How to Use the AppDynamics (Application Performance Monitor API) MCP in Mastra AI

Q: How do I integrate AppDynamics (Application Performance Monitor API) with a Mastra AI agent?

Install @mastra/mcp and instantiate the MCPClient with your Vinkius URL. Then, just call mcpClient.listTools() and spread the result into your agent's tool configuration. Mastra handles the rest.

Q: How does Mastra AI use the AppDynamics (Application Performance Monitor API) tools for conditional logic?

You can base your workflow's if/then branches on the output of any tool. For example, if listhealthruleviolations returns a list with a length greater than zero, then you can execute diagnostic steps using getmetricdata and listsnapshots.

Build resilient, multi-step SRE workflows for AppDynamics. Automate incident response and diagnostics with Mastra AI's workflow engine.

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Connect AppDynamics (Application Performance Monitor API) MCP to Mastra AI

Create your Vinkius account to connect AppDynamics (Application Performance Monitor API) 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 AppDynamics (Application Performance Monitor API) with Mastra AI

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Chain Diagnostics into Workflows

This isn't just about fetching data; it's about building intelligent sequences. A Mastra AI workflow can `list_health_rule_violations`, and for each violation, automatically trigger a call to `get_metric_data` for the affected application and node. You can add conditional logic. If CPU metrics are high, the workflow can then use `list_snapshots` to find the most expensive transactions during that time. Mastra's engine connects these steps into a single, automated diagnostic run.

Reliable Health Rule Deployment with Mastra AI

Use Mastra AI to build a bulletproof process for managing AppDynamics configurations. A workflow can `export_health_rules` from a primary application, then use a loop to `import_health_rules` into a dozen other apps. Mastra's built-in retry logic is key here. If an import fails for one application, it won't stop the whole process. It will retry with backoff, log the failure, and continue with the rest, ensuring your deployment is as complete as possible.

Create Proactive Monitoring Agents

Go beyond simple alerts. A Mastra AI agent can run on a schedule, using `list_business_transactions` to check for new, untracked endpoints and `list_custom_match_rules` to see if they're configured correctly. If the agent finds a mismatch, it can trigger another workflow. For instance, it could `create_event` in AppDynamics to flag the unmonitored transaction for a developer to review. This MCP server provides the tools to turn monitoring into a proactive process.

Setup guide

Set up AppDynamics (Application Performance Monitor API) 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 AppDynamics (Application Performance Monitor API) 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: "appdynamics-application-performance-monitor-api-mcp-client",
  servers: {
    "appdynamics-application-performance-monitor-api-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

const agent = new Agent({
  name: "AppDynamics (Application Performance Monitor API) Agent",
  model: openai("gpt-4o"),
  instructions: "You have access to AppDynamics (Application Performance Monitor API) tools.",
  tools: {
    ...(await mcpClient.listTools()),
  },
});

const result = await agent.generate(
  "List recent AppDynamics (Application Performance Monitor API) transactions"
);
console.log(result.text);

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Common questions about AppDynamics (Application Performance Monitor API) MCP in Mastra AI

Install `@mastra/mcp` and instantiate the `MCPClient` with your Vinkius URL. Then, just call `mcpClient.listTools()` and spread the result into your agent's tool configuration. Mastra handles the rest.

Absolutely. That's a core Mastra AI feature. Your workflow can call the `create_event` tool, and if it fails, Mastra's engine can automatically retry the call a few times before escalating.

You can base your workflow's `if/then` branches on the output of any tool. For example, if `list_health_rule_violations` returns a list with a length greater than zero, then you can execute diagnostic steps using `get_metric_data` and `list_snapshots`.

It's all about resilience and state management. Mastra AI provides automatic retries, conditional branching, and a proper workflow engine, so you're not just running commands—you're running a robust, stateful automation that can handle failures.

Vinkius ensures your data, like application metric data and user lists, never leaves a secure context. Each request runs in its own V8 isolate sandbox which is destroyed immediately after. Your auth token is the only key, and Vinkius doesn't persist any of the data passing through.

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