> ## Documentation Index
> Fetch the complete documentation index at: https://portkey-docs-feat-rerank-documentation.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Qdrant MCP server

> The Qdrant MCP server enables AI agents to store and retrieve semantic information using vector search through MCP. Built for persistent memory, contextual knowledge, and efficient semantic retrieval workflows.

## When you should use this server

* Give AI assistants **persistent memory** across sessions and conversations
* Store knowledge, facts, or documents in a vector database for later retrieval
* Retrieve **semantic matches** to queries instead of relying on exact keyword lookups
* Manage contextual memory for long-running workflows or applications

## Key features

* Semantic vector storage and retrieval
* Context-aware memory persistence
* Efficient similarity search
* Metadata filtering and payload storage
* Cross-session memory for AI assistants
* Compatibility with both cloud and self-hosted deployments

## Requirements

* **Hosting:** Works with a running Qdrant instance (cloud or self-hosted)
* **Authentication:** Standard Qdrant API authentication (if enabled)
* **Collections:** Requires specifying a collection name unless a default is configured

## Tools provided

### qdrant-store

Stores information in the Qdrant vector database with optional metadata.

**Parameters:**

* `information` *(string, required)* — content to store
* `metadata` *(JSON, optional)* — associated metadata to store alongside the vector
* `collection_name` *(string, required if no default)* — collection to store data in

**Returns:**

* Confirmation message with vector ID and status

### qdrant-find

Retrieves semantically relevant information from Qdrant based on the meaning of the query.

**Parameters:**

* `query` *(string, required)* — text to search for semantically similar content
* `collection_name` *(string, required if no default)* — collection to search

**Returns:**

* Matching stored information, ordered by semantic similarity

## Notes

* Best used as a **memory backend** for AI assistants needing semantic recall
* Requires an active Qdrant instance; supports both **Qdrant Cloud** and **self-hosted deployments**