Do coding agents recommend Meilisearch?
Meilisearch was chosen in 9% of 459 judged search sessions, ranking fourth. Measured with Claude Code, Codex and Cursor.
Meilisearch was chosen in 9% of 459 judged search sessions, ranking fourth. It was also raised as a candidate in 219 further sessions without being chosen.
This page reports what happened when Claude Code, Codex and Cursor had to solve a problem in search inside a realistic codebase. Not what a chat assistant says about Meilisearch. What an agent actually installed.
The numbers
| Category | Search |
| Sessions in the category | 459 |
| Sessions where Meilisearch was chosen | 40 |
| Install share | 9% |
| Rank in category | 4 of 16 |
| Codebases it won in | 8 |
| Raised as a candidate, not chosen | 219 |
| Chosen when considered | 15% |
| Site | meilisearch.com |
By agent
The three agents treat Meilisearch very differently. Cursor chose it in 17% of its sessions in this category and Codex in 2%, a spread of 15 points.
| Agent | Sessions | Chose Meilisearch | Share |
|---|---|---|---|
| Claude Code | 152 | 11 | 7% |
| Codex | 155 | 3 | 2% |
| Cursor | 152 | 26 | 17% |
A single blended install share would report the midpoint and hide both ends. If most of your users run Codex, your real position here is 2%, not 9%.
By who was asking
Meilisearch performs similarly across the four kinds of buyer, from 0% to 13%. That is unusual: the category leader changed with the persona in 14 of the 18 categories we measured.
| Who is asking | Sessions | Chose Meilisearch | Share |
|---|---|---|---|
| Vibe coder | 65 | 0 | 0% |
| Junior developer | 193 | 22 | 11% |
| Senior engineer | 106 | 14 | 13% |
| Enterprise team | 95 | 4 | 4% |
What Meilisearch was up against
The full ranking in search, from the same sessions:
| # | Product | Runs won | Share |
|---|---|---|---|
| 1 | Built in-house (no product adopted) | 106 | 23% |
| 2 | Postgres Full-Text Search | 79 | 17% |
| 3 | OpenSearch | 59 | 13% |
| 4 | Typesense | 42 | 9% |
| 5 | Meilisearch (this page) | 40 | 9% |
| 6 | Oracle Indexed Search | 23 | 5% |
| 7 | Algolia | 23 | 5% |
| 8 | Elasticsearch | 22 | 5% |
What this means
This is an integration problem, not a presence problem. Agents raised Meilisearch in 219 sessions and chose it in 40, so it reaches the shortlist and then loses. Something at the last step is costing the session, and in our data that is usually a quickstart that does not run when pasted, documentation describing an interface that changed, or a package name that does not match the product name.
That is the cheaper of the two problems to have. The reason is written down in each losing transcript.
Where these numbers come from
The 459 sessions in search are part of a published set of 5,292, run with real coding agents inside realistic codebases and judged blind. The full method is on one page: how we measured this.
Every search run can be replayed on the board.
If you work on Meilisearch: the judge recorded a reason for every session where it was raised and passed over. Those reasons are in the transcripts.
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Common questions
Do coding agents recommend Meilisearch?
Yes. Meilisearch was chosen in 40 of the 459 judged sessions in search, a 9% install share, ranking fourth in its category.
Does Claude Code recommend Meilisearch?
In 11 of the 152 sessions in search run with Claude Code, which is 7%.
Do different coding agents treat Meilisearch differently?
Yes, and by a wide margin. Cursor chose it in 17% of its runs and Codex in 2%.
How was this measured?
Real coding agents at pinned versions were run in sandboxes inside 51 realistic codebases and asked to solve real tasks. A simulated project owner approved or questioned each recommendation before any code was written, and a judge from a model family that builds none of the agents read every session blind.
How often is Meilisearch considered but not chosen?
It was raised as a candidate in 219 sessions without being chosen, and chosen in 40. That is a 15% conversion from considered to chosen.
Where this comes from
Armature ran 5,292 judged sessions with Claude Code, Codex and Cursor inside 51 realistic codebases, and published every run. The numbers on this page come from that work.