How to Use the Maxar (Satellite Imagery) MCP in CrewAI

Q: How do I pass the Maxar (Satellite Imagery) MCP Server to a CrewAI agent?

Pass the Vinkius HTTP URL directly into the mcps array when defining your CrewAI agents. The framework automatically parses the tools and exposes them to the agent's brain.

Run multi-agent crews that coordinate satellite searches, analyze footprints, and place orders using CrewAI and Maxar (Satellite Imagery).

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Connect Maxar (Satellite Imagery) MCP to CrewAI

Create your Vinkius account to connect Maxar (Satellite Imagery) to CrewAI 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 Maxar (Satellite Imagery) with CrewAI

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Coordinate Multi-Agent Satellite Searches

`search_discovery` allows your research agent to scan the catalog for specific coordinates while an analyst agent evaluates the metadata. They share state to filter out bad angles or high cloud cover. By delegating the search to a specialized agent, your crew can process huge geographic areas in parallel. No single agent gets bogged down with raw data processing.

Autonomous Imagery Ordering with CrewAI

`create_order` runs under the supervision of your operations agent, which triggers purchases only when quality criteria are met. A second moderator agent can watch the budget. This MCP Server tool integrates with CrewAI's hierarchical memory, ensuring agents remember previous search results before buying new tiles. You avoid duplicate orders and wasted API spend.

Automated Endpoint Resolution

`get_mws_endpoints` and `get_ard_tile` let your mapping agent resolve raw coordinates into active web map services. The agent automatically configures the correct projection and tile formats. This MCP Server integration helps your crew output ready-to-use GIS configurations directly to your team's Slack or database. Manual clicking and coordinate copying are completely eliminated from the pipeline.

Setup guide

Set up Maxar (Satellite Imagery) 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 Maxar (Satellite Imagery) tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

task = Task(
    description="List recent Maxar (Satellite Imagery) 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 →

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="Maxar (Satellite Imagery) Analyst",
        goal="Access and analyze Maxar (Satellite Imagery) data via MCP.",
        backstory="Expert analyst with direct Maxar (Satellite Imagery) access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Maxar (Satellite Imagery) 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 →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Maxar. 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 Maxar (Satellite Imagery) MCP in CrewAI

Pass the Vinkius HTTP URL directly into the `mcps` array when defining your CrewAI agents. The framework automatically parses the tools and exposes them to the agent's brain.

Yes, CrewAI manages tool access across the team, allowing different agents to call `search_discovery` or `get_ard_tile` concurrently. The framework handles the scheduling while Vinkius handles the execution.

Yes, your agents can use their reasoning capabilities to format raw addresses into bounding boxes before calling the tools. They handle the conversion step so you don't have to.

The server manages connection pooling, but you should configure your agents' backoff settings to handle heavy parallel requests. This prevents your API key from getting flagged.

All geographic bounding boxes and API tokens are processed in an ephemeral zero-trust runtime. Vinkius ensures your sensitive mission areas are never stored or leaked during agent execution.

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