How to Use the Apidog MCP in Google ADK

Q: How do I limit which Apidog MCP tools my Google ADK agent can see?

You pass an optional toolnames filter when initializing your McpToolset. This restricts the agent to specific operations, like only allowing it to list endpoints.

Q: Can Gemini write BigQuery schemas directly from Apidog data?

Yes, by fetching schemas with getendpoint. The agent parses the properties and translates them into BigQuery table definitions automatically.

Give your Google ADK enterprise agents direct access to Apidog schemas for long-context Gemini reasoning.

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Connect Apidog MCP to Google ADK

Create your Vinkius account to connect Apidog 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 Apidog with Google ADK

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Feed raw specs into Gemini's million-token context

`export_openapi` pulls your entire Apidog API specification into a single JSON dump. Because Google ADK runs on Gemini's massive context window, you can dump the whole spec directly into the prompt. Your agent analyzes complex multi-step API chains without running out of memory. This lets the model plan intricate data pipelines that connect your cloud databases to external endpoints.

Map Google ADK endpoints to BigQuery pipelines

`list_endpoints` outputs every route defined in your Apidog project so your Google ADK agent can map them. You can write scripts where Gemini identifies data sources and targets. Combine this with `get_endpoint` to extract precise payloads. Your MCP agent reads the schema, maps it to BigQuery tables, and generates SQL load jobs.

Discover schemas for Vertex AI tuning

`list_schemas` returns the data models and DTOs defined inside your Apidog workspace. This gives your agent a dictionary of your enterprise data structures. Using these schemas, Google ADK can format training data for Vertex AI models. You ensure that fine-tuned models output payloads that align perfectly with your live production APIs.

Setup guide

Set up Apidog 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 Apidog 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="Apidog_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Apidog tools via MCP.",
    tools=mcp_tools,
)

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Common questions about Apidog MCP in Google ADK

Yes, Google ADK supports both Stdio and HTTP transports. You configure `StreamableHttpServerParameters` with your Vinkius endpoint to connect the agent.

You pass an optional `tool_names` filter when initializing your `McpToolset`. This restricts the agent to specific operations, like only allowing it to list endpoints.

Static files drift, but this MCP Server queries your live workspace dynamically. Your Gemini agents always work with the absolute latest API specs without manual updates.

Yes, by fetching schemas with `get_endpoint`. The agent parses the properties and translates them into BigQuery table definitions automatically.

Your API designs and credentials pass through a zero-trust, ephemeral proxy. We do not store your OpenAPI specs or workspace tokens on disk.

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