@rosalinddb/mcp
The @rosalinddb/mcp server lets AI clients (e.g., Claude Desktop, Cursor) interact with a RosalindDB vector database instance to manage datasets, store and search vectors, and monitor usage — without writing REST calls directly.
Dataset Management
List datasets: View all vector datasets with their dimension, status, and row count.
Create a dataset: Create a new empty vector dataset by specifying a name and vector dimension.
Get dataset details: Retrieve a single dataset's metadata including status (
empty/validating/indexing/indexed/error), row count, and timestamps — useful for polling indexing progress.Delete a dataset: Permanently remove a dataset and all its vectors.
Vector Operations
Ingest vectors: Upsert vector records (ID, embedding values, optional metadata) into a dataset.
Query vectors: Run a nearest-neighbor similarity search (L2 distance) with an optional metadata filter.
Get / list / delete individual vectors: Fetch, enumerate, or remove specific vectors by ID.
Administration & Monitoring
Get usage: Check vectors stored vs. quota, queries today vs. daily limit, and quota reset time.
List API keys: View API key metadata (name, creation time, last use, revocation status) — raw key values are never exposed.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@@rosalinddb/mcpfind the top 5 vectors closest to [0.2,0.8,0.3] in the 'embeddings' dataset"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
@rosalinddb/mcp
Model Context Protocol server for RosalindDB.
A Model Context Protocol (MCP) server for RosalindDB — a cost-optimized, object-storage-first vector search database.
This server lets MCP-capable AI clients (Claude Desktop, Cursor, Claude Code,
and others) operate a RosalindDB instance directly: create datasets, ingest
vectors, run similarity queries, and check usage — without hand-writing REST
calls. It is a thin wrapper over RosalindDB's v1 REST API: it authenticates
with an rb_live_ API key when the backend has auth enabled, otherwise it
runs unauthenticated against an OSS-default backend. It contains no business
logic of its own.
The RosalindDB engine lives at
rosalinddb/rosalinddb.
Self-host it via docker compose and point this MCP at it.
Tools
Tool | RosalindDB endpoint | What it does |
|
| List all datasets with dimension, status, row count. |
|
| Create a new empty dataset with a name and vector dimension. |
|
| Get one dataset's details and indexing status. |
|
| Delete a dataset and its vectors. |
|
| Upsert vector records (id, values, optional metadata). Read-your-writes when the recall tier is on. |
|
| Vector similarity search with an optional flat metadata filter. Reports the serving tier in |
|
| Fetch one vector's id + metadata (optionally its embedding). |
|
| List/enumerate stored vectors (memories) with an optional filter. |
|
| Delete one vector by id (read-your-deletes when the recall tier is on). |
|
| Current usage and quotas (vectors stored, queries today). |
|
| List the instance's API keys (metadata only). |
For very large embedding dumps (over the 10 MiB ingest_vectors cap), use
RosalindDB's async import-job flow directly via the REST API.
Related MCP server: MCP-Smallest.ai
Recall tier (read-your-writes)
RosalindDB can run an optional recall tier — a hot pgvector instance the
server enables with RB_RECALL + RB_RECALL_DSN. It's transparent to this MCP
(nothing to configure client-side), but it changes the behavior an agent sees:
ingest_vectorsis read-your-writes. With recall on, an upsert is synchronous (nojob_idin the result) and the vector is immediately returned by the nextquery_vectors. With recall off, ingest is eventually consistent (returns ajob_id) — pollget_datasetuntilstatusisindexed.delete_vectoris read-your-deletes. With recall on, a delete is a synchronous tombstone ({ synchronous: true }) and the vector is gone from queries at once; with recall off it queues a rebuild ({ async: true, job_id }).query_vectorsreports the serving tier inmode:recall(the recall tier),hot/cold(the consolidated object-storage tier —hot= shard already cached in memory,cold= first fetch), orephemeral(no shard yet, computed on demand). Recall and consolidated results are unioned, with recall authoritative for anything written since the last consolidation.
This makes RosalindDB usable as agent working memory: store a fact and recall it on the very next turn. See the engine's recall / consolidate docs.
Auth modes
The RosalindDB backend ships in two modes; the MCP server supports both:
OSS default (
RB_REQUIRE_AUTH=false): no auth, no API key needed. This is whatdocker compose upgives you out of the box. SetROSALINDDB_API_URLto your stack and leaveROSALINDDB_API_KEYunset. Thelist_api_keys,get_usage, and signup endpoints are disabled in this mode; calls to them surface a clearauth_disabledhint.Multi-tenant self-host (
RB_REQUIRE_AUTH=true): setROSALINDDB_API_KEY=rb_live_.... Create a key withPOST /auth/keys(or usePOST /auth/signupfor the first user on a fresh stack).
Configuration
The server reads two environment variables:
Variable | Required | Default | Description |
| No | — | A RosalindDB API key ( |
| No |
| Base URL of the RosalindDB API. |
When set, the key is sent as Authorization: Bearer rb_live_... on every
request. A key that doesn't start with rb_live_ triggers a startup warning
but is not rejected (in case you front the backend with a custom auth proxy).
Wiring it into an MCP client
Add this to your MCP client config (for Claude Desktop,
claude_desktop_config.json):
{
"mcpServers": {
"rosalinddb": {
"command": "npx",
"args": ["-y", "@rosalinddb/mcp"],
"env": {
"ROSALINDDB_API_URL": "http://localhost:8080"
}
}
}
}npx -y @rosalinddb/mcp downloads and runs the server on demand — no global
install needed. The server speaks the stdio transport, the standard for a
locally-launched MCP server.
Pointing at a non-local instance? Set
ROSALINDDB_API_URLto its base URL. If auth is on, also setROSALINDDB_API_KEY=rb_live_.... The backend lives at rosalinddb/rosalinddb.
Local development
npm install # install dependencies
npm run build # compile TypeScript to dist/
npm test # run the vitest unit + in-process MCP suite
npm run smoke # build, then drive a real tools/list over stdioTo run the server directly from a local checkout:
{
"mcpServers": {
"rosalinddb": {
"command": "node",
"args": ["/absolute/path/to/mcp-server/dist/index.js"],
"env": {
"ROSALINDDB_API_URL": "http://localhost:8080"
}
}
}
}Live smoke test
With a running RosalindDB stack and a real key, tests/live-smoke.mjs
exercises create → ingest → usage → query → delete end to end:
npm run build
ROSALINDDB_API_KEY=rb_live_... node tests/live-smoke.mjsIt is skipped automatically when no key is set.
Error handling
RosalindDB API errors are mapped to clear, actionable MCP tool errors — never
a raw stack trace. A 404 surfaces as "dataset does not exist — list datasets
or create it first"; a 429 quota error explains the limit and how to recover;
a 404 auth_disabled (calling list_api_keys against an OSS-default
backend) explains that the auth endpoints are gated behind
RB_REQUIRE_AUTH=true; and a 503 recall_write_failed / recall_delete_failed
/ recall_unavailable explains that the read-your-writes tier is momentarily
down and the call should be retried.
License
Apache 2.0. See LICENSE.
Security
To report a vulnerability, see SECURITY.md.
Maintenance
Resources
Unclaimed servers have limited discoverability.
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If you are the server author, to access and configure the admin panel.
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