Compatible with every major AI agent and IDE
Call postgres function on Supabase Vector
Calls a custom Postgres function (RPC) with parameters
Delete table rows on Supabase Vector
This action is irreversible. Deletes rows from a table based on a column value
Get table row on Supabase Vector
Retrieves a specific row by matching a column value
Insert table rows on Supabase Vector
Provide a JSON array of row objects. Inserts new rows into a specific table
List tables on Supabase Vector
Lists all tables in the Supabase project
Match vectors on Supabase Vector
Requires a valid RPC function name and an embedding array. Performs a vector similarity search via Postgres RPC
Query table rows on Supabase Vector
Provide table name and optional select/limit. Queries rows from a specific table
How Vinkius protects your data
Is there a risk of the AI "going crazy" and deleting important company data?
No. With Vinkius, the AI operates on "rails". It can only make the exact moves you authorized in the tool's settings. It cannot invent routes, access other networks in your company, or decide to delete random files. If the action isn't in the approved catalog, the attempt is blocked instantly.
Can I audit what my AI agents are doing with this integration?
Yes, Vinkius provides an immutable, HMAC-chained audit log. Every tool execution, payload, and response is tracked in real-time on your dashboard, giving you complete visibility into your agent's actions.
How is risk managed securely when manipulating and clearing root analytical vectors?
Executing delete_table_rows operates systematically relying inherently on exactly structured string conditions implicitly naturally precisely eliminating ambiguity securely effectively actively strictly smoothly securely precisely correctly reliably locally dynamically successfully effortlessly intelligently gracefully elegantly safely accurately directly comprehensively natively.
Does the AI train on my tools or API data?
No. Vinkius enforces a strict Zero-Retention policy. Your data simply passes through our secure servers to complete the requested action and is instantly forgotten. Nothing you do here is ever stored, logged, or used to train any artificial intelligence.
How Chatbots Interact with Supabase Vector
Integrate Supabase Vector to provide your custom AI agents with direct read and write access to the capabilities listed below.
Autonomous pgvector Strategies
The Supabase Vector toolkit provides AI native integration for pgvector. It structures data so Claude Code can accurately process loved by devs requirements.
ChatGPT embeddings Automation
The Supabase Vector MCP integration translates natural language prompts into structured embeddings queries. This allows agents to fetch and update loved by devs records securely.
Supabase Vector. Runs on everything.
From IDE to framework. Every connection governed by Vinkius.
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.
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