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Mato Grosso do Sul Open Data MCP Server for LangChainGive LangChain instant access to 7 tools to Datastore Search, Datastore Search Sql, Get Package, and more

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LangChain is the leading Python framework for composable LLM applications. Connect Mato Grosso do Sul Open Data through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

Ask AI about this MCP Server for LangChain

The Mato Grosso do Sul Open Data MCP Server for LangChain is a standout in the Data Analytics category — giving your AI agent 7 tools to work with, ready to go from day one.

Built for AI Agents by Vinkius

Vinkius delivers Streamable HTTP and SSE to any MCP client

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

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MultiServerMCPClient({
        "mato-grosso-do-sul-open-data": {
            "transport": "streamable_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,
        )
        response = await agent.ainvoke({
            "messages": [{
                "role": "user",
                "content": "Using Mato Grosso do Sul Open Data, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())
Mato Grosso do Sul Open Data
Fully ManagedVinkius Servers
60%Token savings
High SecurityEnterprise-grade
IAMAccess control
EU AI ActCompliant
DLPData protection
V8 IsolateSandboxed
Ed25519Audit chain
<40msKill switch
Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Mato Grosso do Sul Open Data MCP Server

Connect to the Mato Grosso do Sul (MS) Open Data Portal to explore and analyze public information from the Brazilian state. This server allows AI agents to programmatically access datasets, organizations, and specific resource records.

LangChain's ecosystem of 500+ components combines seamlessly with Mato Grosso do Sul Open Data through native MCP adapters. Connect 7 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.

What you can do

  • Datasets & Packages — List all available public data packages and retrieve detailed metadata using list_packages and get_package.
  • Resource Inspection — Drill down into specific files or links within datasets to understand their structure with get_resource.
  • DataStore Search — Filter and search through actual records in CSVs or spreadsheets directly using datastore_search.
  • SQL Queries — Execute complex SQL statements on DataStore resources for advanced data analysis with datastore_search_sql.
  • Organizational Context — List the government organizations and groups responsible for the data via list_organizations and list_groups.

The Mato Grosso do Sul Open Data MCP Server exposes 7 tools through the Vinkius. Connect it to LangChain in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 7 Mato Grosso do Sul Open Data tools available for LangChain

When LangChain connects to Mato Grosso do Sul Open Data through Vinkius, your AI agent gets direct access to every tool listed below — spanning open-data, brazil, public-records, 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 Mato Grosso do Sul Open Data

Search data in a DataStore resource

datastore

Datastore search sql on Mato Grosso do Sul Open Data

Execute a SQL query on DataStore resources

get

Get package on Mato Grosso do Sul Open Data

Get details of a specific dataset package

get

Get resource on Mato Grosso do Sul Open Data

Get details of a specific resource

list

List groups on Mato Grosso do Sul Open Data

List all groups

list

List organizations on Mato Grosso do Sul Open Data

List all organizations

list

List packages on Mato Grosso do Sul Open Data

List all dataset packages

Connect Mato Grosso do Sul Open Data to LangChain via MCP

Follow these steps to wire Mato Grosso do Sul Open Data into LangChain. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

01

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai
02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token
03

Run the agent

Save the code and run python agent.py
04

Explore tools

The agent discovers 7 tools from Mato Grosso do Sul Open Data via MCP

Why Use LangChain with the Mato Grosso do Sul Open Data MCP Server

LangChain provides unique advantages when paired with Mato Grosso do Sul Open Data through the Model Context Protocol.

01

The largest ecosystem of integrations, chains, and agents. combine Mato Grosso do Sul Open Data MCP tools with 500+ LangChain components

02

Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step

03

LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging

04

Memory and conversation persistence let agents maintain context across Mato Grosso do Sul Open Data queries for multi-turn workflows

Mato Grosso do Sul Open Data + LangChain Use Cases

Practical scenarios where LangChain combined with the Mato Grosso do Sul Open Data MCP Server delivers measurable value.

01

RAG with live data: combine Mato Grosso do Sul Open Data tool results with vector store retrievals for answers grounded in both real-time and historical data

02

Autonomous research agents: LangChain agents query Mato Grosso do Sul Open Data, synthesize findings, and generate comprehensive research reports

03

Multi-tool orchestration: chain Mato Grosso do Sul Open Data tools with web scrapers, databases, and calculators in a single agent run

04

Production monitoring: use LangSmith to trace every Mato Grosso do Sul Open Data tool call, measure latency, and optimize your agent's performance

Example Prompts for Mato Grosso do Sul Open Data in LangChain

Ready-to-use prompts you can give your LangChain agent to start working with Mato Grosso do Sul Open Data immediately.

01

"List all the public data packages available in Mato Grosso do Sul."

02

"Search for records containing 'Campo Grande' in the resource ID 550e8400-e29b-41d4-a716-446655440000."

03

"Run a SQL query to select all columns from resource 'receita-2023' where the value is greater than 1000000."

Troubleshooting Mato Grosso do Sul Open Data MCP Server with LangChain

Common issues when connecting Mato Grosso do Sul Open Data to LangChain through Vinkius, and how to resolve them.

01

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Mato Grosso do Sul Open Data + LangChain FAQ

Common questions about integrating Mato Grosso do Sul Open Data MCP Server with LangChain.

01

How does LangChain connect to MCP servers?

Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.
02

Which LangChain agent types work with MCP?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.
03

Can I trace MCP tool calls in LangSmith?

Yes. All MCP tool invocations appear as traced steps in LangSmith, showing input parameters, response payloads, latency, and token usage.

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