Meilisearch Cloud uses GateRook’s Meilisearch connector. A project's URL and a search key.
The screenshots show GateRook 2.0.0: the Meilisearch Cloud form, the endpoint selector, and this connector’s actual tool preview. The form and preview have not been saved. Select a screenshot to open it at full size.
1. Create a connection and enter the settings
In GateRook, open Connections, select Add connection, search for Meilisearch Cloud, choose its card and select Continue to configure.
Copy the Meilisearch Cloud project's HTTPS endpoint and create an API key restricted to the required indexes and read actions.
A default search key is intended for search requests. Inspecting indexes, settings or documents can require additional specific read permissions; grant those deliberately rather than using the master key for routine analysis.
Enter a Name, for example meilisearch-cloud-demo. Your AI app uses this name to choose the connection.
Enter the project endpoint in Server URL. Select API key for Authentication and paste the scoped key into API key.
Restrict Indexes to the index identifiers the agent should inspect. These must match the actual index UIDs, which can differ from a display label.
Keep CA certificate (PEM) empty for the usual publicly trusted Cloud endpoint.
Choose Development, Staging or Production to match the service. Review the connector’s limit and access settings before continuing.
2. Test the connection and add it to an endpoint
Select Continue to test. GateRook checks the settings from your computer. Review the result and resolve any connection, certificate or permission error before continuing.
Run Continue to test, then try a bounded search. If search works but index inspection or document retrieval is denied, check the relevant API-key actions. A 403 for a metadata operation does not imply the search key is invalid.
After the test passes, select Continue to add to an endpoint. Choose the endpoint your AI app uses, review its tool modes, then select Save connection. GateRook offers default as the starter endpoint.
3. Use the connection from your AI IDE
After saving Meilisearch Cloud on the endpoint and passing its connection test, ask your AI app to use meilisearch-cloud-demo, or the name you chose. If its tools are missing, confirm the endpoint assignment and refresh the MCP connection or start a new chat.
The preview below shows this connector’s default tools before saving. The table explains what each tool can do; connection settings, credentials and endpoint policies can restrict access further.
Start with a small read request. Replace example resource names with existing resources your connection may access. Open Activity after the call to inspect its connection, tool, arguments, policy decision and result metadata.
Ask your AI, for example
- “List the search indexes this key is permitted to inspect.”
- “Search the products index for a specific term and return at most 10 hits.”
- “Inspect the filterable and sortable attributes of the products index without changing settings.”
| Tool | What it does | Starts as |
|---|---|---|
search_list_indexes | List the permitted Meilisearch indexes and available document counts. | Read only |
search_describe_index | Show the primary key, readable searchable/filterable/sortable attributes, ranking rules, configured embedders and index statistics. | Read only |
search_query | Search with text, filters, facets, sorting and pagination. Vector or hybrid search requires a configured embedder; choose it when the index has more than one. | Read only |
search_get_documents | Documents by id, up to 100. | Read only |
search_index_documents | Adds or replaces up to 100 documents of one index, or merges their fields into existing ones. You approve the exact documents. Never retried. | Approval |
search_delete_documents | Deletes documents by id, up to 1,000 of one index. You approve the exact ids; nothing else is deleted. Never retried. | Approval |
You can change each tool’s mode on the endpoint. Every call your AI makes appears in Activity.