How to Use the Aracaju MCP in LlamaIndex

Index Aracaju transparency data directly into your LlamaIndex vector stores for zero-hallucination public finance RAG.

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Connect Aracaju MCP to LlamaIndex

Create your Vinkius account to connect Aracaju 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 Aracaju with LlamaIndex

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Index Aracaju revenues into LlamaIndex

The `list_revenues` tool fetches live municipal income data, which your LlamaIndex pipeline indexes directly into a vector store. This turns raw public finance numbers into a semantic database your agent can query. Instead of guessing where municipal funds come from, your agent retrieves grounded financial facts. You avoid hallucinations by forcing the model to cite specific revenue entries.

Query bids semantically with this MCP Server

The `list_bids` tool retrieves public tenders, converting complex procurement documents into searchable chunks. This MCP Server lets your agent perform semantic searches over active municipal bidding processes. Your agent can quickly find bids related to specific sectors, like health or education, without exact keyword matches. You speed up the analysis of city contracts significantly.

Ground payroll queries in LlamaIndex

The `list_personnel` tool pulls active public servant salary data to ground your agent's answers. LlamaIndex uses this tool output as context, preventing the agent from generating fictional salary figures. You get a reliable QA system for municipal payroll. Every answer your agent provides is backed by a verifiable record from the Aracaju transparency portal.

Setup guide

Set up Aracaju 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 Aracaju 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 Aracaju tools.",
)
response = await agent.run("List recent Aracaju 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 Aracaju Transparency. 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 Aracaju MCP in LlamaIndex

Yes, you can store the outputs of the expense tools in a local vector index to avoid calling the API repeatedly. This speeds up your semantic search queries significantly.

The tool spec automatically maps the JSON output from tools like `list_contracts` into standard LlamaIndex document objects. This lets your indexers read the data without custom parsers.

Use the basic client to connect to the Vinkius endpoint, then wrap it in the tool spec. Pass the resulting tools to your function agent to start indexing.

Yes, the tools support pagination parameters so your agent can crawl through thousands of rows of municipal data without hitting memory limits.

Because this server only retrieves publicly available city finances and contracts, no private personal data is ever accessed. Vinkius secures the connection using token-based authentication and routes all traffic through ephemeral sandboxes.

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