Qdrant MCP on Qdrant - Vector Search Engine

Qdrant Cloud MCP

info@qdrant.tech (Andrey Vasnetsov) — Mon, 01 Jan 0001 00:00:00 +0000

Qdrant Cloud MCP

The Qdrant Cloud MCP server lets your AI assistant manage your Qdrant Cloud account in plain language. It also searches the official Qdrant documentation, so your assistant can answer questions with current docs and code snippets.

It is a remote server: there is nothing to install or run, and you sign in with OAuth in your browser instead of pasting an API key into a config file.

Qdrant Docs MCP

info@qdrant.tech (Andrey Vasnetsov) — Mon, 01 Jan 0001 00:00:00 +0000

Qdrant Docs MCP

The Qdrant Docs MCP server gives your AI assistant read access to the content on qdrant.tech: the documentation, technical articles, the blog, and Qdrant Academy courses. Documentation changes between releases. With this server, your assistant looks up current behavior instead of answering from what it remembers.

It is a remote server with no authentication, so there is nothing to install and no key to paste.

Endpoint: https://search.qdrant.tech/mcp
Transport: HTTP (streamable)
Auth: None

Tools

Tool	What it does
`list_docs`	Browses the structure of the content. Without arguments, it lists the top-level sections. With a section path such as `/documentation/search/`, it lists that section’s pages with short descriptions.
`search_docs`	Searches the documentation, articles, blog, and courses. Narrow it with `sources` to one or more of `documentation`, `articles`, `blog`, and `course`, or with `partition` to `develop`, `deploy`, `ecosystem`, or `learn` to search one part of the documentation.
`get_page`	Reads one page in full as Markdown, including its code examples. Pass a qdrant.tech URL or a path such as `/documentation/search/hybrid-queries/`.
`search_snippets`	Finds code examples by what they do. Pass a `language`, such as `python`, `typescript`, `rust`, `java`, `csharp`, `go`, `http`, or `shell`, to get examples for one client.

A typical lookup runs in two steps. The assistant calls search_docs to find the relevant pages, then get_page to read them. Search results are short excerpts, so the assistant reads the page before it relies on the answer. When your question is about code, it calls search_snippets first, and then get_page on the snippet page, which shows the same example in every client language.

Qdrant MCP (Open Source)

info@qdrant.tech (Andrey Vasnetsov) — Mon, 01 Jan 0001 00:00:00 +0000

Qdrant MCP (Open Source)

mcp-server-qdrant is the official open source MCP server for Qdrant. It acts as a semantic memory layer on top of a Qdrant collection: your assistant stores pieces of information and retrieves them later by meaning.

You run it yourself, next to the assistant or on your own infrastructure, and point it at any Qdrant deployment: Qdrant Cloud, a local instance, or a local database file. The server creates the collection if it does not exist, and generates embeddings with FastEmbed, so you need no embedding provider key.