Can I train a machine learning model using SQL through my agent?

Yes. Use the `execute_sql_query` tool with the 'CREATE MODEL' statement. Your agent will dispatch the command to MindsDB, which will automatically handle the data processing and training of your predictor asynchronously.

How do I connect an external database like PostgreSQL to MindsDB using the agent?

The `execute_sql_query` tool supports the 'CREATE DATABASE' syntax. You can command your agent to link a new data source by providing the connection parameters, allowing MindsDB to query your existing data natively.

Can my agent retrieve the status of an ongoing model training?

Absolutely. Use the `get_model` tool by providing the model name and project. Your agent will report the current training state, accuracy metrics, and any errors encountered during the AI generation process.

MindsDB (AI Database & Predictors) MCP Server for Google ADK 6 tools — connect in under 2 minutes

Name: MindsDB (AI Database & Predictors)
Availability: InStock
Author: Vinkius

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

Built by Vinkius GDPR 6 Tools SDK

Google Agent Development Kit (ADK) is Google's framework for building production AI agents. Add MindsDB (AI Database & Predictors) 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

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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="mindsdb_ai_database_predictors_agent",
    instruction=(
        "You help users interact with MindsDB (AI Database & Predictors) "
        "using 6 available tools."
    ),
    tools=[mcp_tools],
)

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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 MindsDB (AI Database & Predictors) MCP Server

Connect your MindsDB instance to any AI agent and take full control of your machine learning workflows, automated predictions, and data integrations through natural SQL-based conversation.

Google ADK natively supports MindsDB (AI Database & Predictors) as an MCP tool provider. declare Vinkius Edge URL and the framework handles discovery, validation, and execution automatically. Combine 6 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

Predictive Orchestration — Execute arbitrary SQL statements to trigger automated machine learning commands, including 'CREATE MODEL' and 'SELECT ... PREDICT' directly from your agent
Model Lifecycle Audit — List trained AI tables (models) across your projects and retrieve detailed meta-features tracking generation progress or internal accuracy metrics
Data Source Integration — Enumerate external databases connected through MindsDB (e.g., PostgreSQL, Snowflake, ClickHouse) to audit your data pipeline boundaries securely
Virtual View Management — List virtual data views and SQL structural mappings that act as proxy tables for complex data transformation logic
Cluster Diagnostics — Retrieve active cluster status and version statistics to verify the availability and health of your MindsDB environment
Advanced SQL Execution — Run sophisticated queries combining scalar data with ML predictions to fetch literal insights across any schema entity natively

The MindsDB (AI Database & Predictors) MCP Server exposes 6 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 MindsDB (AI Database & Predictors) to Google ADK via MCP

Follow these steps to integrate the MindsDB (AI Database & Predictors) 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 6 tools from MindsDB (AI Database & Predictors) via MCP

Why Use Google ADK with the MindsDB (AI Database & Predictors) MCP Server

Google ADK provides unique advantages when paired with MindsDB (AI Database & Predictors) 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 MindsDB (AI Database & Predictors)

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 MindsDB (AI Database & Predictors) tools with BigQuery, Vertex AI, and Cloud Functions

MindsDB (AI Database & Predictors) + Google ADK Use Cases

Practical scenarios where Google ADK combined with the MindsDB (AI Database & Predictors) MCP Server delivers measurable value.

Enterprise data agents: ADK agents query MindsDB (AI Database & Predictors) and cross-reference results with internal databases for comprehensive analysis

Multi-modal workflows: combine MindsDB (AI Database & Predictors) tool responses with Gemini's vision and language capabilities in a single agent

Automated compliance checks: schedule ADK agents to query MindsDB (AI Database & Predictors) regularly and flag policy violations or configuration drift

Internal tool platforms: build self-service agent platforms where teams connect their own MCP servers including MindsDB (AI Database & Predictors)

MindsDB (AI Database & Predictors) MCP Tools for Google ADK (6)

These 6 tools become available when you connect MindsDB (AI Database & Predictors) to Google ADK via MCP:

execute_sql_query

E.g: CREATE DATABASE, SELECT ... WHERE, CREATE MODEL ... PREDICT. Wrap logic safely. VERY IMPORTANT: queries returning a large number of rows MUST be explicitly wrapped in a LIMIT statement or risk hitting context overflow. Execute arbitrary SQL statements bounding MindsDB elements

get_model

Get an explicitly trained AI prediction engine

get_status

Acts as a ping tracer returning valid core version/health specs. Get active cluster diagnostic and version statistics

list_databases

List external databases connected through MindsDB

list_models

Use when checking which algorithms are ready to query predictions. List trained AI tables (models) available in a project

list_views

List virtual data views stored inside a target project

Example Prompts for MindsDB (AI Database & Predictors) in Google ADK

Ready-to-use prompts you can give your Google ADK agent to start working with MindsDB (AI Database & Predictors) immediately.

"List all ML models in the 'mindsdb' project"

"Execute SQL: SELECT price, price_explain FROM mindsdb.home_price_predictor WHERE sqft = 2500"

"Show me all connected databases in my MindsDB instance"

Troubleshooting MindsDB (AI Database & Predictors) MCP Server with Google ADK

Common issues when connecting MindsDB (AI Database & Predictors) to Google ADK through the Vinkius, and how to resolve them.

McpToolset not found

Update: pip install --upgrade google-adk

MindsDB (AI Database & Predictors) + Google ADK FAQ

Common questions about integrating MindsDB (AI Database & Predictors) 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.