How to Use the ALESP (Assembleia SP) MCP in LlamaIndex

Q: Is it possible to filter ALESP (Assembleia SP) data before indexing in LlamaIndex?

Yes, you can use the allowedtools filter. This limits the data pulled from the assembly to only the categories your agent requires.

Q: Can I search ALESP (Assembleia SP) history using LlamaIndex?

By indexing historical records from getdocumentoandamento, your agent can perform semantic searches across years of legislative activity.

Index legislative history into searchable knowledge bases with LlamaIndex and the ALESP (Assembleia SP) MCP Server.

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Connect ALESP (Assembleia SP) MCP to LlamaIndex

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Setup ALESP (Assembleia SP) with LlamaIndex

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Vectorize ALESP (Assembleia SP) documents

Turn legislative proposals into searchable vectors. By calling `get_documento_andamento`, you pull the latest status updates and push them into your index for instant retrieval. This turns static legislative data into a dynamic knowledge base. Your agent answers questions about laws based on the retrieved text rather than relying on stale training data.

Query LlamaIndex with live assembly data

Combine your private documents with public records from the assembly. When you run `get_legislacao_normas`, the output is indexed alongside your existing files for unified semantic search. Your agent performs RAG operations that bridge the gap between internal policy and state law. It's a precise way to ground AI responses in verified facts.

Automate ALESP (Assembleia SP) data ingestion

Use the server to keep your index fresh without manual imports. Tools like `get_deputados` provide a steady stream of updates that you can pipe directly into your vector store. This keeps your agent current on committee members and staff assignments. You define the frequency and scope of updates within your indexing pipeline.

Setup guide

Set up ALESP (Assembleia SP) 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 ALESP (Assembleia SP) 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 ALESP (Assembleia SP) tools.",
)
response = await agent.run("List recent ALESP (Assembleia SP) data")

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Common questions about ALESP (Assembleia SP) MCP in LlamaIndex

The tool outputs are converted into structured documents. These are then embedded into your vector store for semantic retrieval.

Yes, you can use the allowed_tools filter. This limits the data pulled from the assembly to only the categories your agent requires.

By indexing historical records from `get_documento_andamento`, your agent can perform semantic searches across years of legislative activity.

You just need the MCP tool spec for LlamaIndex. It handles the mapping of tools to your agent functions automatically.

Your vector store is encrypted at rest within your environment. Only the specific legislative data you choose to index is stored there.

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