How to Use the Ayuntamiento de Zaragoza MCP in LangChain

Q: Can LangChain agents read existing Ayuntamiento de Zaragoza 311 tickets?

Yes. Call listopen311requests to pull an array of active complaints. The agent parses the JSON response and can filter by status or category.

Build intelligent pipelines for Zaragoza city services using LangChain to route 311 requests and book municipal appointments.

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Connect Ayuntamiento de Zaragoza MCP to LangChain

Create your Vinkius account to connect Ayuntamiento de Zaragoza to LangChain 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 Ayuntamiento de Zaragoza with LangChain

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Perplexity

Chain Zaragoza MCP Server data

LangChain ReAct agents parse incoming citizen complaints and route them through the `submit_open311_request` tool. You write the logic that decides if a pothole report needs immediate attention or just logs into the municipal database. The agent checks `list_open311_services` first to map the issue to the correct department ID. Tracing these interactions happens automatically in LangSmith. You see the exact token usage when the agent pulls historical data via `list_open311_requests` before creating a new ticket. Every input and output gets logged so you know exactly why the agent made a specific API call.

Automate Cita Previa booking

Municipal appointment scheduling requires multiple steps that fit perfectly into a LangGraph state machine. Your agent queries `list_agendas` to find the right office, checks `get_agenda_availability` for open slots, and finally executes the `book_appointment` MCP tool. The output of each node feeds directly into the next. Handling failures becomes trivial with built-in retry mechanisms. If `get_my_appointments` times out, the chain pauses and tries again without losing the user's session context. You control the exact execution flow from search to final booking confirmation.

Query semantic city datasets

Zaragoza publishes massive amounts of public data that your agent can query dynamically. Using `execute_sparql_query`, you pass raw SPARQL strings directly to the city's semantic web endpoint. The agent retrieves lists of restaurants, monuments, or bus stops and formats them for the user. Fallback chains handle cases where the complex SPARQL query fails. The system automatically pivots to `query_dataset` for simpler, REST-based data retrieval. You build resilience directly into the agent's decision tree.

Setup guide

Set up Ayuntamiento de Zaragoza MCP in LangChain

Prerequisites

Python 3.10+ installed
langchain-mcp-adapters + langgraph packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install langchain-mcp-adapters langgraph langchain-openai. The MCP adapters package converts MCP tools into native LangChain BaseTool objects.
2

Connect via HTTP transport
Use MultiServerMCPClient with "transport": "http" pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create a ReAct agent
Pass the discovered tools to create_react_agent() from LangGraph. The agent automatically routes Ayuntamiento de Zaragoza tool calls through the MCP protocol.
4

Run with any LLM
Swap ChatOpenAI for ChatAnthropic, ChatGoogleGenerativeAI, or any LangChain-compatible model. The MCP tools work identically across all providers.

agent.py

from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI

async with MultiServerMCPClient({
    "ayuntamiento-de-zaragoza-mcp": {
        "transport": "http",
        "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
    }
}) as client:
    tools = client.get_tools()

    agent = create_react_agent(
        ChatOpenAI(model="gpt-4o"),
        tools,
    )
    result = await agent.ainvoke({
        "messages": "List recent Ayuntamiento de Zaragoza transactions"
    })
    print(result["messages"][-1].content)

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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 Ayuntamiento de Zaragoza. 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 Ayuntamiento de Zaragoza MCP in LangChain

Use MultiServerMCPClient with your Vinkius endpoint URL and pass the bearer token in the transport headers. The client automatically handles auth for protected tools like `create_map`.

Yes. Call `list_open311_requests` to pull an array of active complaints. The agent parses the JSON response and can filter by status or category.

LangChain catches the transport error and triggers your fallback chain. You define how the agent responds, whether that means queuing the `submit_open311_request` payload or alerting the user.

LangSmith captures every tool invocation automatically. You view the exact latency and token counts for `execute_sparql_query` in your project dashboard.

Vinkius runs the integration inside an ephemeral V8 isolate sandbox. Tools like `book_appointment` handle sensitive identification numbers and contact details, but the memory clears completely after the session ends.

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