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Meilisearch MCP Server

by devlimelabs

update-embedders

Configure embedders for vector search in Meilisearch indexes to enable semantic search capabilities.

Instructions

Configure embedders for vector search

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
indexUidYesUnique identifier of the index
embeddersYesJSON object containing embedder configurations

Implementation Reference

  • The main handler function for the 'update-embedders' tool. It parses the embedders JSON input, validates it as an object, and sends a PATCH request to the Meilisearch API to update the embedders configuration for the specified index.
    async ({ indexUid, embedders }) => { try { // Parse the embedders string to ensure it's valid JSON const parsedEmbedders = JSON.parse(embedders); // Ensure embedders is an object if (typeof parsedEmbedders !== 'object' || parsedEmbedders === null || Array.isArray(parsedEmbedders)) { return { isError: true, content: [{ type: "text", text: "Embedders must be a JSON object" }], }; } const response = await apiClient.patch(`/indexes/${indexUid}/settings/embedders`, parsedEmbedders); return { content: [{ type: "text", text: JSON.stringify(response.data, null, 2) }], }; } catch (error) { return createErrorResponse(error); } }
  • Zod schema defining the input parameters for the tool: indexUid (string) and embedders (string representing a JSON object).
    { indexUid: z.string().describe("Unique identifier of the index"), embedders: z.string().describe("JSON object containing embedder configurations"), },
  • Direct registration of the 'update-embedders' tool on the MCP server using server.tool(), specifying name, description, input schema, and handler function.
    server.tool( "update-embedders", "Configure embedders for vector search", { indexUid: z.string().describe("Unique identifier of the index"), embedders: z.string().describe("JSON object containing embedder configurations"), }, async ({ indexUid, embedders }) => { try { // Parse the embedders string to ensure it's valid JSON const parsedEmbedders = JSON.parse(embedders); // Ensure embedders is an object if (typeof parsedEmbedders !== 'object' || parsedEmbedders === null || Array.isArray(parsedEmbedders)) { return { isError: true, content: [{ type: "text", text: "Embedders must be a JSON object" }], }; } const response = await apiClient.patch(`/indexes/${indexUid}/settings/embedders`, parsedEmbedders); 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(server), which in turn registers the 'update-embedders' tool along with other vector tools.
    registerVectorTools(server);

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