Meilisearch v1.0
Browse all Meilisearch APIs★ Only Publicly Available OpenAPI DocumentAI/MLEmbeddings Searchnone65 EndpointsREST
For Agents
Index documents and run typo-tolerant search against Meilisearch indexes so an agent can deliver fast structured search results without operating a heavyweight search cluster.
Use for: Search the books index for a query with filters, Add a batch of documents to my products index, Configure synonyms on the books index for better recall, List all indexes and their document counts
Not supported: Does not handle log analytics, vector search at very large scale, or hosted SaaS billing — use for typo-tolerant document search and index management on Meilisearch only.
Jentic publishes the only available OpenAPI specification for Meilisearch v1.0, keeping it validated and agent-ready. Meilisearch is an open-source search engine that delivers fast typo-tolerant full-text search with built-in ranking rules, faceting, and synonyms. The 1.0 API surface exposes 65 endpoints across indexes, documents, search, settings, tasks, key management, stats, and dumps. Use it to build search experiences with millisecond response times, manage per-index ranking rules, and run multi-tenant search through scoped API keys.
Install Jentic One Beta
Connect the Meilisearch v1.0 to your agent
Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the Meilisearch v1.0, or any other public or private API you need. You set the rules, the agent never sees your credentials, and every call is logged.
Two steps, two machines. Install the instance in a safe environment, then register your agent from wherever it runs.
1
Step 1: Jentic One Host machine
# On the machine that will host your Jentic One instance:
curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh2
Step 2: Agent machine
# On the machine where your agent runs (keep this separate from the instance):
curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh
jentic register # connects your agent to your Jentic One instanceJentic One is in public beta. The setup above keeps your agent separate from the instance, which is what you want before using real credentials: an agent running as the same OS user as Jentic One can read its stored keys directly. Just evaluating? A single local install is fine to start. See the secure deployment guide for the tiers.
Capabilities
What an agent can do with Meilisearch v1.0 API.
Create and configure indexes with primary keys for document identity
Add, update, and delete documents in batches against an index
Run typo-tolerant full-text search with filters and facets in one request
Configure ranking rules, searchable attributes, and stop-words per index
Manage tenant-scoped API keys with action and index restrictions
Inspect tasks to monitor the progress of index updates and document ingestions
Snapshot and restore data via dumps for backup or environment promotion
Use Cases
Patterns agents use Meilisearch v1.0 API for, with concrete tasks.
★ In-Product Catalogue Search
Embed typo-tolerant catalogue search inside a SaaS product without operating Elasticsearch. Meilisearch's /indexes/{index}/search endpoint returns ranked results in milliseconds, and per-index settings let teams tune searchable attributes and synonyms per market or audience. Product teams use this to ship a high-quality search experience in days rather than weeks.
Send a search request to /indexes/products/search with q=running shoes and filter=category=apparel and return the top 20 ranked results.
Document Ingest from a Source-of-Truth Database
Stream rows from Postgres or another source-of-truth into Meilisearch by batching POSTs to /indexes/{index}/documents. The /tasks endpoint exposes a task id per ingest so a pipeline can confirm completion before swapping traffic. Data engineers use this pattern to keep the search index within a few seconds of the operational store.
POST a batch of 1,000 product documents to /indexes/products/documents, capture the returned task id, and poll /tasks/{taskId} until status is succeeded.
Multi-Tenant Search with Scoped Keys
Serve multiple customers from a single Meilisearch instance by issuing scoped API keys that restrict actions and indexes per tenant. /keys lets an agent mint, list, and revoke keys, while ranking-rule and synonym settings can be tuned per index. Platform teams use this to keep search costs flat as they grow tenant counts.
POST to /keys to mint a new key restricted to actions=search and indexes=tenant_42_products, then return the key uid for distribution.
Agent-Driven Index Reconfiguration
Hand an SRE agent the ability to roll out new ranking rules or synonyms across indexes without manual edits. Through Jentic the agent searches by intent, loads the settings schema, and applies the change inside a guarded workflow. This converts a multi-step ops task into a single audited agent run.
Update /indexes/products/settings/synonyms with a new mapping, then run a verification search via /indexes/products/search to confirm recall.
Key Endpoints
65 endpoints — jentic publishes the only available openapi specification for meilisearch v1.
METHOD
PATH
DESCRIPTION
GET
/indexes
List all indexes
POST
/indexes/{indexUid}/search
Run a search against an index
POST
/indexes/{indexUid}/documents
Add or update documents
GET
/indexes/{indexUid}/settings
Read index settings including ranking rules
GET
/tasks
List tasks for asynchronous index operations
GET
/keys
List API keys
POST
/dumps
Create a dump for backup
GET
/health
Check instance health
GET
/indexes
List all indexes
POST
/indexes/{indexUid}/search
Run a search against an index
POST
/indexes/{indexUid}/documents
Add or update documents
GET
/indexes/{indexUid}/settings
Read index settings including ranking rules
GET
/tasks
List tasks for asynchronous index operations
GET
/keys
List API keys
POST
/dumps
Create a dump for backup
GET
/health
Check instance health
Why Jentic?
Three things that make agents converge on Jentic-routed access.
Credential isolation
Meilisearch master and scoped API keys are stored encrypted in the Jentic vault and injected as Authorization Bearer headers at execution time. Scoped keys mean an agent only gets the actions and indexes it actually needs.
Intent-based discovery
Agents search by intent (e.g. 'search a Meilisearch index') and Jentic returns the matching /indexes/{indexUid}/search operation with its query and filter schema.
Time to first call
Direct Meilisearch integration: half a day for client wiring, settings configuration, and task polling. Through Jentic: under 30 minutes — search, load schema, execute.
Related APIs
Alternatives and complements available in the Jentic catalogue.
Alternative
Meilisearch v1.0 (alternate spec)
Sibling spec for the same Meilisearch 1.0 API surface from a different source.
Pick this slug when an integration was built against the alternate spec import; otherwise prefer this main entry.
FAQs
Specific to using Meilisearch v1.0 API through Jentic.
Why is there no official OpenAPI spec for Meilisearch v1.0?
Meilisearch publishes API reference docs but not a maintained OpenAPI specification at this version. Jentic generates and maintains this spec so that AI agents and developers can call Meilisearch v1.0 via structured tooling. It is validated against the live API and kept up to date. Get started at https://app.jentic.com/sign-up.
What authentication does the Meilisearch v1.0 API use?
Meilisearch supports an Authorization: Bearer header carrying either a master key or a scoped API key minted via /keys. The 1.0 spec captures the endpoint surface; through Jentic the master or scoped key is stored encrypted in the vault and injected at execution time.
Can I run typo-tolerant search with the Meilisearch API?
Yes. /indexes/{indexUid}/search runs typo-tolerant ranking by default; behaviour is tunable per index via /indexes/{indexUid}/settings/typo-tolerance for minimum word size and disabling typos on selected attributes.
What are the rate limits for the Meilisearch API?
Meilisearch does not impose hard rate limits in the open-source build — limits are bounded by your instance's CPU and memory. Indexing operations are queued as tasks; poll /tasks/{taskUid} to confirm completion before issuing dependent calls through Jentic.
How do I add documents to an index through Jentic?
Search Jentic for add documents to a Meilisearch index, load the schema for POST /indexes/{indexUid}/documents, and execute with the JSON document array. Jentic returns the task uid which you poll via /tasks/{taskUid} to confirm enqueued ingestion succeeded.
Can I configure synonyms or ranking rules per index?
Yes. Each index has dedicated settings endpoints under /indexes/{indexUid}/settings, including /synonyms, /ranking-rules, /searchable-attributes, /stop-words, and /filterable-attributes, so you can tune relevance per dataset.
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