Ollama MCP Server

import type { Ollama } from 'ollama'; import { ResponseFormat } from '../types.js'; import { formatResponse } from '../utils/response-formatter.js'; import type { ToolDefinition } from '../autoloader.js'; import { EmbedInputSchema } from '../schemas.js'; /** * Generate embeddings for text input */ export async function embedWithModel( ollama: Ollama, model: string, input: string | string[], format: ResponseFormat ): Promise<string> { const response = await ollama.embed({ model, input, }); return formatResponse(JSON.stringify(response), format); } export const toolDefinition: ToolDefinition = { name: 'ollama_embed', description: 'Generate embeddings for text input. Returns numerical vector representations.', inputSchema: { type: 'object', properties: { model: { type: 'string', description: 'Name of the model to use', }, input: { type: 'string', description: 'Text input. For batch processing, provide a JSON-encoded array of strings, e.g., ["text1", "text2"]', }, format: { type: 'string', enum: ['json', 'markdown'], default: 'json', }, }, required: ['model', 'input'], }, handler: async (ollama: Ollama, args: Record<string, unknown>, format: ResponseFormat) => { const validated = EmbedInputSchema.parse(args); return embedWithModel(ollama, validated.model, validated.input, format); }, };