How to Use the INPE (STAC API - Satélites) MCP in CrewAI

Q: How do I configure CrewAI agents to use INPE (STAC API - Satélites) tools?

Add the server URL to the mcps list in your Agent definition. CrewAI automatically discovers tools like searchitems and assigns them to the agent.

Q: Can I limit which CrewAI agents have access to INPE (STAC API - Satélites) MCP Server?

Yes, use MCPServerHTTP and toolfilter to assign specific tools to specific agents. For example, give only your GIS agent access to listcollectionitems.

Q: How do CrewAI agents coordinate when searching INPE (STAC API - Satélites)?

One agent uses listcollections to find active datasets, then passes those collection IDs to a second agent who runs searchitems to locate cloud-free imagery.

Q: Does this setup support the standard STAC API spec?

Yes, it exposes standard STAC endpoints like getconformance and getrootcatalog. This ensures compatibility with any LLM trained on spatial data standards.

Deploy specialized agent teams to analyze Brazilian satellite catalogs using CrewAI.

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Setup INPE (STAC API - Satélites) with CrewAI

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Multi-agent coordination for Earth observation

The `search_items` tool enables your research crew to locate specific satellite frames across multiple Brazilian missions. In a CrewAI setup, one agent can generate search coordinates, while a second agent calls this tool to retrieve the matching STAC items. You can restrict tool access using `tool_filter` so only your mapping agent handles the geospatial queries. This separation of duties prevents other agents from wasting context window space on raw coordinate arrays.

Map catalog hierarchies with this MCP Server

The `get_root_catalog` tool retrieves the top-level entry points for the Brazilian Space Research Institute's data. This MCP Server lets your manager agent map out the available satellite collections before directing worker agents to search specific regions. CrewAI's shared memory allows agents to pass the root catalog structure between tasks. Your crew can systematically crawl from the root to specific sub-collections without redundant network requests.

Inspect specific satellite sensors autonomously

The `get_collection` tool provides detailed parameters for platforms like CBERS-4. Your analytical agents use this metadata to compare sensor bands and resolution before recommending specific datasets for environmental monitoring. By passing the HTTP endpoint to `mcps` in your CrewAI configuration, your agents instantly understand how to structure inquiries for specific Brazilian space assets. The crew handles the entire discovery process without manual coding.

Setup guide

Set up INPE (STAC API - Satélites) MCP in CrewAI

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke INPE (STAC API - Satélites) tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="INPE (STAC API - Satélites) Analyst",
    goal="Access and analyze INPE (STAC API - Satélites) data via MCP.",
    backstory="Expert analyst with direct INPE (STAC API - Satélites) access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent INPE (STAC API - Satélites) transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

server_params = SseServerParameters(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="INPE (STAC API - Satélites) Analyst",
        goal="Access and analyze INPE (STAC API - Satélites) data via MCP.",
        backstory="Expert analyst with direct INPE (STAC API - Satélites) access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent INPE (STAC API - Satélites) transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

    crew = Crew(agents=[agent], tasks=[task])
    result = crew.kickoff()
    print(result)

Get your connection token →

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Common questions about INPE (STAC API - Satélites) MCP in CrewAI

Add the server URL to the `mcps` list in your Agent definition. CrewAI automatically discovers tools like `search_items` and assigns them to the agent.

Yes, use `MCPServerHTTP` and `tool_filter` to assign specific tools to specific agents. For example, give only your GIS agent access to `list_collection_items`.

One agent uses `list_collections` to find active datasets, then passes those collection IDs to a second agent who runs `search_items` to locate cloud-free imagery.

Yes, it exposes standard STAC endpoints like `get_conformance` and `get_root_catalog`. This ensures compatibility with any LLM trained on spatial data standards.

All geospatial coordinates and collection queries are processed in memory during the crew's execution. Vinkius runs the connector in a secure, zero-trust sandbox, ensuring your spatial queries remain private.

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