Compatible with every major AI agent and IDE
What is the INMET (Apitempo - Meteorologia) MCP Server?
Connect to the INMET (Instituto Nacional de Meteorologia) API to retrieve comprehensive weather data across Brazil. This server allows AI agents to query a vast network of automatic and manual stations, providing precise atmospheric measurements and forecasts.
What you can do
- Meteorological Stations — List all automatic (T) and manual (M) stations across the Brazilian territory.
- Historical & Real-time Data — Fetch daily or hourly measurements (temperature, humidity, pressure) for specific station IDs.
- Regional Analysis — Query data for all stations within specific Brazilian regions (N, NE, CO, SE, S) for a given date.
- Weather Forecasts — Get detailed forecasts for cities using IBGE codes or retrieve all available forecasts at once.
- Satellite Imagery — Access the latest GOES-16 satellite metadata and image URLs for visual weather monitoring.
How it works
- Subscribe to this server
- Enter your INMET API Token (if required)
- Start querying weather patterns directly from your AI assistant
Who is this for?
- Data Scientists & Researchers — analyze climate trends and historical weather patterns in Brazil.
- Logistics & Agriculture — monitor local weather conditions and forecasts to optimize operations.
- Developers — integrate official Brazilian meteorological data into applications without complex API handling.
Built-in capabilities (8)
Get weather forecasts for all supported cities
Get weather forecast for a specific city
Get meteorological data by date for a station
Get meteorological data for all stations in a specific region
Get latest GOES-16 satellite images
Get daily meteorological data for a specific station
Get hourly data for a specific station and time
List meteorological stations by type
Why CrewAI?
When paired with CrewAI, INMET (Apitempo - Meteorologia) becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call INMET (Apitempo - Meteorologia) tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.
- —
Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools
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CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the
mcpsparameter and agents auto-discover every available tool at runtime - —
Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls
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Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports
INMET (Apitempo - Meteorologia) in CrewAI
INMET (Apitempo - Meteorologia) and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect INMET (Apitempo - Meteorologia) to CrewAI 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 INMET (Apitempo - Meteorologia) in CrewAI
The INMET (Apitempo - Meteorologia) 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 8 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in CrewAI 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
INMET (Apitempo - Meteorologia) for CrewAI
Every tool call from CrewAI to the INMET (Apitempo - Meteorologia) 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 get the weather forecast for a specific city in Brazil?
You can use the get_forecast_by_city tool by providing the city's IBGE code. The agent will return detailed forecast information including temperature and conditions.
Can I access real-time satellite imagery of Brazil?
Yes! Use the get_satellite_images tool to retrieve the latest metadata and URLs for GOES-16 satellite images covering the Brazilian territory.
How do I find the ID of a meteorological station?
Use the list_stations tool with the type 'T' for automatic or 'M' for manual stations. This will provide a list of all stations and their respective IDs.
How does CrewAI discover and connect to MCP tools?
CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.
Can different agents in the same crew use different MCP servers?
Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.
What happens when an MCP tool call fails during a crew run?
CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.
Can CrewAI agents call multiple MCP tools in parallel?
CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.
Can I run CrewAI crews on a schedule (cron)?
Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.
MCP tools not discovered
Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.
Agent not using tools
Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".
Timeout errors
CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.
Rate limiting or 429 errors
Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.
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