Compatible with every major AI agent and IDE
What is the Rio Grande do Sul (Dados RS) MCP Server?
Connect to the Dados RS portal and explore the public data infrastructure of Rio Grande do Sul, Brazil. This server allows any AI agent to interact with the state's CKAN-based repository to find, inspect, and analyze government information.
What you can do
- Dataset Discovery — List all available datasets or search for specific topics like health, education, or finance using keywords.
- Organization Insights — Explore the government bodies (organizations) that publish data and list their specific contributions.
- Thematic Browsing — Navigate data through thematic groups such as 'Environment', 'Security', or 'Economy'.
- Deep Data Querying — Access tabular data within resources using filters or execute complex SQL queries directly against the DataStore.
- Resource Inspection — Fetch metadata for specific files, links, and data distributions to understand their structure before downloading.
How it works
- Subscribe to this server
- (Optional) Enter your Dados RS API Key for higher rate limits
- Start querying public data from Claude, Cursor, or any MCP-compatible client
Who is this for?
- Data Scientists & Researchers — quickly find and query government statistics without manual CSV downloads
- Journalists — audit public spending and government actions through direct access to official records
- Developers — integrate real-time public data into applications using the DataStore SQL capabilities
Built-in capabilities (11)
List all datasets (packages)
List groups
List organizations
Search datasets (packages)
Search DataStore
SQL Query on DataStore
Search resources
Show dataset details
Show group details
Show organization details
Show resource details
Why LangChain?
LangChain's ecosystem of 500+ components combines seamlessly with Rio Grande do Sul (Dados RS) through native MCP adapters. Connect 11 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.
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The largest ecosystem of integrations, chains, and agents. combine Rio Grande do Sul (Dados RS) MCP tools with 500+ LangChain components
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Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step
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LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging
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Memory and conversation persistence let agents maintain context across Rio Grande do Sul (Dados RS) queries for multi-turn workflows
Rio Grande do Sul (Dados RS) in LangChain
Rio Grande do Sul (Dados RS) and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect Rio Grande do Sul (Dados RS) to LangChain through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.
Raw MCP | Vinkius | |
|---|---|---|
| Server catalog | Find and host yourself | 4,000+ managed |
| Infrastructure | Self-hosted | Sandboxed V8 isolates |
| Credential handling | Plaintext in config | Vault + runtime injection |
| Data loss prevention | None | Configurable DLP policies |
| Kill switch | None | Global instant shutdown |
| Financial circuit breakers | None | Per-server limits + alerts |
| Audit trail | None | Ed25519 signed logs |
| SIEM log streaming | None | Splunk, Datadog, Webhook |
| Honeytokens | None | Canary alerts on leak |
| Custom domains | Not applicable | DNS challenge verified |
| GDPR compliance | Manual effort | Automated purge + export |
Why teams choose Vinkius for Rio Grande do Sul (Dados RS) in LangChain
The Rio Grande do Sul (Dados RS) 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. All 11 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in LangChain only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.

* 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
How Vinkius secures
Rio Grande do Sul (Dados RS) for LangChain
Every tool call from LangChain to the Rio Grande do Sul (Dados RS) MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
How can I search for datasets related to a specific topic like 'COVID'?
Use the search_datasets tool with the q parameter set to your topic. For example, searching for 'covid' will return all matching packages from the portal.
Can I perform advanced data analysis using SQL on the portal's data?
Yes! The search_datastore_sql tool allows you to execute full SQL SELECT statements against datasets stored in the CKAN DataStore, enabling complex filtering and aggregation.
How do I find which government departments are publishing data?
Use the list_organizations tool to get a complete list of all government bodies. You can then use show_organization with a specific ID to see their metadata and datasets.
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.
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.
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.
MultiServerMCPClient not found
Install: pip install langchain-mcp-adapters
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