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

Q: Is legislative data from ALESP (Assembleia SP) secure when processed by CrewAI?

All MCP tool calls, including queries to getfuncionarioscargos or getlotacoes, run through an ephemeral, zero-trust V8 sandbox. Your credentials and retrieved staff records are never exposed to external networks.

Deploy specialized agent crews to analyze São Paulo legislative data autonomously using CrewAI.

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Connect ALESP (Assembleia SP) MCP to CrewAI

Create your Vinkius account to connect ALESP (Assembleia SP) to CrewAI 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 ALESP (Assembleia SP) with CrewAI

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Run multi-agent ALESP (Assembleia SP) legislative audits

`get_deputados` serves as the starting point for your research crew. One agent fetches the list of active deputies while a second agent pulls their cabinet expenses via `get_despesas_gabinetes`. Because CrewAI agents share memory, the analyzer agent remembers previous expense spikes when reviewing new data. They collaborate autonomously to draft reports without manual intervention.

Track state norms with an autonomous CrewAI research team

`get_legislacao_normas` allows your policy-focused crew to retrieve state laws and decrees. You assign a researcher agent to fetch the norms, while a legal analyst agent categorizes them using `get_legislacao_temas`. This multi-agent setup processes complex legislative themes sequentially. The crew works through the data step-by-step, ensuring every decree is correctly mapped to its corresponding administrative unit via `get_uas`.

Monitor committee votes using specialized MCP Server tools

`get_comissoes_votacoes` provides the raw vote tallies from legislative panels. Your monitor agent watches these votes, while a moderator agent evaluates the political impact based on party alignments from `get_partidos`. You configure this pipeline by passing the Vinkius HTTP endpoint directly into the agents' `mcps` array. The crew coordinates their actions, escalating critical vote shifts to your team's Slack channel.

Setup guide

Set up ALESP (Assembleia SP) MCP in CrewAI

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke ALESP (Assembleia SP) tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="ALESP (Assembleia SP) Analyst",
    goal="Access and analyze ALESP (Assembleia SP) data via MCP.",
    backstory="Expert analyst with direct ALESP (Assembleia SP) access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent ALESP (Assembleia SP) transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

Get your connection token →

Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

server_params = SseServerParameters(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="ALESP (Assembleia SP) Analyst",
        goal="Access and analyze ALESP (Assembleia SP) data via MCP.",
        backstory="Expert analyst with direct ALESP (Assembleia SP) access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent ALESP (Assembleia SP) transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

    crew = Crew(agents=[agent], tasks=[task])
    result = crew.kickoff()
    print(result)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by ALESP. 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 ALESP (Assembleia SP) MCP in CrewAI

You pass the Vinkius MCP Server URL directly in the agent's `mcps` parameter. For granular control, import `MCPServerHTTP` from `crewai.mcp` and use a tool filter to expose only specific endpoints like `get_deputados`.

Yes, agents share access to the configured tools. While your researcher agent uses `get_comissoes` to map committees, your analyst agent can simultaneously query `get_comissoes_membros` to identify key members.

You set up a hierarchical crew where a manager agent assigns tasks to specialists. One specialist fetches proposal histories using `get_documento_andamento` while another evaluates the authors using `get_documento_autor`.

CrewAI supports Streamable HTTP and SSE transports. When connecting to the Vinkius managed server, the framework automatically handles the connection protocol using your single endpoint token.

All MCP tool calls, including queries to `get_funcionarios_cargos` or `get_lotacoes`, run through an ephemeral, zero-trust V8 sandbox. Your credentials and retrieved staff records are never exposed to external networks.

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