n8n-nodes-mongodb-vector-search

An n8n community node designed for high-performance MongoDB Vector Search, standard queries, and custom JSON aggregation pipelines. It integrates directly with MongoDB Atlas Vector Search and leverages connection pooling to ensure fast, low-latency execution.

Features

• Atlas Vector Search: Natively query MongoDB Atlas vector indexes using query vectors and candidates constraints.
• Connection Pooling: Connections are cached globally in memory, reusing MongoClient instances across executions to prevent connection establishment overhead.
• EJSON Parsing: Supports Extended JSON natively, allowing you to easily use MongoDB-specific types (e.g. {"$oid": "..."}, {"$date": "..."}) in queries.
• Seamless Credential Reuse: Directly reuses n8n's standard MongoDB (mongoDb) credentials.
• Custom Searches: Run custom native queries or complex aggregation pipelines via the raw JSON code editor.
• Aesthetic Iconography: Comes with matching icons for both light and dark modes.

Installation

To install this community node in your n8n instance:

1. Go to Settings > Community Nodes.
2. Click Install a new node.
3. Enter the npm package name: n8n-nodes-mongodb-vector-search.
4. Agree to the terms and click Install.

Once installed, restart n8n (if self-hosted) to load the node assets.

Operations & Configuration

1. Vector Search

Uses MongoDB Atlas Vector Search ($vectorSearch aggregation stage).

• Index Name: Name of the Vector Search index in Atlas (default is default).
• Embedding Field: Field containing the vector embeddings (e.g. embedding).
• Query Vector: The input search embedding as a JSON array of numbers (e.g. [0.021, -0.14, 0.985]).
• Num Candidates: Number of candidate documents to scan (default 100).
• Limit: Number of documents to return.
• Filter: Optional MongoDB filter query to narrow down vector search results (e.g. {"status": "active"}).
• Projection: Optional fields projection.

2. Find (Normal Search)

Performs a standard query against a collection.

• Query (JSON): Standard MongoDB query filter (e.g. {"category": "AI", "age": {"$gte": 21}}).
• Sort (JSON): Sort order representation (e.g. {"createdAt": -1}).
• Limit / Skip: Pagination settings.

3. Custom Search

Runs a native query or custom aggregation.

• Custom Type: Choose between Native Query (find) or Aggregation Pipeline (aggregate).
• Query (JSON): Input raw filter JSON.
• Aggregation Pipeline (JSON): Input raw pipeline stages array JSON (e.g., [{"$match": {...}}, {"$group": {...}}]).

Advanced Options

• EJSON Formatting: Enabled by default. Converts MongoDB type definitions from JSON input automatically and serializes results safely.
• Output Mode:
  • Separate Items: Emits each document as a separate n8n execution item.
  • Single Array: Groups all resulting documents into a single array under the key results.
• Include Similarity Score: Appends Atlas similarity score as _score in vector search results.