Can my agent perform high-speed vector similarity searches?

Yes. Provide the database, table, and the vector embedding array in JSON format. The agent uses ClickHouse's native distance functions (cosine or L2) to return the closest matches, leveraging ClickHouse's industry-leading OLAP performance.

Can I execute arbitrary SQL commands directly through the agent?

Absolutely. The 'execute_sql' tool allows you to push any valid ClickHouse SQL (DML, DDL, or SELECT) to your cluster. This is perfect for managing tables, updating records, or generating custom analytical reports on the fly.

How do I check if my ClickHouse instance supports HNSW indices?

Ask your agent to get the version details. The agent checks your ClickHouse build and identifies exactly which capability branches are active, confirming if advanced vector features like HNSW support are available in your runtime environment.

ClickHouse (Vector Search) MCP Server for Google ADK 7 tools — connect in under 2 minutes

Name: ClickHouse (Vector Search)
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 ClickHouse (Vector Search) as an MCP tool provider through the 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="clickhouse_vector_search_agent",
    instruction=(
        "You help users interact with ClickHouse (Vector Search) "
        "using 7 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 ClickHouse (Vector Search) MCP Server

Connect your ClickHouse cluster to any AI agent and take full control of your analytical and vector data through natural conversation.

Google ADK natively supports ClickHouse (Vector Search) as an MCP tool provider — declare the 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

Schema Management — List databases and tables, and inspect deep column schemas including specialized Array(Float32) vector types
SQL Execution — Push arbitrary DML, DDL, or SELECT queries to your cluster to manage data and generate real-time reports
Vector Search — Identify mathematical distance traces using cosineDistance or L2Distance metrics for high-dimensional semantic search
Cluster Monitoring — Extract internal structural states, row counts, and compression ratios to audit cluster health
Capability Auditing — Check instance versions and binary limits to identify exact capability branches like HNSW support

The ClickHouse (Vector Search) 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 ClickHouse (Vector Search) to Google ADK via MCP

Follow these steps to integrate the ClickHouse (Vector Search) 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 ClickHouse (Vector Search) via MCP

Why Use Google ADK with the ClickHouse (Vector Search) MCP Server

Google ADK provides unique advantages when paired with ClickHouse (Vector Search) 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 ClickHouse (Vector Search)

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 ClickHouse (Vector Search) tools with BigQuery, Vertex AI, and Cloud Functions

ClickHouse (Vector Search) + Google ADK Use Cases

Practical scenarios where Google ADK combined with the ClickHouse (Vector Search) MCP Server delivers measurable value.

Enterprise data agents: ADK agents query ClickHouse (Vector Search) and cross-reference results with internal databases for comprehensive analysis

Multi-modal workflows: combine ClickHouse (Vector Search) tool responses with Gemini's vision and language capabilities in a single agent

Automated compliance checks: schedule ADK agents to query ClickHouse (Vector Search) regularly and flag policy violations or configuration drift

Internal tool platforms: build self-service agent platforms where teams connect their own MCP servers including ClickHouse (Vector Search)

ClickHouse (Vector Search) MCP Tools for Google ADK (7)

These 7 tools become available when you connect ClickHouse (Vector Search) to Google ADK via MCP:

describe_table

Perform structural extraction of properties driving active column schemas

execute_sql

Provision a highly-available SQL execution pushing arbitrary arbitrary DML/DDL or SELECTs

get_table_stats

Extracts explicitly attached internal structural states pulling cluster health

get_version

g. HNSW support). Identify precise active cluster limits spanning the execution runtime

list_databases

Identify bounded logical arrays managing top-level ClickHouse schemas

list_tables

Retrieve the exact structural matching verifying table limits inside a database

vector_search

Identify explicit mathematical distance traces routing Vector Embeddings

Example Prompts for ClickHouse (Vector Search) in Google ADK

Ready-to-use prompts you can give your Google ADK agent to start working with ClickHouse (Vector Search) immediately.

"List all databases in my ClickHouse cluster"

"Find the top 5 most similar records in table 'embeddings' using this vector: [0.1, 0.5, -0.2]"

"Get table stats for 'analytics_prod.sales_data'"

Troubleshooting ClickHouse (Vector Search) MCP Server with Google ADK

Common issues when connecting ClickHouse (Vector Search) to Google ADK through the Vinkius, and how to resolve them.

McpToolset not found

Update: pip install --upgrade google-adk

ClickHouse (Vector Search) + Google ADK FAQ

Common questions about integrating ClickHouse (Vector Search) 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.