Qdrant MCP Server for Mastra AI 7 tools — connect in under 2 minutes
Mastra AI is a TypeScript-native agent framework built for modern web stacks. Connect Qdrant through Vinkius and Mastra agents discover all tools automatically. type-safe, streaming-ready, and deployable anywhere Node.js runs.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import { Agent } from "@mastra/core/agent";
import { createMCPClient } from "@mastra/mcp";
import { openai } from "@ai-sdk/openai";
async function main() {
// Your Vinkius token. get it at cloud.vinkius.com
const mcpClient = await createMCPClient({
servers: {
"qdrant": {
url: "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
},
},
});
const tools = await mcpClient.getTools();
const agent = new Agent({
name: "Qdrant Agent",
instructions:
"You help users interact with Qdrant " +
"using 7 tools.",
model: openai("gpt-4o"),
tools,
});
const result = await agent.generate(
"What can I do with Qdrant?"
);
console.log(result.text);
}
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 Qdrant MCP Server
Connect your Qdrant vector database (Cloud or Self-Hosted) to any AI agent and bring powerful semantic retrieval and database management into your conversation.
Mastra's agent abstraction provides a clean separation between LLM logic and Qdrant tool infrastructure. Connect 7 tools through Vinkius and use Mastra's built-in workflow engine to chain tool calls with conditional logic, retries, and parallel execution. deployable to any Node.js host in one command.
What you can do
- Discover Collections — List all vector collections in your cluster, fetch detailed distance metrics, and monitor total payload points instantly
- Semantic Vector Search — Perform nearest neighbor similarity searches. Pass a JSON array of floats and retrieve the exact payloads matching your query
- Data Management — Read specific points by ID or scroll sequentially through giant datasets to debug payloads and embedding quality
- Mutation Operations — Delete redundant data points safely without building separate admin scripts
The Qdrant MCP Server exposes 7 tools through the Vinkius. Connect it to Mastra AI 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 Qdrant to Mastra AI via MCP
Follow these steps to integrate the Qdrant MCP Server with Mastra AI.
Install dependencies
Run npm install @mastra/core @mastra/mcp @ai-sdk/openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.ts and run with npx tsx agent.ts
Explore tools
Mastra discovers 7 tools from Qdrant via MCP
Why Use Mastra AI with the Qdrant MCP Server
Mastra AI provides unique advantages when paired with Qdrant through the Model Context Protocol.
Mastra's agent abstraction provides a clean separation between LLM logic and tool infrastructure. add Qdrant without touching business code
Built-in workflow engine chains MCP tool calls with conditional logic, retries, and parallel execution for complex automation
TypeScript-native: full type inference for every Qdrant tool response with IDE autocomplete and compile-time checks
One-command deployment to any Node.js host. Vercel, Railway, Fly.io, or your own infrastructure
Qdrant + Mastra AI Use Cases
Practical scenarios where Mastra AI combined with the Qdrant MCP Server delivers measurable value.
Automated workflows: build multi-step agents that query Qdrant, process results, and trigger downstream actions in a typed pipeline
SaaS integrations: embed Qdrant as a first-class tool in your product's AI features with Mastra's clean agent API
Background jobs: schedule Mastra agents to query Qdrant on a cron and store results in your database automatically
Multi-agent systems: create specialist agents that collaborate using Qdrant tools alongside other MCP servers
Qdrant MCP Tools for Mastra AI (7)
These 7 tools become available when you connect Qdrant to Mastra AI via MCP:
count
Counts the total number of points in a collection
delete
This action is irreversible. Deletes specific points from a collection
get_collection
Retrieves detailed information about a specific collection
get_points
Retrieves specific points by their IDs
list_collections
Lists all collections in the Qdrant instance
scroll
Returns points with their payloads. Scrolls through points in a collection, useful for pagination
search
You must provide a JSON array of floats for the query vector. Performs a nearest neighbor vector search in a collection
Example Prompts for Qdrant in Mastra AI
Ready-to-use prompts you can give your Mastra AI agent to start working with Qdrant immediately.
"List the configurations for all collections in my Qdrant instance."
"Count the total embedded points in the 'docs-embeddings' collection."
"Scroll and show me the IDs and payloads of the first 3 items in the 'users' collection."
Troubleshooting Qdrant MCP Server with Mastra AI
Common issues when connecting Qdrant to Mastra AI through the Vinkius, and how to resolve them.
createMCPClient not exported
npm install @mastra/mcpQdrant + Mastra AI FAQ
Common questions about integrating Qdrant MCP Server with Mastra AI.
How does Mastra AI connect to MCP servers?
MCPClient with the server URL and pass it to your agent. Mastra discovers all tools and makes them available with full TypeScript types.Can Mastra agents use tools from multiple servers?
Does Mastra support workflow orchestration?
Connect Qdrant 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 Qdrant to Mastra AI
Get your token, paste the configuration, and start using 7 tools in under 2 minutes. No API key management needed.