enable-vector-search
Activate vector search capabilities in Meilisearch to enable semantic similarity-based document retrieval using AI embeddings.
Instructions
Enable the vector search experimental feature in Meilisearch
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Implementation Reference
- src/tools/vector-tools.ts:25-36 (handler)The handler function that executes the tool logic: POSTs to Meilisearch /experimental-features endpoint to enable vectorStore experimental feature and returns the API response or handles errors.
async () => { try { const response = await apiClient.post('/experimental-features', { vectorStore: true, }); return { content: [{ type: "text", text: JSON.stringify(response.data, null, 2) }], }; } catch (error) { return createErrorResponse(error); } } - src/tools/vector-tools.ts:21-37 (registration)Direct registration of the 'enable-vector-search' MCP tool, including name, description, empty input schema, and inline handler.
server.tool( "enable-vector-search", "Enable the vector search experimental feature in Meilisearch", {}, async () => { try { const response = await apiClient.post('/experimental-features', { vectorStore: true, }); return { content: [{ type: "text", text: JSON.stringify(response.data, null, 2) }], }; } catch (error) { return createErrorResponse(error); } } ); - src/index.ts:68-68 (registration)Top-level registration call that invokes registerVectorTools to add the 'enable-vector-search' tool (among others) to the main MCP server instance.
registerVectorTools(server); - src/index.ts:11-11 (registration)Import of the vector-tools module containing the enable-vector-search tool registration.
import registerVectorTools from './tools/vector-tools.js';