Vald MCP Server for Google ADK 6 tools — connect in under 2 minutes
Google Agent Development Kit (ADK) is Google's framework for building production AI agents. Add Vald as an MCP tool provider through the Vinkius and your ADK agents can call every tool with full schema introspection.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
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="vald_agent",
instruction=(
"You help users interact with Vald "
"using 6 available tools."
),
tools=[mcp_tools],
)
* 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 Vald MCP Server
Connect your Vald cluster to any AI agent and bring distributed, high-speed approximate nearest neighbor (ANN) vector search directly to your conversational workflow.
Google ADK natively supports Vald as an MCP tool provider — declare the 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
- Vector Search — Perform rapid semantic searches across millions of embedded data points just by querying the agent.
- Data Ingestion — Insert new high-dimensional vectors directly into the Vald index for instant future retrievability in your RAG pipelines.
- Index Management — Update the vector representations of existing records or permanently remove specific items from the engine cluster.
- Cluster Health — Automatically retrieve operational system information, agent health statuses, and node details regarding your active Vald deployment.
The Vald 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 Vald to Google ADK via MCP
Follow these steps to integrate the Vald 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 Vald via MCP
Why Use Google ADK with the Vald MCP Server
Google ADK provides unique advantages when paired with Vald 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 Vald
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 Vald tools with BigQuery, Vertex AI, and Cloud Functions
Vald + Google ADK Use Cases
Practical scenarios where Google ADK combined with the Vald MCP Server delivers measurable value.
Enterprise data agents: ADK agents query Vald and cross-reference results with internal databases for comprehensive analysis
Multi-modal workflows: combine Vald tool responses with Gemini's vision and language capabilities in a single agent
Automated compliance checks: schedule ADK agents to query Vald regularly and flag policy violations or configuration drift
Internal tool platforms: build self-service agent platforms where teams connect their own MCP servers including Vald
Vald MCP Tools for Google ADK (6)
These 6 tools become available when you connect Vald to Google ADK via MCP:
delete_vector
This action is irreversible. Permanently removes a vector from the Vald index
get_engine_info
Retrieves operational information and health of the Vald engine
get_vector_details
Retrieves the raw vector data for a specific ID
insert_vector
Provide a unique ID and the vector as a JSON array. Inserts a new vector into the Vald index
search_vectors
Provide a query vector as a JSON array of floats. Performs a nearest neighbor vector similarity search
update_vector
Provide the existing ID and new vector array. Updates an existing vector in the Vald index
Example Prompts for Vald in Google ADK
Ready-to-use prompts you can give your Google ADK agent to start working with Vald immediately.
"Is the Vald cluster operational right now?"
"Can you check the vector details stored for UUID 'user-profile-89'?"
"Update the existing item 'context-fragment-12' with this new 1536-dimensional array: [0.38, -0.19, 0...]."
Troubleshooting Vald MCP Server with Google ADK
Common issues when connecting Vald to Google ADK through the Vinkius, and how to resolve them.
McpToolset not found
pip install --upgrade google-adkVald + Google ADK FAQ
Common questions about integrating Vald MCP Server with Google ADK.
How does Google ADK connect to MCP servers?
Can ADK agents use multiple MCP servers?
Which Gemini models work best with MCP tools?
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Connect Vald to Google ADK
Get your token, paste the configuration, and start using 6 tools in under 2 minutes. No API key management needed.