Can the AI pinpoint the exact error in a failed Python data flow?

Yes. Upon discovering a FAILED execution with `list_flow_runs`, it uses `get_flow_run` to unpack the explicit metadata and stack trace, isolating exactly what task and line broke your ETL logic.

How does the agent find where a flow actually executes (compute layer)?

It investigates `list_deployments` and `list_work_pools`. This exposes the underlying compute binding, allowing the AI to tell you whether the workflow executed inside an ECS cluster, Kubernetes, or a local Docker agent.

Where do I retrieve the Workspace ID precisely?

From the Prefect Cloud URL. The format is `app.prefect.cloud/account/{AccountId}/workspace/{WorkspaceId}`. Copy the UUID strictly following the `/workspace/` path.

Prefect MCP Server for Google ADK 7 tools — connect in under 2 minutes

Name: Prefect
Availability: InStock
Author: Vinkius

google.github.io/adk-docs/tools/mcp-tools

Built by Vinkius GDPR 7 Tools SDK

Google Agent Development Kit (ADK) is Google's framework for building production AI agents. Add Prefect as an MCP tool provider through Vinkius and your ADK agents can call every tool with full schema introspection.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

from google.adk.agents import Agent
from google.adk.tools.mcp_tool import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import (
    StreamableHTTPConnectionParams,
)

# Your Vinkius token. get it at cloud.vinkius.com
mcp_tools = McpToolset(
    connection_params=StreamableHTTPConnectionParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
    )
)

agent = Agent(
    model="gemini-2.5-pro",
    name="prefect_agent",
    instruction=(
        "You help users interact with Prefect "
        "using 7 available tools."
    ),
    tools=[mcp_tools],
)

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Prefect MCP Server

Equip any AI agent with direct line-of-sight into your Prefect Cloud workspaces. Empower your LLMs to parse Python data pipelines, identify exactly why an ETL flow crashed, and audit underlying cloud infrastructure blocks conversational.

Google ADK natively supports Prefect as an MCP tool provider. declare Vinkius Edge URL and the framework handles discovery, validation, and execution automatically. Combine 7 tools with Gemini's long-context reasoning for complex multi-tool workflows, with production-ready session management and evaluation built in.

What you can do

Audit Pipelines & Runs — Ask the AI to fetch all list_flows and dissect their historical execution via list_flow_runs, identifying bottlenecks
Execution Breakdown — Command the agent to pull absolute tracing of a crashed workflow via get_flow_run to literally read the Python traceback
Infrastructure & Blocks — Let the agent audit secure list_blocks connections (AWS, GCP) binding your Prefect environments
Automations & Triggers — Instantly review list_automations dictating active webhook-based flow triggers

The Prefect MCP Server exposes 7 tools through the Vinkius. Connect it to Google ADK in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Prefect to Google ADK via MCP

Follow these steps to integrate the Prefect MCP Server with Google ADK.

Install Google ADK

Run pip install google-adk

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Create the agent

Save the code above and integrate into your ADK workflow

Explore tools

The agent will discover 7 tools from Prefect via MCP

Why Use Google ADK with the Prefect MCP Server

Google ADK provides unique advantages when paired with Prefect through the Model Context Protocol.

Google ADK natively supports MCP tool servers. declare a tool provider and the framework handles discovery, validation, and execution

Built on Gemini models, ADK provides long-context reasoning ideal for complex multi-tool workflows with Prefect

Production-ready features like session management, evaluation, and deployment come built-in. not bolted on

Seamless integration with Google Cloud services means you can combine Prefect tools with BigQuery, Vertex AI, and Cloud Functions

Prefect + Google ADK Use Cases

Practical scenarios where Google ADK combined with the Prefect MCP Server delivers measurable value.

Enterprise data agents: ADK agents query Prefect and cross-reference results with internal databases for comprehensive analysis

Multi-modal workflows: combine Prefect tool responses with Gemini's vision and language capabilities in a single agent

Automated compliance checks: schedule ADK agents to query Prefect regularly and flag policy violations or configuration drift

Internal tool platforms: build self-service agent platforms where teams connect their own MCP servers including Prefect

Prefect MCP Tools for Google ADK (7)

These 7 tools become available when you connect Prefect to Google ADK via MCP:

get_flow_run

Get complete contextual metadata, runtime limits, and specific variables tied to an executed Prefect Flow Run

list_automations

List all Cloud Automations mapping explicit webhook/event actions dictating real-time flow triggers

list_blocks

List all secure infrastructure Blocks defining Secrets, AWS paths, or GCP configurations directly in Prefect

list_deployments

List all active deployments representing scheduled or triggered physical workflow instances

list_flow_runs

List recent active, scheduled, or failed flow runs recording actual physical data pipelining limits

list_flows

List all engineered Python workflows registered natively on Prefect Cloud

list_work_pools

List all physical Work Pools acting as routing destinations for dynamically dispatched flow runs

Example Prompts for Prefect in Google ADK

Ready-to-use prompts you can give your Google ADK agent to start working with Prefect immediately.

"Did the 'DB Sync Hourly' flow experience any failed runs today? Provide the traceback."

"Show me what infrastructure is tied to our 'Production Data Warehouse' deployment."

"List all active automations tracking webhook payloads."

Troubleshooting Prefect MCP Server with Google ADK

Common issues when connecting Prefect to Google ADK through the Vinkius, and how to resolve them.

McpToolset not found

Update: pip install --upgrade google-adk

Prefect + Google ADK FAQ

Common questions about integrating Prefect MCP Server with Google ADK.

How does Google ADK connect to MCP servers?

Import the MCP toolset class and pass the server URL. ADK discovers and registers all tools automatically, making them available to your agent's tool-use loop.

Can ADK agents use multiple MCP servers?

Yes. Declare multiple MCP tool providers in your agent configuration. ADK merges all tool schemas and the agent can call tools from any server in a single turn.

Which Gemini models work best with MCP tools?

Gemini 2.0 Flash and Pro models both support function calling required for MCP tools. Flash is recommended for latency-sensitive use cases, Pro for complex reasoning.