How to Use the Gobierno Abierto Valencia MCP in LlamaIndex

Q: How do I add the Gobierno Abierto Valencia tools to a LlamaIndex agent?

Install the tools via pip install llama-index-tools-mcp. Initialize the MCP client with the server URL, wrap it in a McpToolSpec, and pass the tools to your FunctionAgent.

Q: Can LlamaIndex store queries from Gobierno Abierto Valencia in a vector database?

Yes, you can run searchdatastore to fetch municipal records and load them directly into your vector store. This lets you run semantic searches over Valencia's public records later.

Q: How does Gobierno Abierto Valencia handle schema changes in LlamaIndex?

Your agent should call showpackage to inspect the dataset schema before querying. LlamaIndex can parse this metadata to adjust its query parameters dynamically if the portal structure changes.

Index live public records from Valencia directly into your LlamaIndex vector stores for grounded RAG.

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Connect Gobierno Abierto Valencia MCP to LlamaIndex

Create your Vinkius account to connect Gobierno Abierto Valencia 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 Gobierno Abierto Valencia with LlamaIndex

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Index Valencia's data categories into LlamaIndex

The `list_groups` tool retrieves the high-level categories of Valencia's open data portal to bootstrap your index. Your LlamaIndex pipeline uses these groups to organize and route semantic search queries to the right data silos. By combining this with `list_packages`, your agent builds a local map of Valencia's public data structure. This map is then indexed, allowing users to search for relevant datasets using natural language instead of exact API keys.

Feed raw resource metadata into your vector index

The `show_resource` tool extracts detailed metadata for individual files on the Valencia portal. LlamaIndex reads this metadata to understand the file formats and update dates before indexing the content. Your agent uses `show_package` to get the broader context of the dataset. This ensures that every vector chunk stored in your index has the correct municipal metadata tags attached to it.

Query live municipal databases using the MCP Server

The `search_datastore` tool pulls live records directly from Valencia's active databases. LlamaIndex uses these real-time records to answer user queries with actual, current public data rather than relying on stale training data. This tool allows your RAG application to bypass static document uploads entirely. Your agent queries the live datastore, formats the rows, and indexes them on the fly to provide accurate, grounded answers.

Setup guide

Set up Gobierno Abierto Valencia 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 Gobierno Abierto Valencia 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 Gobierno Abierto Valencia tools.",
)
response = await agent.run("List recent Gobierno Abierto Valencia 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 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.

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Common questions about Gobierno Abierto Valencia MCP in LlamaIndex

Install the tools via `pip install llama-index-tools-mcp`. Initialize the MCP client with the server URL, wrap it in a `McpToolSpec`, and pass the tools to your `FunctionAgent`.

Yes, you can run `search_datastore` to fetch municipal records and load them directly into your vector store. This lets you run semantic searches over Valencia's public records later.

Your agent should call `show_package` to inspect the dataset schema before querying. LlamaIndex can parse this metadata to adjust its query parameters dynamically if the portal structure changes.

Yes, you can use LlamaIndex's tool filtering to only expose `search_datastore` and `show_resource` to your agent. This limits the agent's focus to querying specific datasets rather than listing the entire catalog.

It only accesses public municipal datasets and open records from Valencia's portal, meaning no personal or sensitive data is processed. Your LlamaIndex queries and vector store embeddings are kept secure within your own infrastructure and Vinkius's MCP sandbox.

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