How to Use the KeepTrack Space Intelligence MCP in AutoGen

Build multi-agent AutoGen debates to analyze orbital telemetry and satellite launch data.

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Connect KeepTrack Space Intelligence MCP to AutoGen

Create your Vinkius account to connect KeepTrack Space Intelligence to AutoGen 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 KeepTrack Space Intelligence with AutoGen

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Debate orbital safety with multi-agent workflows

The `get_satellite_details` tool on this MCP Server provides the raw telemetry that your AutoGen agents use to debate orbital safety and collision risks. A tracking agent pulls the coordinates while a safety agent analyzes the risk, converging on a consensus before alerting operators. This cooperative analysis prevents single-agent errors when interpreting complex orbital parameters. The agents negotiate and cross-verify the data before presenting the final assessment.

Coordinate launch assessments in AutoGen

`get_recent_space_launches` feeds recent orbital events into an AutoGen conversation thread where specialized agents analyze the payloads. One agent evaluates the launch trajectory while another checks for potential orbital interference. This MCP Server integration allows you to build multi-step verification loops. The agents discuss the launch details and automatically trigger further tracking queries if they spot a high-risk trajectory.

Automate space catalog search debates

`search_satellites` allows your agents to locate specific space assets during an ongoing discussion about orbital congestion. The agents use the search results to dynamically adjust their analysis of active debris. Because AutoGen supports multi-agent negotiation, one agent can challenge another's search parameters if a query returns too many results. This ensures your automated tracking pipelines remain precise and focused on relevant targets.

Setup guide

Set up KeepTrack Space Intelligence 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 KeepTrack Space Intelligence 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="KeepTrack Space Intelligence_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent KeepTrack Space Intelligence data")
print(result.messages[-1].content)

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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="KeepTrack Space Intelligence_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent KeepTrack Space Intelligence data")
    print(result.messages[-1].content)

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Common questions about KeepTrack Space Intelligence MCP in AutoGen

The agents share tool outputs through the group chat history. When one agent calls a tool, the resulting satellite telemetry is visible to all other agents in the conversation.

Yes, you pass the tools list specifically to the AssistantAgent constructor for the agent responsible for orbital analysis.

The agents use their built-in debate mechanism to compare the search results against known orbital parameters until they reach a consensus.

Multi-agent collaboration allows for deeper validation of telemetry data, where one agent queries the tools and another verifies the orbital calculations.

Yes, all orbital debris queries and satellite telemetry requests are routed through an encrypted, ephemeral connection. No tracking requests are logged or stored outside your active AutoGen session.

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