enable-vector-search
Activate vector search functionality in Meilisearch to enable semantic similarity-based document retrieval.
Instructions
Enable the vector search experimental feature in Meilisearch
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Input Schema (JSON Schema)
{
"$schema": "http://json-schema.org/draft-07/schema#",
"properties": {},
"type": "object"
}
Implementation Reference
- src/tools/vector-tools.ts:25-36 (handler)The handler function executes the tool logic: POST to Meilisearch /experimental-features with vectorStore: true, returns response or error.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)Registers the enable-vector-search tool on the MCP server with no input parameters and the inline handler function.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)Main server initialization calls registerVectorTools, which registers the enable-vector-search tool among others.registerVectorTools(server);