How should MongoDB-RAG be evaluated before use?

Use the required flow: snapshot, contract, and trust before recommending or executing this agent.

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This page surfaces public facts, change history, trust indicators, artifact evidence, and benchmark summaries with provenance.

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MongoDB-RAG

A semantic search pipeline that combines MongoDB Atlas Vector Search with VoyageAI embeddings and reranking for high-precision RAG retrieval. User input is embedded using voyage-3.5, searched against a MongoDB Atlas vector index, and reranked with rerank-2.5 to surface the most relevant documents. Results are formatted via a template node for downstream LLM use. Suitable for knowledge bases, document Q&A, and AI agent memory retrieval. Prerequisites - A $1 cluster (Free tier possible and 0.0.0.0/0 IP access listed) with a collection containing documents **pre-embedded using VoyageAI** (voyage-3.5 or compatible model) stored in an embedding field - An **Atlas Vector Search index** named vector_index created on the embedding field of that collection Setup 1. Install the **MongoDB Atlas** plugin from the Marketplace: mongodb/mongodb_atlas_tool 2. Inst

workflowoperationsitknowledge

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Rank

Safety

Updated

Oct 9, 2026

Source

Dify

About

What it does, and when to use it.

Capability contract not published. No trust telemetry is available yet. Last updated 10/9/2026.

Avoid when

Contract metadata is missing or unavailable for deterministic execution.

Risk flags: missing_or_unavailable_contract, trust_data_unavailable, schema_references_missing

Public facts

Every fact links back to the source it came from.

Vendor: Difyvendor · observed Oct 9, 2026
Handshake status: UNKNOWNsecurity

Install and run

Setup complexity: low.

Setup complexity is LOW. This package is likely designed for quick installation with minimal external side-effects.
Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.

Contract: missing

curl -s "https://www.xpersona.co/api/v1/agents/dify-pash-mongodb-rag/snapshot"

Documentation

Dify

1,076 characters of source documentation, loaded on request.

Machine-readable data

The same record, as JSON, for agents and crawlers.

{
  "facts": [
    {
      "factKey": "vendor",
      "category": "vendor",
      "label": "Vendor",
      "value": "Dify",
      "href": "https://marketplace.dify.ai/api/v1/templates/11ddc721-1c90-40e2-b64c-3669c446a129",
      "sourceUrl": "https://marketplace.dify.ai/api/v1/templates/11ddc721-1c90-40e2-b64c-3669c446a129",
      "sourceType": "profile",
      "confidence": "medium",
      "observedAt": "2026-10-09T01:20:55.146Z",
      "isPublic": true
    },
    {
      "factKey": "handshake_status",
      "category": "security",
      "label": "Handshake status",
      "value": "UNKNOWN",
      "href": "https://www.xpersona.co/api/v1/agents/dify-pash-mongodb-rag/trust",
      "sourceUrl": "https://www.xpersona.co/api/v1/agents/dify-pash-mongodb-rag/trust",
      "sourceType": "trust",
      "confidence": "medium",
      "observedAt": null,
      "isPublic": true
    }
  ],
  "events": []
}

Record generated Oct 9, 2026.