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Elasticsearch vs Typesense

Typesense scores higher on the AgentReady, 50/100 against 44/100. They differ on 11 of the 41 signals. Which ones decides whether an agent can adopt them without a person watching.

What each one is

Elasticsearch. Elastic is a company providing the Elasticsearch Platform for search, observability, and security.

Typesense. Typesense is a lightning-fast, open-source search engine designed to deliver instant, relevant search results.

Where Elasticsearch is ahead

Elasticsearch passes mcp discoverable, and Typesense does not. That is discover, whether an agent can find the product at all without being told it exists.

It also holds adopt: mcp integration available. Typesense misses it.

And on operate, observable execution. Typesense misses it.

Where Typesense is ahead

Typesense passes llms.txt published, and Elasticsearch does not. That is discover, whether an agent can find the product at all without being told it exists.

It also holds understand: authentication documented, pricing understandable and limits / constraints documented. Elasticsearch misses those.

And on adopt, no mandatory sales call, free trial or free allowance and copyable quickstart. Elasticsearch misses those.

Finally, on operate, structured, predictable output. Elasticsearch misses it.

What neither does

Both fail llms-full.txt / full agent docs, structured api reference, openapi / spec quality, request examples provided, response examples provided, errors and status codes documented, self-service signup, agent-compatible signup flow, programmatic credential creation, fast time to first request, machine-readable errors, retry behavior documented, idempotency support, rate-limit behavior predictable, agent compatibility verified. If your agent needs any of those, you will be building it yourself either way.

Score, pillar by pillar

The AgentReady splits into four pillars, scored separately, because a product can be easy to find and still impossible to adopt.

Discover. Elasticsearch leads 87 to 80. Elasticsearch misses llms.txt published, llms-full.txt / full agent docs; Typesense misses llms-full.txt / full agent docs, mcp discoverable.

Understand is whether an agent can read the docs and work out how the API behaves before calling it. Typesense leads 38 to 15. Elasticsearch misses structured api reference, openapi / spec quality, authentication documented, pricing understandable, request examples provided, response examples provided, errors and status codes documented, limits / constraints documented; Typesense misses structured api reference, openapi / spec quality, request examples provided, response examples provided, errors and status codes documented.

Adopt. Typesense leads 45 to 40. Elasticsearch misses self-service signup, no mandatory sales call, agent-compatible signup flow, programmatic credential creation, free trial or free allowance, fast time to first request, copyable quickstart; Typesense misses self-service signup, agent-compatible signup flow, programmatic credential creation, fast time to first request, mcp integration available.

Operate. Both sit at 35/100 here. Elasticsearch misses structured, predictable output, machine-readable errors, retry behavior documented, idempotency support, rate-limit behavior predictable, agent compatibility verified; Typesense misses machine-readable errors, retry behavior documented, idempotency support, rate-limit behavior predictable, observable execution, agent compatibility verified.

Pricing

Elasticsearch does not publish a machine-readable starting price. Typesense does not publish one and has a free tier.

Signal by signal

Which to pick

Typesense clears more of the signals an agent needs, so it is the safer default for unattended use. Full profiles: Elasticsearch and Typesense. Alternatives to each: Elasticsearch, Typesense.

An agent can fetch this as data: POST /v1/compare {"slugs": ["elastic", "typesense"]}