How to Use the AgentOps (Agent Telemetry and Monitoring) MCP in Google ADK

Q: How do I connect the AgentOps (Agent Telemetry and Monitoring) MCP Server to Google ADK?

Use pip install google-adk. Create an McpToolset with your Vinkius endpoint and pass it to your LlmAgent.

Q: Can I filter the AgentOps (Agent Telemetry and Monitoring) tools exposed to Google ADK?

You can. Pass a toolnames list to the toolset constructor to restrict access to specific functions like trace fetching.

Pipe agent telemetry straight into your Gemini context using Google ADK.

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Connect AgentOps (Agent Telemetry and Monitoring) MCP to Google ADK

Create your Vinkius account to connect AgentOps (Agent Telemetry and Monitoring) to Google ADK 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 AgentOps (Agent Telemetry and Monitoring) with Google ADK

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Perplexity

Google ADK trace analysis

Gemini models can ingest massive amounts of data. Using the `get_trace` tool, your agent pulls full execution histories from AgentOps into that 1M+ token context window for deep analysis. You spot patterns across thousands of interactions quickly. The agent reads the raw trace logs and correlates them with your existing BigQuery datasets to find performance bottlenecks.

Extract span details

Sometimes a single step ruins the entire workflow. The `get_span` tool isolates specific actions, giving your Gemini agent the exact parameters used during that moment. Fixing enterprise agents happens faster this way. The agent examines the failed span and suggests code fixes based on the surrounding context stored in Vertex AI.

Track metrics via MCP Server

High-level monitoring keeps your cloud infrastructure healthy. Calling `get_trace_metrics` pulls execution times and token counts directly into your Google Cloud environment. Developers use `get_project` to grab the overarching project state. Your reporting agent then formats these metrics and pushes them to your internal dashboards.

Setup guide

Set up AgentOps (Agent Telemetry and Monitoring) MCP in Google ADK

Prerequisites

Python 3.10+ installed
google-adk package (pip install google-adk)
Active Vinkius subscription with a valid endpoint token

1

Install Google ADK

Run pip install google-adk to install the Agent Development Kit. MCP support is included via the McpToolset class.
2

Connect via SSE transport

Use McpToolset.from_server() with SseServerParams pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create an LlmAgent

Pass the returned mcp_tools list directly to LlmAgent(tools=mcp_tools). The ADK maps each MCP tool to a native Gemini function call — no manual schema definitions required.
4

Run with any Gemini model

The agent works with any Gemini model (gemini-2.0-flash, gemini-2.5-pro, etc.). Copy the full example on the right to get started with AgentOps (Agent Telemetry and Monitoring) tools in your ADK agent.

agent.py

from google.adk.agents import LlmAgent
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import SseServerParams

# Connect to the MCP via SSE
mcp_tools, exit_stack = await McpToolset.from_server(
    connection_params=SseServerParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    )
)

# Create your agent with auto-discovered tools
agent = LlmAgent(
    name="AgentOps (Agent Telemetry and Monitoring)_agent",
    model="gemini-2.0-flash",
    instruction="You have access to AgentOps (Agent Telemetry and Monitoring) tools via MCP.",
    tools=mcp_tools,
)

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Common questions about AgentOps (Agent Telemetry and Monitoring) MCP in Google ADK

Use `pip install google-adk`. Create an `McpToolset` with your Vinkius endpoint and pass it to your `LlmAgent`.

You can. Pass a `tool_names` list to the toolset constructor to restrict access to specific functions like trace fetching.

Yes. You can pull massive trace histories and let Gemini analyze the entire dataset in one pass.

Vinkius manages the auth layer. You only need to provide the single endpoint token when setting up the HTTP transport.

Your spans and trace metrics process inside an ephemeral V8 Isolate. The sandbox destroys all memory after the connection drops, keeping your enterprise telemetry private.

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