Can my AI agent do similarity searches across vector embeddings?

Yes. Ask the agent to find documents related to a specific vector array in your target collection. The agent natively passes the numerical array directly into Astra DB's ANN engine, instantly returning the top semantically matched documents.

Does this work like standard Cassandra or is it strictly vector-only?

Both. While it excels at vector searches, the integration fully supports standard NoSQL JSON documents. You can insert, find, count, and delete standard text documents using strict JSON filters just like regular database operations.

Can I switch seamlessly between different collections?

Absolutely. Just mention the target collection by name in your prompts, and the agent adapts flawlessly. If you forget which ones exist, you can instruct it to list all available collections within your default namespace anytime.

DataStax Astra DB Vector MCP Server for Google ADK 7 tools — connect in under 2 minutes

Name: DataStax Astra DB Vector
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 DataStax Astra DB Vector 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="datastax_astra_db_vector_agent",
    instruction=(
        "You help users interact with DataStax Astra DB Vector "
        "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 DataStax Astra DB Vector MCP Server

Connect your Astra DB instance to any AI agent and seamlessly execute complex NoSQL and vector searches through natural conversation. Built on DataStax's powerful engine, this integration gives your AI agents full contextual access to your unstructured data layer.

Google ADK natively supports DataStax Astra DB Vector 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

Vector Search — Perform Approximate Nearest Neighbor (ANN) similarity searches directly within your chat to find semantically related documents
Document Management — Insert, discover, read, count, or delete exact NoSQL JSON documents across your active collections
Collections — List and browse available tables and collections currently active in your configured Astra DB namespace

The DataStax Astra DB Vector 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 DataStax Astra DB Vector to Google ADK via MCP

Follow these steps to integrate the DataStax Astra DB Vector 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 DataStax Astra DB Vector via MCP

Why Use Google ADK with the DataStax Astra DB Vector MCP Server

Google ADK provides unique advantages when paired with DataStax Astra DB Vector 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 DataStax Astra DB Vector

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 DataStax Astra DB Vector tools with BigQuery, Vertex AI, and Cloud Functions

DataStax Astra DB Vector + Google ADK Use Cases

Practical scenarios where Google ADK combined with the DataStax Astra DB Vector MCP Server delivers measurable value.

Enterprise data agents: ADK agents query DataStax Astra DB Vector and cross-reference results with internal databases for comprehensive analysis

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

Automated compliance checks: schedule ADK agents to query DataStax Astra DB Vector regularly and flag policy violations or configuration drift

Internal tool platforms: build self-service agent platforms where teams connect their own MCP servers including DataStax Astra DB Vector

DataStax Astra DB Vector MCP Tools for Google ADK (7)

These 7 tools become available when you connect DataStax Astra DB Vector to Google ADK via MCP:

count_documents

Count total documents in an Astra DB collection

delete_document

Delete a document from an Astra DB collection

find_documents

Useful for standard NoSQL document retrieval. Find documents in an Astra DB collection

find_one_document

Find a single document in an Astra DB collection

insert_document

The document can include a pre-generated $vector key for embedding searches. Insert a new document into an Astra DB collection

list_collections

List all collections in the Astra DB namespace

vector_search

Perform an ANN vector similarity search on an Astra DB collection

Example Prompts for DataStax Astra DB Vector in Google ADK

Ready-to-use prompts you can give your Google ADK agent to start working with DataStax Astra DB Vector immediately.

"List the collections available in my Astra DB."

"Count the documents inside the 'products' collection."

"Find documents matching this filter in 'user_vectors': {"city": "San Francisco"}."

Troubleshooting DataStax Astra DB Vector MCP Server with Google ADK

Common issues when connecting DataStax Astra DB Vector to Google ADK through the Vinkius, and how to resolve them.

McpToolset not found

Update: pip install --upgrade google-adk

DataStax Astra DB Vector + Google ADK FAQ

Common questions about integrating DataStax Astra DB Vector 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.