Data & Storage · Integration
Bonsai Elasticsearch
Add Bonsai Elasticsearch to your product for your customers, and give your AI agents governed access to it.
Embed a Bonsai Elasticsearch integration so your customers can index and query their own clusters from inside your product, with governed agent access to the same data. Index mappings differ per customer and change without notice, so schema mapping is configuration rather than a code change and a release on your side, and bulk indexing is throttled so a large backfill does not overwhelm a cluster. fastn handles per-tenant credentials and API upkeep.
In your product
Embedded for your customers. Per-tenant auth, no per-customer code, maintained by fastn.
Let customers connect their own Bonsai cluster so your product reads and writes documents in their indices.
Run search queries and aggregations against a customer's index and render the results in your product.
Index and bulk-update documents from your product, with throttling so a backfill does not overload the cluster.
Read index mappings, document counts, and cluster health so operators see the state of their own search tier.
For your AI agents
Governed, audited access for the agents you build, through the MCP server.
An agent runs a query against a customer's index to ground an answer in their own documents.
An agent reindexes or updates documents within governed permissions, with the action audited.
An agent reads cluster and index health and explains why a query is slow.
Example prompt
Show index document counts and sizes for this cluster and flag any index with unassigned shards.
Set up Bonsai Elasticsearch in 4 steps
- 01Open the Bonsai Elasticsearch connector from your fastn dashboard.
- 02Have each customer authenticate their own Bonsai cluster with least-privilege credentials.
- 03Map the indices and document fields your product uses, then enable queries and indexing actions.
- 04Call them from your product, or expose them to an agent through the MCP server.
Why teams use the Bonsai Elasticsearch integration
What you get by embedding it with fastn instead of building it yourself.
- Ship a Bonsai Elasticsearch integration without building it. Your customers connect their own Bonsai Elasticsearch account inside your product and work their records, datasets and fields there, with no per-customer code on your side.
- Handle the part that actually costs time: schemas differ per customer and change without notice, and volumes can be large. fastn owns the auth, token refresh, rate limits, pagination and breaking-change fixes, so a Bonsai Elasticsearch update is not your on-call problem.
- One integration serves your product and your agents. The same governed Bonsai Elasticsearch connection powers in-product features and gives AI agents scoped, audited access, so you read and write your customers' data where it already lives without wiring it twice.
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How do I add a Bonsai Elasticsearch integration to my product?
Enable the Bonsai Elasticsearch connector in your fastn dashboard, then let each customer authenticate their own Bonsai Elasticsearch account. fastn handles the OAuth flow, token storage and refresh per tenant, so there is no Bonsai Elasticsearch client code in your app and no per-customer branch in your codebase. Setup is 4 steps.
Do my customers each connect their own Bonsai Elasticsearch account?
Yes. Every connection is scoped to the individual customer, so each authorises their own Bonsai Elasticsearch account and only ever sees their own records, datasets and fields. That per-tenant isolation is the point of an embedded integration: you support the long tail of customer setups without maintaining an integration per customer.
Can AI agents use this Bonsai Elasticsearch integration?
Yes. The same connection is exposed to your agents through the fastn MCP gateway, with permissions scoped per tenant and every call audited. An agent runs a query against a customer's index to ground an answer in their own documents.
Who maintains the Bonsai Elasticsearch integration?
fastn does. When Bonsai Elasticsearch changes an endpoint, deprecates a field or alters its auth, the fix lands in the connector rather than in your backlog, and your customers' connections keep working.
Does the Bonsai Elasticsearch integration adapt when a customer's schema changes?
Schema and field mapping is configuration per customer, so a change on their side is a mapping update rather than a code change and a release on yours.
How are large Bonsai Elasticsearch reads handled?
Pagination and throttling are handled for you, and initial backfills are rate-limited so a large import does not exhaust a customer's API allowance.
What can I build with the Bonsai Elasticsearch integration?
A common starting point: connect their own Bonsai cluster so your product reads and writes documents in their indices. Teams also use it for the other use cases listed above, and expose it to agents for governed reads and writes.
How much does the Bonsai Elasticsearch integration cost?
It is included. Pricing is based on connected accounts, not on how many connectors you enable, so adding Bonsai Elasticsearch does not change your per-connector cost. You can start free with 3 connected accounts.
Add Bonsai Elasticsearch to your product
Start free with 3 connected accounts. No sales call required, and no per-customer integration code.