qdrant-full-mcp

One MCP server for all of Qdrant. Manage your Qdrant Cloud account (clusters, backups, API keys) and work with your data (collections, points, vector and hybrid search) from Claude Code, Codex, Cursor, VS Code or any MCP client. Everything the official mcp-server-qdrant does (store and find text) is included; see the comparison.

Unofficial community project, not affiliated with or endorsed by Qdrant.

• Cloud management: create, scale, suspend, restart, back up, restore and delete clusters through the official Qdrant Cloud API.
• Data plane: create collections, upsert and search points, hybrid dense + sparse search, payload indexes.
• Plain-text memory: store_text and find_text embed text locally (FastEmbed), so you can store and search without making vectors yourself. Works with collections made by the official mcp-server-qdrant.
• Safe by default: every change is a dry run until confirmed; destructive actions need the exact resource name.
• One variable to start: just your Cloud Management Key. The account ID is detected automatically, and the agent creates and remembers the database key itself, so you can go from no cluster to searching your data in one chat.

Quick start

1. Get a key. Qdrant Cloud Console -> Access Management -> Cloud Management Keys -> create one. (Least privilege is fine: read-only permissions are enough for the read tools.)

2. Download once. Requires uv. The first run fetches the dependencies (about 40 seconds, cached afterwards), which is longer than some clients wait for a server to start:

uvx qdrant-full-mcp --help

3. Add it to your client:

Claude Code

claude mcp add qdrant -e QDRANT_CLOUD_API_KEY=your-management-key -- uvx qdrant-full-mcp

Check with claude mcp list, or /mcp inside Claude Code. Then try: "List my Qdrant Cloud clusters."

Prefer not to store the key in Claude's config? Set QDRANT_CLOUD_API_KEY in your shell profile and use -e 'QDRANT_CLOUD_API_KEY=${QDRANT_CLOUD_API_KEY}' instead.

As a plugin (adds a usage skill that teaches Claude the safe workflows):

/plugin marketplace add Jeevav62/qdrant-full-mcp
/plugin install qdrant@qdrant-full-mcp

With the plugin, set QDRANT_CLOUD_API_KEY in your environment before starting Claude Code.

Codex

codex mcp add qdrant --env QDRANT_CLOUD_API_KEY=your-management-key -- uvx qdrant-full-mcp

Or edit ~/.codex/config.toml by hand:

[mcp_servers.qdrant]
command = "uvx"
args = ["qdrant-full-mcp"]
startup_timeout_sec = 60

[mcp_servers.qdrant.env]
QDRANT_CLOUD_API_KEY = "your-management-key"

Verify with codex mcp list.

Cursor, Claude Desktop, Windsurf and other JSON-config clients

{
  "mcpServers": {
    "qdrant": {
      "command": "uvx",
      "args": ["qdrant-full-mcp"],
      "env": { "QDRANT_CLOUD_API_KEY": "your-management-key" }
    }
  }
}

(Cursor: ~/.cursor/mcp.json. Claude Desktop: claude_desktop_config.json.)

VS Code

.vscode/mcp.json:

{
  "servers": {
    "qdrant": {
      "type": "stdio",
      "command": "uvx",
      "args": ["qdrant-full-mcp"],
      "env": { "QDRANT_CLOUD_API_KEY": "your-management-key" }
    }
  }
}

From a local clone

git clone https://github.com/Jeevav62/qdrant-full-mcp
claude mcp add qdrant -e QDRANT_CLOUD_API_KEY=your-management-key -- uv run --project ./qdrant-full-mcp qdrant-full-mcp

Using the data tools

The management key manages infrastructure only; Qdrant does not let it read or write vectors. Data needs a database API key, and the agent can make one for you, with no config editing and no restart:

"Create a free cluster in AWS Mumbai, then make me a database key and store these notes in it."

When create_database_api_key creates a key, the server remembers it for that cluster and the data tools use it at once. The agent asks whether to save it on this machine; if you say yes, every later session (Claude Code, Codex, Cursor, ...) uses it automatically. Saved keys live in %APPDATA%\qdrant-full-mcp\keys.json on Windows or ~/.config/qdrant-full-mcp/keys.json elsewhere (file mode 600, never printed by any tool). Deleting the key or the cluster removes it from there too; forget_database_api_key removes it on request, list_remembered_keys shows what is stored without secrets. Set QDRANT_MCP_KEY_FILE=off to never write keys to disk.

You can still set keys yourself; they take priority over remembered ones:

export QDRANT_API_KEY_<CLUSTER_ID>=the-database-key    # per cluster (UUID uppercased, '-' -> '_')
export QDRANT_API_KEY=the-database-key                 # fallback for any cluster

Pass cluster_id to any data tool and the endpoint is looked up for you. For a local or self-hosted Qdrant, set QDRANT_URL (e.g. http://localhost:6333) and QDRANT_API_KEY instead and skip cluster_id.

Store and search plain text

store_text and find_text embed text on your machine with FastEmbed, the same approach as the official mcp-server-qdrant, so no vectors are needed. Nothing extra to install.

For a simple agent memory, set a default collection:

claude mcp add qdrant -e QDRANT_URL=https://your-cluster:6333 -e QDRANT_API_KEY=db-key -e COLLECTION_NAME=memory   -- uvx qdrant-full-mcp

Then just say "Remember that refunds take 5 business days" and later "How long do refunds take?". With COLLECTION_NAME set, storing into that collection happens in one step and the collection is created on first use; any other collection keeps the dry-run-then-confirm flow. Without it, name the collection in your request.

• No server at all: set QDRANT_LOCAL_PATH=./qdrant-data instead of QDRANT_URL and Qdrant runs inside the MCP server, storing data in that folder (:memory: keeps it in RAM). Every data and text tool works the same. Good for learning and small projects; switch to a real cluster later by changing one variable.
• TOOL_STORE_DESCRIPTION and TOOL_FIND_DESCRIPTION replace the tool descriptions, e.g. "Store a reusable code snippet with its description", to turn the memory into something specific. QDRANT_SEARCH_LIMIT sets the default number of results (5).
• The first text call downloads the model (about 90 MB, cached afterwards).
• Filtering on Qdrant Cloud: Cloud clusters require a payload index on any field you filter by. Ask "add a keyword index on metadata.topic in memory" once; if you forget, the error tells the model the exact call that fixes it.
• Default model sentence-transformers/all-MiniLM-L6-v2 (384 dimensions); change it with EMBEDDING_MODEL.
• Layout matches the official server: a named vector fast-<model> and payload {"document", "metadata"}, so both servers can read and write the same collection.

Remote (HTTP) mode

stdio is the default. To run it as a server that clients connect to over HTTP:

qdrant-full-mcp --transport streamable-http --port 8000   # endpoint http://127.0.0.1:8000/mcp
qdrant-full-mcp --transport sse                           # older SSE clients

It binds to 127.0.0.1 by default. There is no built-in authentication and the server holds your Qdrant keys, so if you bind to another address (--host 0.0.0.0), put an authenticating proxy in front of it.

With Docker (the image includes the default embedding model and serves streamable HTTP on port 8000):

docker build -t qdrant-full-mcp .
docker run -p 127.0.0.1:8000:8000 -e QDRANT_URL=https://your-cluster:6333 -e QDRANT_API_KEY=db-key   -e COLLECTION_NAME=memory qdrant-full-mcp

Example prompts

• "List my Qdrant Cloud clusters." / "Show the available AWS regions."
• "Create a Qdrant cluster in AWS London with the smallest paid package." (shows the price first, waits for your approval)
• "Scale cluster X to 3 nodes." / "Suspend cluster X."
• "Back up cluster X every day at 3am and keep backups for 14 days."
• "Restore backup Y into a new cluster called restored-1."
• "Create a read-only database API key for cluster X that expires in 90 days."
• "Make a database key for cluster X and save it on this machine." (data tools then work in every session)
• "Create a collection docs with a dense vector (768, Cosine) and a sparse vector for hybrid search."
• "Add a keyword index on tenant_id in docs." / "How many points are in docs?"
• "Store these three FAQ answers in collection faq." / "Search faq for how refunds work."
• "Delete cluster old-test." (you must confirm the exact name)

Tools

Cloud, read-only: list_accounts, list_clusters, get_cluster, list_cloud_providers, list_regions, list_packages, list_releases, list_backups, list_backup_schedules, list_database_api_keys, list_members

Cloud, changes things: create_cluster, update_cluster, delete_cluster, restart_cluster, suspend_cluster, unsuspend_cluster, create_backup, delete_backup, restore_backup_to_new_cluster, restore_backup (in place, overwrites), create_backup_schedule, delete_backup_schedule, create_database_api_key (remembered so data tools work at once), delete_database_api_key, list_remembered_keys, forget_database_api_key

Data, read-only: list_collections, get_collection, list_payload_indexes, count_points, get_points, scroll_points, query_points (dense or sparse), hybrid_query_points (dense + sparse, RRF or DBSF fusion)

Data, changes things: create_collection (single, named and sparse vectors), delete_collection, create_payload_index, delete_payload_index, upsert_points, delete_points

Text: store_text (embeds and upserts, creates the collection if missing), find_text (embeds the query and searches)

Compared with the official mcp-server-qdrant

The text tools use the same collection layout, so the two servers can share a collection.

Safety

• Every mutating tool is a dry run unless confirm=true, and the tool descriptions tell the model to get your approval first.
• Irreversible tools need the exact name: delete_cluster and restore_backup (confirm_cluster_name), delete_collection (confirm_collection_name).
• QDRANT_MCP_READ_ONLY=1 (or QDRANT_READ_ONLY=1) blocks every confirmed write. QDRANT_MCP_MODULES (e.g. cloud, data,text) loads only the modules you list.
• Keys come from environment variables only and are never logged or echoed. A new database key's secret is shown once by Qdrant.
• Ids and paths are validated before any request. Prefer least-privilege keys.

Configuration

See .env.example. Never commit real values.

Status and roadmap

Verified against the live Qdrant Cloud API on a free-tier cluster: cluster create and update, restart, suspend and unsuspend, database API keys, and the data tools (collections, named and sparse vectors, upsert, dense, sparse and hybrid search, payload indexes, deletes). The text tools were verified end to end through the MCP protocol (stdio and streamable HTTP) against a local Qdrant 1.19 with the real FastEmbed model, including a first run with an empty model cache. Local mode (QDRANT_LOCAL_PATH) was verified for every data tool, including dense, sparse and hybrid search, and through the MCP protocol; the Docker image was verified over HTTP from a second container. The text tools and data tools were also verified on a Qdrant Cloud cluster: 26 checks covering store/find, metadata filters, default collection, read-only mode, named and sparse collections, payload indexes, dense, sparse and hybrid search, deletes, and a stdio server process calling find_text on Cloud. The remembered-key flow was verified on Cloud through the MCP protocol: create a key with remember="save", store and search in the same session, then search again from a fresh server process with no key in its config, then delete the key and confirm the saved copy is gone.

Not verified live yet: backups, backup schedules and restores (free-tier clusters do not support them), and cluster delete. Test those on a throwaway paid cluster first.

Ideas for later: snapshots, named-vector search options (quantization, HNSW tuning), payload updates without re-upserting, collection aliases, cluster configuration settings.

Not covered by design: inviting or removing members, roles and billing; hybrid-cloud environments and serverless spaces; embedding models other than FastEmbed's (for the other tools, bring your own vectors).

Development

pip install -e ".[dev]"
pytest

Cloud API schemas: https://github.com/qdrant/qdrant-cloud-public-api. The Cloud REST gateway expects snake_case query parameters (e.g. page_size) and accepts camelCase JSON bodies.

License

MIT. Unofficial community project, not affiliated with or endorsed by Qdrant. "Qdrant" is a trademark of its owner.