Agent-ready OpenAPI document · curated by JenticAI/MLEmbeddings Searchnone65 EndpointsREST
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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://jentic.com/install.sh?src=apis&api=%2Fapis%2Fmeilisearch.com%2Fmeilisearch-main" | sh2
Step 2: Agent machine
# On the machine where your agent runs (keep this separate from the instance):
curl -fsSL "https://jentic.com/install.sh?src=apis&api=%2Fapis%2Fmeilisearch.com%2Fmeilisearch-main" | 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
Jentic AI Readiness Score
This API is usable in Jentic One now. Its AI-readiness score against Jentic's framework shows where it stands today and where improvements would make it even easier for agents to use.
M
Meilisearch v1.0
- AI-Aware (A-)71/100
87
Foundational Compliance70
Developer Experience & Jentic Compatibility45
AI-Readiness & Agent Experience92
Agent Usability100
Security100
AI DiscoverabilityPowered by JenticScoring Framework 1.0.0 | Scoring Engine 0.4.0
Show dimension breakdown
87
Foundational Compliance
Base layer of spec validity and structural soundness.
Grade: ASignals: 4
97%
Lint Results
Aggregated quality score from linter diagnostics, weighted by severity.
100%
Resolution Completeness
Percentage of `$ref` references that resolve successfully.
100%
Specification Validity
Checks whether the API description parses successfully and conforms to its declared specification (e.g., OpenAPI).
50%
Structural Integrity
Structural correctness score based on schema issues using logarithmic dampening.
70
Developer Experience & Jentic Compatibility
Clarity, completeness, and ingestion readiness for developers and tooling.
Grade: A-Signals: 4
56%
Example Density
How richly the API is illustrated with examples.
99%
Example Validity
Percentage of examples that conform to their schemas.
25%
Response Coverage
Percentage of operations with complete response definitions (success, client error, server error).
100%
Tooling Readiness
Health of API ingestion, bundling, and resolution within Jentic pipelines.
45
AI-Readiness & Agent Experience
Semantic breadth, depth, and agent comprehension for AI systems.
Grade: DSignals: 4
16%
Description Coverage
Coverage of descriptions across API elements.
0%
Error Standardization
Coverage of RFC 9457 Problem Details for error responses.
97%
OperationId Quality
Coverage, uniqueness, and casing consistency of operationIds for AI inference.
67%
Summary Coverage
Coverage of summaries across operations/tags/info.
92
Agent Usability
Functional utility, complexity comfort, and AI orchestration readiness.
Grade: A+Signals: 1
92%
Complexity Comfort
Agent comfort level based on API operational and structural complexity.
100
Security
Trust, risk posture, and security compliance.
Grade: A+Signals: 1
100%
Authentication Strength
Average quality of security schemes based on authentication method strength (weakest link for OAuth2).
100
AI Discoverability
Findability, semantic richness, and reasoning readiness.
Grade: A+Signals: 1
100%
Descriptive Richness
Clarity and depth of descriptions across API elements.
Score it yourself
Every API in the directory is allowlisted, so you can re-score it with no key required.
npx @jentic/api-scorecard-cli score <openapi-url>Why Jentic?
What agents get from Jentic-routed access to this vendor.
Setup
Wiring Meilisearch by hand means pointing at your instance host, sending the master or scoped key as a bearer header, and hand-coding index, document, and search calls plus task polling. Through Jentic you install once, import Meilisearch from the API Directory, store the key once, and your agent calls it.
Permission scoping
Meilisearch puts the index id in the URL path (/indexes/{indexUid}/...), so a rule can pin your agent to one index: it can search and read documents there and nothing else. You choose the operations it may call, so index deletion or dump creation is included only if you add it.
Credential isolation
Your Meilisearch API key is stored once, encrypted, by your own Jentic One instance and injected as the Authorization Bearer header at execution time. It never enters the agent's prompt, logs, or context.
Intent-based discovery
Agents search Jentic by intent such as 'search a Meilisearch index' or 'add documents to an index', and Jentic returns the matching /indexes/{indexUid}/search operation with its query and filter schema so the agent calls the right endpoint without browsing the reference docs.
Related APIs
Alternatives and complements available in the Jentic catalogue.
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 with Jentic One, the self-hosted execution layer.
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.
Can I limit what my agent is allowed to do with the Meilisearch API?
Yes. Because Meilisearch puts the index id in the URL path (/indexes/{indexUid}/...), your self-hosted Jentic One instance lets you write a rule that pins the agent to a single index, so it can search and read documents there and nothing else. You decide which operations it may call, so destructive actions like index deletion or dump creation via /dumps are available only if you explicitly add them. The Meilisearch key is held by your own Jentic One instance and injected at execution time, so the agent never sees the credential and can only run the operations your rules permit.
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