Data & Storage · Integration
Elasticsearch
Add Elasticsearch to your product for your customers, and give your AI agents governed access to it.
An Elasticsearch integration lets your product search a customer's own cluster rather than a copy you maintain. You write documents into indices, describe them with a mapping, shape how text is broken up with analyzers, then read with the Query DSL and aggregations. Mappings are the catch. A field's type is fixed once an index exists, so changing it means building a new index and reindexing behind an alias instead of altering anything in place. Search is also near real time rather than immediate: a document just written may not match until the index refreshes, which surprises anyone expecting read after write. fastn stores each cluster endpoint and API key per tenant, and follows Elastic's API changes for you.
In your product
Embedded for your customers. Per-tenant auth, no per-customer code, maintained by fastn.
Let a customer point your product at their own cluster so the documents you index stay in infrastructure they run.
Search with the Query DSL and summarise with aggregations, so counts come back computed rather than fetched.
Move a mapping change through a new index and an alias swap, since a field type cannot be altered in place.
Treat the refresh delay as expected, so a freshly written document that does not match yet is not raised as a bug.
For your AI agents
Governed, audited access for the agents you build, through the MCP server.
An agent runs a permitted query against one tenant's indices, and the indices it read are recorded.
An agent inspects a mapping before composing a query, so it filters on fields that are actually searchable.
An agent indexes or deletes documents within scoped permissions, so stale content stops being returned.
Example prompt
Search this index for documents matching the phrase and give me a count grouped by their status field.
Set up Elasticsearch in 4 steps
- 01Enable the Elasticsearch connector from your fastn dashboard.
- 02Have each customer authorise their own Elasticsearch account, so calls run under their credentials rather than a shared key.
- 03Decide which indices, mappings and documents your product needs, then confirm the field types you query, since a mapping is fixed at index creation.
- 04Call it from your product and expose it to your agents through the same governed connection.
Why teams use the Elasticsearch integration
What you get by embedding it with fastn instead of building it yourself.
- Ship an Elasticsearch integration without building it. Your customers connect their own 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 an Elasticsearch update is not your on-call problem.
- One integration serves your product and your agents. The same governed 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 an Elasticsearch integration to my product?
Enable the Elasticsearch connector in your fastn dashboard, then let each customer authenticate their own Elasticsearch account. fastn handles the OAuth flow, token storage and refresh per tenant, so there is no 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 Elasticsearch account?
Yes. Every connection is scoped to the individual customer, so each authorises their own 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 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 permitted query against one tenant's indices, and the indices it read are recorded.
Who maintains the Elasticsearch integration?
fastn does. When 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 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 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 Elasticsearch integration?
A common starting point: let a customer point your product at their own cluster so the documents you index stay in infrastructure they run. 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 Elasticsearch integration cost?
It is included. Pricing is based on connected accounts, not on how many connectors you enable, so adding Elasticsearch does not change your per-connector cost. You can start free with 3 connected accounts.
Add Elasticsearch to your product
Start free with 3 connected accounts. No sales call required, and no per-customer integration code.