Supabase Vector MCP Server for Google ADK 7 tools — connect in under 2 minutes
Google Agent Development Kit (ADK) is Google's framework for building production AI agents. Add Supabase Vector as an MCP tool provider through the Vinkius and your ADK agents can call every tool with full schema introspection.
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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="supabase_vector_agent",
instruction=(
"You help users interact with Supabase Vector "
"using 7 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 Supabase Vector MCP Server
Integrate the powerful AI-native PostgreSQL extensions of Supabase Vector straight into your conversational LLM workflows. By authenticating your environment natively with the service_role key, your AI assistant bypasses row-level security constraints to operate as an unrestricted database administrator. Perform advanced similarity searches using the pgvector extension, parse and manipulate multi-dimensional embeddings, and execute foundational CRUD operations via simple natural language commands. Streamline RAG (Retrieval-Augmented Generation) setups and semantic engineering directly, avoiding the need for external dashboards or manual SQL querying.
Google ADK natively supports Supabase Vector 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
- Semantic Vector Matching — Seamlessly query unstructured contextual similarities performing embedding comparisons by executing
match_vectorsutilizing custom postgres RPC parameters locally. - Database Structural Interaction — Systematically browse schema availability utilizing
list_tablesand extract specific data arrays effortlessly throughquery_table_rows. - Content State Manipulations — Seamlessly orchestrate data inputs invoking
insert_table_rowsor explicitly clear legacy assignments logically mapping identifiers withdelete_table_rows. - Custom Functional Logic — Launch sophisticated PL/pgSQL algorithms statically configured in your Supabase backend directly with
call_postgres_function.
The Supabase 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 Supabase Vector to Google ADK via MCP
Follow these steps to integrate the Supabase 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 Supabase Vector via MCP
Why Use Google ADK with the Supabase Vector MCP Server
Google ADK provides unique advantages when paired with Supabase 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 Supabase 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 Supabase Vector tools with BigQuery, Vertex AI, and Cloud Functions
Supabase Vector + Google ADK Use Cases
Practical scenarios where Google ADK combined with the Supabase Vector MCP Server delivers measurable value.
Enterprise data agents: ADK agents query Supabase Vector and cross-reference results with internal databases for comprehensive analysis
Multi-modal workflows: combine Supabase Vector tool responses with Gemini's vision and language capabilities in a single agent
Automated compliance checks: schedule ADK agents to query Supabase 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 Supabase Vector
Supabase Vector MCP Tools for Google ADK (7)
These 7 tools become available when you connect Supabase Vector to Google ADK via MCP:
call_postgres_function
Calls a custom Postgres function (RPC) with parameters
delete_table_rows
This action is irreversible. Deletes rows from a table based on a column value
get_table_row
Retrieves a specific row by matching a column value
insert_table_rows
Provide a JSON array of row objects. Inserts new rows into a specific table
list_tables
Lists all tables in the Supabase project
match_vectors
Requires a valid RPC function name and an embedding array. Performs a vector similarity search via Postgres RPC
query_table_rows
Provide table name and optional select/limit. Queries rows from a specific table
Example Prompts for Supabase Vector in Google ADK
Ready-to-use prompts you can give your Google ADK agent to start working with Supabase Vector immediately.
"Using the 'match_docs' vector RPC natively, analyze my embedding representation returning seamlessly the top 5 matches."
"Browse my schema directly to identify active vector tables and delete any legacy testing embeddings from 'test_docs' securely."
"Insert a new embedding natively calling `insert_table_rows` with the corresponding context efficiently."
Troubleshooting Supabase Vector MCP Server with Google ADK
Common issues when connecting Supabase Vector to Google ADK through the Vinkius, and how to resolve them.
McpToolset not found
pip install --upgrade google-adkSupabase Vector + Google ADK FAQ
Common questions about integrating Supabase Vector 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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Microsoft's framework for multi-agent collaborative conversations.
Connect Supabase Vector to Google ADK
Get your token, paste the configuration, and start using 7 tools in under 2 minutes. No API key management needed.