Typesense Cloud uses GateRook’s Typesense connector. A cluster's load-balanced endpoint and a key with documents:search.
The screenshots show GateRook 2.0.0: the Typesense 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 Typesense Cloud, choose its card and select Continue to configure.
Copy the Typesense Cloud cluster's HTTPS connection endpoint and port, preferably its provided load-balanced endpoint.
Create an API key restricted to the intended collections and read actions. documents:search permits search; inspecting collection schemas or fetching documents can require their corresponding read actions.
Enter a Name, for example typesense-cloud-demo. Your AI app uses this name to choose the connection.
Enter the HTTPS cluster address in Server URL, including the Cloud connection port when specified.
Paste the scoped key into API key. Use a service key for the required reads rather than the Cloud dashboard login.
Limit Collections to the required collection names. Keep CA certificate (PEM) empty for the normal 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.
If searches work but schema discovery fails, check the key's collections:get permission. If a document fetch is denied, check documents:get. A search-only key may be suitable for searches while intentionally denying those other reads.
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 Typesense Cloud on the endpoint and passing its connection test, ask your AI app to use typesense-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 Typesense collections this key permits me to inspect.”
- “Describe the fields and default sorting field of the products collection.”
- “Search products for a selected term with a maximum of 10 results and explain the matching fields.”
| Tool | What it does | Starts as |
|---|---|---|
search_list_indexes | List the permitted Typesense collections and available document counts. | Read only |
search_describe_index | Show collection fields and their types, facet and sort settings, default sorting field and vector fields. | Read only |
search_query | Search text fields with filters, facets, sorting and pagination, or query a configured vector field. Specify the search or vector field when the collection configuration requires it. | 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.