How to Use the Gobierno Abierto Valencia MCP in CrewAI

Deploy autonomous research teams with CrewAI using the Gobierno Abierto Valencia MCP Server.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Gobierno Abierto Valencia MCP to CrewAI

Create your Vinkius account to connect Gobierno Abierto Valencia 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.

GDPR Free for Subscribers

Setup Gobierno Abierto Valencia with CrewAI

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Autonomous civic research with CrewAI

Assign an agent to crawl the portal using `list_groups` and `list_packages` to categorize new datasets. It acts as a scout, finding the relevant records for the rest of your crew to process. This removes the need for manual searching. Your agents work together, with one finding the data and another analyzing the contents.

Specialized data analysis in CrewAI

Use `show_resource` to extract the full details of a file once your research agent identifies it as important. Another agent then parses that information to summarize or act upon the findings. Role-based specialization makes this possible. You get a clean hand-off between the agent that retrieves the data and the agent that interprets it.

Scalable municipal monitoring in CrewAI

Run complex queries with `search_datastore` to feed persistent agents that watch for specific changes in public data. They stay active, checking for updates and reporting back to the monitor agent. You build an autonomous operation that keeps you informed without you having to touch a single line of code. It keeps the pulse on municipal data 24/7.

Setup guide

Set up Gobierno Abierto Valencia 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 Gobierno Abierto Valencia tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

task = Task(
    description="List recent Gobierno Abierto Valencia 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="Gobierno Abierto Valencia Analyst",
        goal="Access and analyze Gobierno Abierto Valencia data via MCP.",
        backstory="Expert analyst with direct Gobierno Abierto Valencia access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Gobierno Abierto Valencia 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 Gobierno Abierto Valencia. 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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Gobierno Abierto Valencia now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Gobierno Abierto Valencia MCP in CrewAI

Pass the server URL directly into your agent's MCP configuration list. The tools are then automatically shared among your crew members.

Yes. CrewAI's shared memory allows agents to pass the results of their tool calls to one another for collaborative analysis.

Use the tool filter configuration to allow only specific agents to access the datastore, keeping your setup secure and efficient.

You can set up a moderator agent to pace the queries. This prevents your crew from overwhelming the portal's API.

The server only interacts with public portals. The data is handled in an ephemeral sandbox, and your agent's internal memory never leaves your local execution environment.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript