Can my agent perform semantic search across my collections?

Yes. Provide the vector embedding array in JSON format, and your agent will return the closest document matches along with their distance metrics. It is the perfect way to test your RAG (Retrieval-Augmented Generation) logic without complex scripts.

How can I verify the health of my self-hosted Chroma instance?

Simply ask your agent to check the heartbeat. The agent performs a nanosecond-level responsiveness test against your API nodes, confirming the physical database is active and reachable from the gateway.

I manage multiple tenants — how do I switch between them?

You can define the tenant and database names during the setup phase. If you need to switch often, you can update the credentials in the dashboard. The agent uses these values for all collection and document operations to ensure strict isolation.

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

Name: Chroma (Vector DB)
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 Chroma (Vector DB) 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="chroma_vector_db_agent",
    instruction=(
        "You help users interact with Chroma (Vector DB) "
        "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 Chroma (Vector DB) MCP Server

Connect your Chroma vector database to any AI agent and take full control of your semantic data through natural conversation.

Google ADK natively supports Chroma (Vector DB) 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 Collections — List all available collections and inspect their deep configuration and metadata
Semantic Search — Perform high-dimensional vector similarity searches to find relevant context for your LLM applications
Document Auditing — Count documents, peek at unstructured data segments, and retrieve specific records by ID
Instance Health — Monitor heartbeats and connectivity across Chroma Cloud or self-hosted instances
Tenant & Database Management — Switch between different tenants and databases to isolate your production and staging environments

The Chroma (Vector DB) 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 Chroma (Vector DB) to Google ADK via MCP

Follow these steps to integrate the Chroma (Vector DB) 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 Chroma (Vector DB) via MCP

Why Use Google ADK with the Chroma (Vector DB) MCP Server

Google ADK provides unique advantages when paired with Chroma (Vector DB) 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 Chroma (Vector DB)

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 Chroma (Vector DB) tools with BigQuery, Vertex AI, and Cloud Functions

Chroma (Vector DB) + Google ADK Use Cases

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

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

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

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

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

Chroma (Vector DB) MCP Tools for Google ADK (7)

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

check_heartbeat

Validate fundamental network availability against explicit Chroma API nodes

count_documents

Execute explicit structural tracking enumerating total document volumes

get_collection

Identify bounded logical settings configuring a specific Vector Collection block

get_documents

Retrieve exact physical documents and semantic context inside known arrays

list_collections

List all explicitly defined Vector Collections within a given tenant database

peek_documents

Extracts explicitly attached bounded preview of the Database limits

query_embeddings

Identify precise logical bounds matching high-dimensional semantic clustering

Example Prompts for Chroma (Vector DB) in Google ADK

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

"List all vector collections"

"Peek at the first 5 documents in 'knowledge-base'"

"Is the Chroma server alive?"

Troubleshooting Chroma (Vector DB) MCP Server with Google ADK

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

McpToolset not found

Update: pip install --upgrade google-adk

Chroma (Vector DB) + Google ADK FAQ

Common questions about integrating Chroma (Vector DB) 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.