs

City analysis usually requires comparing live data against static policy PDFs. LlamaIndex lets you run `list_budget` through the MCP integration, then cross-reference those figures against local zoning laws stored in your existing index. You configure the McpToolSpec to expose specific endpoints. Using the allowed tools filter, you restrict the agent to just `list_personnel` and `list_revenues` while blocking contract queries entirely.

Setup guide

Set up Cuiabá Transparency MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.
3

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all Cuiabá Transparency MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to Cuiabá Transparency tools.",
)
response = await agent.run("List recent Cuiabá Transparency data")

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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 Cuiabá Transparency Portal. 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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Common questions about Cuiabá Transparency MCP in LlamaIndex

Run pip install llama-index-tools-mcp to get the adapter. Initialize a BasicMCPClient with the endpoint URL, wrap it in an McpToolSpec, and pass the async tool list to your FunctionAgent.

The framework embeds the returned JSON into your connected vector store. Subsequent queries run against this indexed knowledge rather than hitting the live endpoint again.

Yes, the tool spec accepts an allowed tools filter. You can expose just the municipal revenue endpoints while hiding the personnel and contract records.

The framework provides an await mcp_tool_spec.to_tool_list_async() method. This ensures your agent doesn't block the main thread while waiting for the MCP server to respond.

The Vinkius zero-trust architecture ensures your queries never leak. When pulling public servant rosters, the server operates purely ephemerally. Connections require a single endpoint token, and no request data persists on the host infrastructure.

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