São Paulo (Cidade) MCP Server for CrewAIGive CrewAI instant access to 11 tools to Datastore Search, Datastore Search Sql, Get Group, and more

Name: São Paulo (Cidade)
Price: 29 USD
Availability: InStock
Rating: 4.9 (1 reviews)
Author: Vinkius

GDPR Free for Subscribers

Connect your CrewAI agents to São Paulo (Cidade) through Vinkius, pass the Edge URL in the `mcps` parameter and every São Paulo (Cidade) tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

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The São Paulo (Cidade) MCP Server for CrewAI is a standout in the Data Analytics category — giving your AI agent 11 tools to work with, ready to go from day one.

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python

from crewai import Agent, Task, Crew

agent = Agent(
    role="São Paulo (Cidade) Specialist",
    goal="Help users interact with São Paulo (Cidade) effectively",
    backstory=(
        "You are an expert at leveraging São Paulo (Cidade) tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token. get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in São Paulo (Cidade) "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 11 available tools "
        "and what they can do."
    ),
)

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

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About São Paulo (Cidade) MCP Server

Connect your AI agent directly to the São Paulo City Open Data Portal (CKAN). This server allows you to navigate thousands of public datasets covering health, education, transport, and finance in Brazil's largest city.

When paired with CrewAI, São Paulo (Cidade) becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call São Paulo (Cidade) tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

What you can do

Dataset Discovery — Search for specific datasets using keywords or list all available packages in the portal.
Granular Inspection — Fetch detailed metadata for datasets and individual resources (files) to understand data structures.
Advanced Data Querying — Perform searches within data stores or execute complex SQL queries directly on CSV-backed resources.
Organizational Mapping — List and inspect city secretariats (organizations) and thematic groups to find relevant data sources.
Tag Exploration — Browse datasets by tags to discover related public information across different departments.

The São Paulo (Cidade) MCP Server exposes 11 tools through the Vinkius. Connect it to CrewAI in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 11 São Paulo (Cidade) tools available for CrewAI

When CrewAI connects to São Paulo (Cidade) through Vinkius, your AI agent gets direct access to every tool listed below — spanning open-data, urban-data, public-administration, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

datastore

Datastore search on São Paulo (Cidade)

Search data within a resource

datastore

Datastore search sql on São Paulo (Cidade)

SQL Query on a resource

get

Get group on São Paulo (Cidade)

Get group details

get

Get organization on São Paulo (Cidade)

Get organization details

get

Get package on São Paulo (Cidade)

Get dataset details

get

Get resource on São Paulo (Cidade)

Get resource details

list

List groups on São Paulo (Cidade)

g., Educação, Meio Ambiente). List groups (themes)

list

List organizations on São Paulo (Cidade)

g., Secretarias) that own datasets. List organizations

list

List packages on São Paulo (Cidade)

List all datasets (packages) in the portal

list

List tags on São Paulo (Cidade)

List tags

Search packages on São Paulo (Cidade)

Search datasets

Connect São Paulo (Cidade) to CrewAI via MCP

Follow these steps to wire São Paulo (Cidade) into CrewAI. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py. CrewAI auto-discovers 11 tools from São Paulo (Cidade)

Why Use CrewAI with the São Paulo (Cidade) MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with São Paulo (Cidade) through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

São Paulo (Cidade) + CrewAI Use Cases

Practical scenarios where CrewAI combined with the São Paulo (Cidade) MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries São Paulo (Cidade) for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries São Paulo (Cidade), analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain São Paulo (Cidade) tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries São Paulo (Cidade) against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Example Prompts for São Paulo (Cidade) in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with São Paulo (Cidade) immediately.

"Search for datasets about public transport in São Paulo."

"List all organizations that provide open data in the portal."

"Get the details for the dataset 'folha-de-pagamento'."

Troubleshooting São Paulo (Cidade) MCP Server with CrewAI

Common issues when connecting São Paulo (Cidade) to CrewAI through Vinkius, and how to resolve them.

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

São Paulo (Cidade) + CrewAI FAQ

Common questions about integrating São Paulo (Cidade) MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.

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