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Review fraud cases with multiple MongoDB Atlas signals

Combine vector, full-text, hybrid-ranking, and graph retrieval to prepare an evidence-backed review of a pending transaction.

Goal

Ground a managed agent’s case summary in traceable Atlas signals and leave the decision to a human.

Steps

  1. Use $vectorSearch for similar decided cases, $search for exact entities/IDs, and $rankFusion to combine rankings. [mongo]
  2. Run $graphLookup over linked accounts; keep retrieval tools read-only and return transaction IDs, signal types, and evidence. [mongo]
  3. Have the agent propose approve/reject; pause risky cases at requires_action, then let the application write the decision and append-only audit record after review. [mongo]

How to verify

Vector, lexical, and relationship evidence link back to records; risky decisions pause for review; decisions and audit entries can be read back for this run.

Troubleshooting

If the Atlas version lacks `$rankFusion`, fuse rankings in the application; keep MongoDB credentials in the host handler, outside agent context and sandbox.

Permissions

Prerequisites

Permissions

Limitations

Model output may be incomplete or wrong; API and beta behavior can change, so verify against the pinned source and current service behavior.

Pinned upstream source

https://github.com/anthropics/anthropic-cookbook/blob/9c1e493ddd2b82df399d2a61b9c806c539e18be6/managed_agents/CMA_with_mongodb_atlas.ipynb

Repository
anthropics/anthropic-cookbook
File path
managed_agents/CMA_with_mongodb_atlas.ipynb
Pinned commit
9c1e493ddd2b82df399d2a61b9c806c539e18be6
Source checked
2026-10-14 · Reviewed against the pinned upstream source

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License: MIT

Main topic

Turn ecommerce campaign materials into a reviewable weekly brief

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