Compatible with every major AI agent and IDE
Count on Qdrant
Counts the total number of points in a collection
Delete on Qdrant
This action is irreversible. Deletes specific points from a collection
Get collection on Qdrant
Retrieves detailed information about a specific collection
Get points on Qdrant
Retrieves specific points by their IDs
List collections on Qdrant
Lists all collections in the Qdrant instance
Scroll on Qdrant
Returns points with their payloads. Scrolls through points in a collection, useful for pagination
Search on Qdrant
You must provide a JSON array of floats for the query vector. Performs a nearest neighbor vector search in a collection
How Vinkius protects your data
Can I set different limits for each virtual assistant on my team?
Absolutely. You have full control in our command center. You can create an AI agent that only "reads" data so the support team can answer questions, and another superpowered agent that can "edit" and "create" information exclusively for your operations team. Each AI gets exactly the level of access you allow.
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.
Does it support deleting vectors?
Yes. If an embedding got corrupted or references dropped articles, use the delete tool. Pass the collection name and the list of specific IDs. Qdrant handles the mutation instantly and updates the index without rebuilding.
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.
Supported Use Cases for Qdrant
We map standard API endpoints to agent-compatible instructions. Connect Qdrant to execute these core functional operations.
Automating vector database with AI
Use the Qdrant server to execute vector database operations from your AI agent. The protocol manages state and authentication for continuous ai frontier workflows.
The Future of semantic search
The Qdrant toolkit provides AI native integration for semantic search. It structures data so Claude Code can accurately process ai frontier requirements.
Qdrant. 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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