Supabase Vector MCP Server for AutoGen 7 tools — connect in under 2 minutes
Microsoft AutoGen enables multi-agent conversations where agents negotiate, delegate, and execute tasks collaboratively. Add Supabase Vector as an MCP tool provider through Vinkius and every agent in the group can access live data and take action.
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Vinkius supports streamable HTTP and SSE.
import asyncio
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.tools.mcp import McpWorkbench
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
async with McpWorkbench(
server_params={"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"},
transport="streamable_http",
) as workbench:
tools = await workbench.list_tools()
agent = AssistantAgent(
name="supabase_vector_agent",
tools=tools,
system_message=(
"You help users with Supabase Vector. "
"7 tools available."
),
)
print(f"Agent ready with {len(tools)} tools")
asyncio.run(main())
* 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.
AutoGen enables multi-agent conversations where agents negotiate, delegate, and collaboratively use Supabase Vector tools. Connect 7 tools through Vinkius and assign role-based access. a data analyst queries while a reviewer validates, with optional human-in-the-loop approval for sensitive operations.
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 AutoGen 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 AutoGen via MCP
Follow these steps to integrate the Supabase Vector MCP Server with AutoGen.
Install AutoGen
Run pip install "autogen-ext[mcp]"
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Integrate into workflow
Use the agent in your AutoGen multi-agent orchestration
Explore tools
The workbench discovers 7 tools from Supabase Vector automatically
Why Use AutoGen with the Supabase Vector MCP Server
AutoGen provides unique advantages when paired with Supabase Vector through the Model Context Protocol.
Multi-agent conversations: multiple AutoGen agents discuss, delegate, and collaboratively use Supabase Vector tools to solve complex tasks
Role-based architecture lets you assign Supabase Vector tool access to specific agents. a data analyst queries while a reviewer validates
Human-in-the-loop support: agents can pause for human approval before executing sensitive Supabase Vector tool calls
Code execution sandbox: AutoGen agents can write and run code that processes Supabase Vector tool responses in an isolated environment
Supabase Vector + AutoGen Use Cases
Practical scenarios where AutoGen combined with the Supabase Vector MCP Server delivers measurable value.
Collaborative analysis: one agent queries Supabase Vector while another validates results and a third generates the final report
Automated review pipelines: a researcher agent fetches data from Supabase Vector, a critic agent evaluates quality, and a writer produces the output
Interactive planning: agents negotiate task allocation using Supabase Vector data to make informed decisions about resource distribution
Code generation with live data: an AutoGen coder agent writes scripts that process Supabase Vector responses in a sandboxed execution environment
Supabase Vector MCP Tools for AutoGen (7)
These 7 tools become available when you connect Supabase Vector to AutoGen 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 AutoGen
Ready-to-use prompts you can give your AutoGen 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 AutoGen
Common issues when connecting Supabase Vector to AutoGen through the Vinkius, and how to resolve them.
McpWorkbench not found
pip install "autogen-ext[mcp]"Supabase Vector + AutoGen FAQ
Common questions about integrating Supabase Vector MCP Server with AutoGen.
How does AutoGen connect to MCP servers?
Can different agents have different MCP tool access?
Does AutoGen support human approval for tool calls?
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Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Supabase Vector to AutoGen
Get your token, paste the configuration, and start using 7 tools in under 2 minutes. No API key management needed.