Supabase Vector MCP Server for Windsurf 7 tools — connect in under 2 minutes
Windsurf brings agentic AI coding to a purpose-built IDE. Connect Supabase Vector through the Vinkius and Cascade will auto-discover every tool — ask questions, generate code, and act on live data without leaving your editor.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
Vinkius Desktop App
The modern way to manage MCP Servers — no config files, no terminal commands. Install Supabase Vector and 2,500+ MCP Servers from a single visual interface.
{
"mcpServers": {
"supabase-vector": {
"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
}
}
}
* 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.
Windsurf's Cascade agent chains multiple Supabase Vector tool calls autonomously — query data, analyze results, and generate code in a single agentic session. Paste the Vinkius Edge URL, reload, and all 7 tools are immediately available. Real-time tool feedback appears inline, so you see API responses directly in your editor.
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 Windsurf 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 Windsurf via MCP
Follow these steps to integrate the Supabase Vector MCP Server with Windsurf.
Open MCP Settings
Go to Settings → MCP Configuration or press Cmd+Shift+P and search "MCP"
Add the server
Paste the JSON configuration above into mcp_config.json
Save and reload
Windsurf will detect the new server automatically
Start using Supabase Vector
Open Cascade and ask: "Using Supabase Vector, help me..." — 7 tools available
Why Use Windsurf with the Supabase Vector MCP Server
Windsurf provides unique advantages when paired with Supabase Vector through the Model Context Protocol.
Windsurf's Cascade agent autonomously chains multiple tool calls in sequence, solving complex multi-step tasks without manual intervention
Purpose-built for agentic workflows — Cascade understands context across your entire codebase and integrates MCP tools natively
JSON-based configuration means zero code changes: paste a URL, reload, and all 7 tools are immediately available
Real-time tool feedback is displayed inline, so you see API responses directly in your editor without switching contexts
Supabase Vector + Windsurf Use Cases
Practical scenarios where Windsurf combined with the Supabase Vector MCP Server delivers measurable value.
Automated code generation: ask Cascade to fetch data from Supabase Vector and generate models, types, or handlers based on real API responses
Live debugging: query Supabase Vector tools mid-session to inspect production data while debugging without leaving the editor
Documentation generation: pull schema information from Supabase Vector and have Cascade generate comprehensive API docs automatically
Rapid prototyping: combine Supabase Vector data with Cascade's code generation to scaffold entire features in minutes
Supabase Vector MCP Tools for Windsurf (7)
These 7 tools become available when you connect Supabase Vector to Windsurf 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 Windsurf
Ready-to-use prompts you can give your Windsurf 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 Windsurf
Common issues when connecting Supabase Vector to Windsurf through the Vinkius, and how to resolve them.
Server not connecting
Supabase Vector + Windsurf FAQ
Common questions about integrating Supabase Vector MCP Server with Windsurf.
How does Windsurf discover MCP tools?
mcp_config.json file on startup and connects to each configured server via Streamable HTTP. Tools are listed in the MCP panel and available to Cascade automatically.Can Cascade chain multiple MCP tool calls?
Does Windsurf support multiple MCP servers?
mcp_config.json. Each server's tools appear in the MCP panel and Cascade can use tools from different servers in a single flow.Connect Supabase Vector with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Supabase Vector to Windsurf
Get your token, paste the configuration, and start using 7 tools in under 2 minutes. No API key management needed.