How to Use the NASA Mars — Rover Photos from the Red Planet MCP in AutoGen

Q: How do I register the NASA Mars — Rover Photos from the Red Planet MCP Server with an AutoGen agent?

Use the mcpservertools helper from the autogen-ext package to load the server's endpoints. You then pass this tool list directly to your AssistantAgent constructor.

Equip your AutoGen agent teams with raw Martian telemetry and images to debate mission statuses and analyze raw planetary data.

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Connect NASA Mars — Rover Photos from the Red Planet MCP to AutoGen

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Setup NASA Mars — Rover Photos from the Red Planet with AutoGen

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Perplexity

Resolve mission data conflicts in AutoGen debates

The `get_mars_manifest` tool provides the ground truth mission timeline and active camera configurations for Curiosity, Opportunity, and Spirit. In an AutoGen MCP setup, your planning agent uses this tool to verify sol ranges before a retrieval agent attempts to download image payloads. If one agent proposes an invalid sol, the validation agent calls this tool to correct the plan. This collaborative debate prevents wasted API calls and keeps your multi-agent conversations focused on real data.

Coordinate multi-agent photo analysis using this MCP Server

The `get_mars_photos` and `get_mars_latest` tools retrieve raw image URLs filtered by camera types like MAST, CHEMCAM, or NAVCAM. Your AutoGen coordinator agent delegates these tools to specialized analyst agents that focus on specific instruments. One agent might pull hazard camera views while another gathers high-resolution mast shots. They then compare findings to compile a detailed report on Martian surface conditions.

Cross-verify historical dates with multi-agent consensus

The `get_mars_photos_by_date` tool fetches raw image records using standard Earth calendar dates instead of Martian sols. Your AutoGen agents use this tool to cross-reference historical data across all three rovers to build comparative planetary timelines. A researcher agent requests the data, a validator agent checks the output format, and a writer agent drafts the summary. This structural separation ensures that raw NASA telemetry is thoroughly processed before reaching the user.

Setup guide

Set up NASA Mars — Rover Photos from the Red Planet MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes NASA Mars — Rover Photos from the Red Planet tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

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

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="NASA Mars — Rover Photos from the Red Planet_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent NASA Mars — Rover Photos from the Red Planet data")
print(result.messages[-1].content)

Get your connection token →

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

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

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="NASA Mars — Rover Photos from the Red Planet_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent NASA Mars — Rover Photos from the Red Planet data")
    print(result.messages[-1].content)

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 NASA. 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 NASA Mars — Rover Photos from the Red Planet MCP in AutoGen

Use the `mcp_server_tools` helper from the `autogen-ext` package to load the server's endpoints. You then pass this tool list directly to your AssistantAgent constructor.

Yes, your agents share the tool definitions and can call them during their conversation. A coordinator agent might call `get_mars_manifest` while an analyst agent concurrently calls `get_mars_photos`.

Your agents debate which camera is best suited for the user's request. Once they agree, the executing agent calls `get_mars_photos` with the agreed camera parameter.

The API returns an empty list, which your validation agent can catch. It can then call `get_mars_manifest` to find the nearest active sol with valid imagery.

This server only transmits public rover names, camera filters, and sol dates to the NASA API. Your internal AutoGen agent conversations, system prompts, and local logs never leave your environment.

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