Indices and records of Algolia: search with filters and facets, records by objectID. Record writes and deletes wait for approval.
The screenshots show GateRook 2.0.0: the Algolia 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 Algolia, choose its card and select Continue to configure.
Find the Algolia Application ID and create an API key limited to the indexes and operations you need.
A search-only key is suitable for searches. Listing and browsing indexes may require additional read permissions, such as listIndexes and browse; an Admin API key is unnecessary for a search-only workflow.
Enter a Name, for example algolia-demo. Your AI app uses this name to choose the connection.
Enter Application ID and API key from the intended Algolia application.
Restrict Indices to the intended index names or patterns. The key’s own index restrictions continue to apply.
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.
If searches work but listing or describing indexes fails, check the key’s allowed operations. Confirm that Application ID, API key and index name all belong to the same application.
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 Algolia on the endpoint and passing its connection test, ask your AI app to use algolia-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 indexes available through algolia-demo.”
- “Search the products index on algolia-demo for wireless headphones and return five matches.”
- “Using algolia-demo, retrieve the product with objectID product-123.”
| Tool | What it does | Starts as |
|---|---|---|
search_list_indexes | List the permitted Algolia indexes and available index counts. | Read only |
search_describe_index | Show readable search, facet, ranking and replica settings and the available object count. Settings require the key’s settings permission. | Read only |
search_query | Search with words, filters, facets and pagination. Choose a replica index for a different sort order; this connector does not accept per-query sorting or vector input. | 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.