How to Use the KeepTrack Space Intelligence MCP in Mastra AI

Q: How do I initialize KeepTrack Space Intelligence in Mastra AI?

Use new MCPClient() and pass the server URL in your configuration block. Mastra automatically detects whether to use Streamable HTTP or SSE transport.

Q: Can Mastra AI retry KeepTrack Space Intelligence queries if they fail?

Yes. You can configure exponential backoff on any step. If getsatellitedetails times out, the workflow engine automatically attempts the call again.

Q: Does the framework support human approval for orbital tracking actions?

Yes. You can enable requireToolApproval for specific tools. The workflow will pause and wait for manual sign-off before running the query.

Q: How do I pass the KeepTrack Space Intelligence tools to my Mastra AI agent?

Call mcpClient.listTools() and spread the results into your agent's tool array. The agent will immediately understand how to query the MCP Server.

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Connect KeepTrack Space Intelligence MCP to Mastra AI

Create your Vinkius account to connect KeepTrack Space Intelligence to Mastra AI 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 Mastra AI

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Automate space launch monitoring

The `get_recent_space_launches` tool feeds directly into Mastra AI workflows. You can build an agent that wakes up every morning, checks the latest orbital flights, and routes the data based on payload types. If the tool hits a rate limit, Mastra handles the exponential backoff automatically. Your workflow won't crash just because the tracking network had a sudden latency spike during a high-profile launch.

Build conditional satellite lookups

The `search_satellites` tool lets your agent find specific hardware before executing deeper queries. Mastra's workflow engine takes the search results and branches logic based on what it finds in orbit. If the search returns a match, the agent moves to the next step. When the query fails or returns empty, the framework can retry with a looser search term or notify a human operator before proceeding.

Connect the MCP Server to complex pipelines

The `get_satellite_details` tool pulls down exact orbital parameters for detailed analysis. Your Mastra AI agent grabs this data and feeds it into downstream tasks like collision risk assessment or coverage mapping. You spread the output of `mcpClient.listTools()` right into your agent's definition. This MCP Server handles the transport layer, letting you focus on the actual logic of the aerospace workflow.

Setup guide

Set up KeepTrack Space Intelligence MCP in Mastra AI

Prerequisites

Node.js 18+ and a TypeScript project
@mastra/mcp + @mastra/core packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run npm install @mastra/mcp @mastra/core plus your preferred model provider (e.g. @ai-sdk/openai).
2

Configure the MCPClient
Create an MCPClient with your Vinkius endpoint as a URL object. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Discover and inject tools
Call mcpClient.listTools() and spread the result into your agent's tools object. All KeepTrack Space Intelligence tools become native Mastra tools.
4

Run with any model
Swap openai("gpt-4o") for any AI SDK-compatible provider. Call agent.generate() and the agent routes tool calls through MCP automatically.

agent.ts

import { MCPClient } from "@mastra/mcp";
import { Agent } from "@mastra/core/agent";
import { openai } from "@ai-sdk/openai";

const mcpClient = new MCPClient({
  id: "keeptrack-space-intelligence-mcp-client",
  servers: {
    "keeptrack-space-intelligence-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

const agent = new Agent({
  name: "KeepTrack Space Intelligence Agent",
  model: openai("gpt-4o"),
  instructions: "You have access to KeepTrack Space Intelligence tools.",
  tools: {
    ...(await mcpClient.listTools()),
  },
});

const result = await agent.generate(
  "List recent KeepTrack Space Intelligence transactions"
);
console.log(result.text);

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Common questions about KeepTrack Space Intelligence MCP in Mastra AI

Use `new MCPClient()` and pass the server URL in your configuration block. Mastra automatically detects whether to use Streamable HTTP or SSE transport.

Yes. You can configure exponential backoff on any step. If `get_satellite_details` times out, the workflow engine automatically attempts the call again.

Yes. You can enable `requireToolApproval` for specific tools. The workflow will pause and wait for manual sign-off before running the query.

Call `mcpClient.listTools()` and spread the results into your agent's tool array. The agent will immediately understand how to query the MCP Server.

The system only sees the specific payload names and satellite IDs you pass to it. It does not track your Mastra AI execution state or store the downstream logic of your workflows. The MCP Server isolates every request.

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