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MCP Prompts Server

import { z } from 'zod'; export const workflowSchema = z.object({ id: z.string(), version: z.number().int().nonnegative(), steps: z.array(z.any()).default([]), }); export const promptSchemas = { list: z.object({ tags: z.union([z.array(z.string()), z.string()]).optional(), isTemplate: z.coerce.boolean().optional(), search: z.string().optional(), limit: z.coerce.number().int().min(1).max(100).default(50).optional(), offset: z.coerce.number().int().min(0).default(0).optional(), }), applyTemplate: z.object({ id: z.string(), variables: z.record(z.any()).default({}).optional(), }), update: z.object({ name: z.string().nullable().optional(), description: z.string().nullable().optional(), category: z.string().nullable().optional(), content: z.string().nullable().optional(), isTemplate: z.boolean().nullable().optional(), metadata: z.record(z.any()).nullable().optional(), tags: z.array(z.string()).nullable().optional(), variables: z.array(z.union([z.string(), z.object({ name: z.string() })])).nullable().optional(), }), }; export type PromptListQuery = z.infer<typeof promptSchemas.list>;

MCP directory API

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curl -X GET 'https://glama.ai/api/mcp/v1/servers/sparesparrow/mcp-prompts'

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