manage-mcp（manage MCP 搜索）

Manage MCP

Complete skill for managing Model Context Protocol (MCP) servers in Nuxt applications. Setup, create, customize with middleware and handlers, review, and troubleshoot.

When to Use

• Setup: "Setup an MCP server in my Nuxt app"
• Create: "Create a tool to calculate BMI" / "Add a resource to read the README"
• Customize: "Add authentication to my MCP server" / "Create middleware for rate limiting"
• Review: "Review my MCP implementation" / "Check for best practices"
• Troubleshoot: "My auto-imports aren't working" / "Cannot connect to endpoint"
• Test: "Create tests for my MCP tools"

Setup MCP Server

Installation

Automatic (recommended):

npx nuxt module add mcp-toolkit

Manual:

pnpm add -D @nuxtjs/mcp-toolkit zod

Add to nuxt.config.ts:

export default defineNuxtConfig({
  modules: ['@nuxtjs/mcp-toolkit'],
  mcp: {
    name: 'My MCP Server',
  },
})

Directory Structure

server/mcp/
├── tools/           # Actions AI can perform
│   ├── admin/       # Subdirectory → group: 'admin'
│   └── content/     # Subdirectory → group: 'content'
├── resources/       # Data AI can read
└── prompts/         # Message templates

Verification

1. Start: pnpm dev
2. Check: http://localhost:3000/mcp (should redirect)
3. Open DevTools (Shift+Alt+D) → MCP tab

Create Tools

Tools are functions AI assistants can call.

Basic Structure

import { z } from 'zod'

export default defineMcpTool({
  description: 'What the tool does',
  inputSchema: {
    param: z.string().describe('Parameter description'),
  },
  handler: async ({ param }) => {
    return 'Result' // or return { foo: 'bar' } for JSON; full CallToolResult still supported
  },
})

Input Patterns

// Required
name: z.string().describe('User name')

// Optional with default
limit: z.number().default(10).describe('Max results')

// Enum
format: z.enum(['json', 'xml']).describe('Format')

// Array
tags: z.array(z.string()).describe('Tags')

Error Handling

if (!param) {
  throw createError({ statusCode: 400, message: 'Error: param required' })
}

Annotations

Behavioral hints that help MCP clients decide when to prompt for confirmation:

export default defineMcpTool({
  annotations: {
    readOnlyHint: true,     // Only reads data, no side effects
    destructiveHint: false,  // Does not delete or destroy data
    idempotentHint: false,   // Multiple calls may have different effects
    openWorldHint: false,    // No external API calls
  },
  // ...
})

Common patterns: read-only tools → readOnlyHint: true, create → idempotentHint: false, update → idempotentHint: true, delete → destructiveHint: true, idempotentHint: true.

Input Examples

Type-safe usage examples that help AI models fill in parameters correctly:

export default defineMcpTool({
  inputSchema: {
    title: z.string().describe('Todo title'),
    content: z.string().optional().describe('Description'),
  },
  inputExamples: [
    { title: 'Buy groceries', content: 'Milk, eggs, bread' },
    { title: 'Fix login bug' },
  ],
  // ...
})

Groups and Tags

Organize tools with group and tags for filtering and progressive discovery:

export default defineMcpTool({
  group: 'admin',
  tags: ['destructive', 'user-management'],
  description: 'Delete a user account',
  // ...
})

Groups are auto-inferred from subdirectories: server/mcp/tools/admin/delete-user.ts → group: 'admin'. Explicit group takes precedence.

Caching

export default defineMcpTool({
  cache: '5m',  // 5 minutes
  // ...
})

See detailed examples →

Create Resources

Resources expose read-only data.

File Resource

import { readFile } from 'node:fs/promises'

export default defineMcpResource({
  description: 'Read a file',
  uri: 'file:///README.md',
  mimeType: 'text/markdown',
  handler: async (uri: URL) => {
    const content = await readFile('README.md', 'utf-8')
    return {
      contents: [{
        uri: uri.toString(),
        text: content,
        mimeType: 'text/markdown',
      }],
    }
  },
})

API Resource

export default defineMcpResource({
  description: 'Fetch API data',
  uri: 'api:///users',
  mimeType: 'application/json',
  cache: '5m',
  handler: async (uri: URL) => {
    const data = await $fetch('https://api.example.com/users')
    return {
      contents: [{
        uri: uri.toString(),
        text: JSON.stringify(data, null, 2),
        mimeType: 'application/json',
      }],
    }
  },
})

Dynamic Resource

import { z } from 'zod'

export default defineMcpResource({
  description: 'Fetch by ID',
  uriTemplate: {
    uriTemplate: 'user:///{id}',
    arguments: {
      id: z.string().describe('User ID'),
    },
  },
  handler: async (uri: URL, args) => {
    const user = await fetchUser(args.id)
    return {
      contents: [{
        uri: uri.toString(),
        text: JSON.stringify(user),
        mimeType: 'application/json',
      }],
    }
  },
})

See detailed examples →

Create Prompts

Prompts are reusable message templates.

Static Prompt

export default defineMcpPrompt({
  description: 'Code review',
  handler: async () => {
    return {
      messages: [{
        role: 'user',
        content: {
          type: 'text',
          text: 'Review this code for best practices.',
        },
      }],
    }
  },
})

Dynamic Prompt

import { z } from 'zod'

export default defineMcpPrompt({
  description: 'Custom review',
  inputSchema: {
    language: z.string().describe('Language'),
    focus: z.array(z.string()).describe('Focus areas'),
  },
  handler: async ({ language, focus }) => {
    return {
      messages: [{
        role: 'user',
        content: {
          type: 'text',
          text: `Review my ${language} code: ${focus.join(', ')}`,
        },
      }],
    }
  },
})

See detailed examples →

Middleware & Handlers

Customize MCP behavior with middleware and handlers for authentication, logging, rate limiting, and more.

Basic Middleware

// server/mcp/middleware.ts
export default defineMcpMiddleware({
  handler: async (event, next) => {
    console.log('MCP Request:', event.path)

    // Check auth
    const token = event.headers.get('authorization')
    if (!token) {
      return createError({ statusCode: 401, message: 'Unauthorized' })
    }

    return next()
  },
})

Custom Handler

// server/mcp/handlers/custom.ts
export default defineMcpHandler({
  name: 'custom-mcp',
  route: '/mcp/custom',
  handler: async (event) => {
    return {
      tools: await loadCustomTools(),
      resources: [],
      prompts: [],
    }
  },
})

Common Use Cases

• Authentication: API keys, JWT tokens
• Rate limiting: Per IP or per user
• Logging: Request/response tracking
• CORS: Cross-origin configuration
• Multiple endpoints: Public/admin separation

See detailed middleware guide →

Interactive Composables

useMcpElicitation()

Ask the connected client for structured input mid-request, or send the user to a URL.

import { z } from 'zod'

export default defineMcpTool({
  name: 'create_release',
  inputSchema: { name: z.string() },
  handler: async ({ name }) => {
    const elicit = useMcpElicitation()

    const result = await elicit.form({
      message: `Pick a channel for "${name}"`,
      schema: {
        channel: z.enum(['stable', 'beta']).describe('Release channel'),
      },
    })

    if (result.action !== 'accept') return 'Cancelled.'
    return `Released "${name}" on ${result.content.channel}.`
  },
})

• Form mode: pass a Zod raw shape, the response is validated and typed.
• URL mode: elicit.url({message, url}) — opt-in per spec, gate with elicit.supports('url').
• Confirm: await elicit.confirm('Continue?') returns a boolean.
• Capability check: elicit.supports('form' | 'url') — always false before init completes.
• Errors: catch McpElicitationError (code: 'unsupported' | 'invalid-schema' | 'invalid-response') to fall back when the client doesn't support elicitation.
• Schema must be a flat object of primitives (string/number/boolean), enums, or string-enum arrays — nested objects are rejected by the spec.

See elicitation docs →

Observability

useMcpLogger()

Split-channel logger: notify the connected client and capture structured wide events (powered by evlog when installed — add it with your package manager; see the Logging guide).

export default defineMcpTool({
  name: 'charge_card',
  inputSchema: { userId: z.string(), amount: z.number().int() },
  handler: async ({ userId, amount }) => {
    const log = useMcpLogger('billing')

    // → server-side wide event (dev terminal + drains)
    log.set({ user: { id: userId }, billing: { amount } })
    log.event('charge_started', { amount })

    // → MCP client (Inspector / Cursor / Claude)
    await log.notify.info({ msg: 'starting charge', amount })

    const receipt = await charge(userId, amount)
    return `Charged ${amount}.`
  },
})

• Client channel (log.notify): notify(level, data, logger?) plus notify.debug / notify.info / notify.warning / notify.error shortcuts. Always resolves, never throws — respects the client's logging/setLevel per session. Works with or without evlog.
• Server channel (requires evlog installed): set(fields) accumulates context onto the request's wide event; event(name, fields?) captures a discrete event; evlog exposes the full request logger. These throw McpObservabilityNotEnabledError when observability is off.
• Wide events are auto-tagged with mcp.transport, mcp.route, mcp.session_id, mcp.method, mcp.request_id, and mcp.tool / mcp.resource / mcp.prompt based on the JSON-RPC payload (no user code required).
• mcp.logging modes: omit (auto-detect — on if evlog installed), true / object (force on, throws at build if missing), false (force off — notify keeps working).

Ship to a backend (drains)

Ship every MCP wide event to Axiom, Sentry, OTLP, HyperDX, Datadog, Better Stack, or PostHog with a single Nitro plugin. Each adapter lives under evlog/adapters/* and is registered on the evlog:drain hook:

import { createAxiomDrain } from 'evlog/adapters/axiom'

export default defineNitroPlugin((nitroApp) => {
  nitroApp.hooks.hook('evlog:drain', createAxiomDrain())
})

The hook is additive — register multiple drains in parallel. Custom drains are just (ctx) => Promise<void> registered on the same hook.

See evlog.dev → for the full list of adapters, env-var conventions, sampling, and redaction.

See logging docs →

Review & Best Practices

MCP code review (agents & humans)

When reviewing or modernizing server/mcp/**, walk through this list so implementations stay aligned with current toolkit behavior and Nuxt server typing.

Tool return values

• Prefer direct returns: string, number, boolean, plain objects, or arrays. The module wraps them into CallToolResult (JSON is pretty-printed for objects).
• Avoid deprecated helpers unless you must support very old code: textResult, jsonResult, errorResult — migrate to direct values and throw createError({statusCode, message}) (or throw new Error(...)) for failures.
• Reserve full CallToolResult (content, structuredContent, embedded resources, isError) for cases that need explicit MCP shapes.

Async context & server composables

• useMcpServer() needs nitro.experimental.asyncContext: true in nuxt.config. If TypeScript reports Promise<McpServerHelper> (common with server auto-imports), use const mcp = await useMcpServer() before registerTool / removeTool / etc.
• useMcpSession() / useEvent(): await if the IDE or vue-tsc indicates a Promise; keep session and event usage inside tool, resource, or prompt handlers.

Hygiene

• Every await on a Promise-backed call in handlers (DB, fetch, composables that return promises).
• Zod: required .describe() on schema fields for good model UX; use inputExamples for non-trivial shapes.
• Annotations: set readOnlyHint, destructiveHint, idempotentHint, openWorldHint honestly.
• Run pnpm eslint / nuxi typecheck on the app after refactors (catch deprecated APIs and missing await early).

Tool Checklist

✅ Use kebab-case filenames ✅ Add .describe() to all Zod fields ✅ Return plain values or throw createError for failures (not deprecated errorResult) ✅ Add caching for expensive ops ✅ Clear, actionable descriptions ✅ Validate all inputs ✅ Add annotations (readOnlyHint, destructiveHint, etc.) ✅ Add inputExamples for tools with optional/complex params ✅ nitro.experimental.asyncContext: true when using useMcpServer()

❌ Generic descriptions ❌ Skip error handling ❌ Expose sensitive data ❌ No input validation ❌ textResult / jsonResult / errorResult in new code (deprecated)

Resource Checklist

✅ Descriptive URIs (config:///app) ✅ Set appropriate MIME types ✅ Enable caching when needed ✅ Handle errors gracefully ✅ Use URI templates for collections

❌ Unclear URI schemes ❌ Skip MIME types ❌ Expose sensitive data ❌ Return huge datasets without pagination

Prompt Checklist

✅ Clear descriptions ✅ Meaningful parameters ✅ Default values where appropriate ✅ Single, focused purpose ✅ Reusable design

❌ Overly complex ❌ Skip descriptions ❌ Mix multiple concerns

Troubleshooting

Auto-imports Not Working

Fix:

1. Check modules: ['@nuxtjs/mcp-toolkit'] in config
2. Restart dev server
3. Files in server/mcp/ directory?
4. Run pnpm nuxt prepare

Endpoint Not Accessible

Fix:

1. Dev server running?
2. Test: curl http://localhost:3000/mcp
3. Check enabled: true in config
4. Review server logs

Validation Errors

Fix:

• Required fields provided?
• Types match schema?
• Use .optional() for optional fields
• Enum values exact match?

Tool Not Discovered

Fix:

• File extension .ts or .js?
• Using export default?
• File in correct directory?
• Restart dev server

See detailed troubleshooting →

Testing with Evals

Setup

pnpm add -D evalite vitest @ai-sdk/mcp ai

Add to package.json:

{
  "scripts": {
    "eval": "evalite",
    "eval:ui": "evalite watch"
  }
}

Basic Test

Create test/mcp.eval.ts:

import { experimental_createMCPClient as createMCPClient } from '@ai-sdk/mcp'
import { generateText } from 'ai'
import { evalite } from 'evalite'
import { toolCallAccuracy } from 'evalite/scorers'

evalite('MCP Tool Selection', {
  data: async () => [
    {
      input: 'Calculate BMI for 70kg 1.75m',
      expected: [{
        toolName: 'bmi-calculator',
        input: { weight: 70, height: 1.75 },
      }],
    },
  ],
  task: async (input) => {
    const mcp = await createMCPClient({
      transport: { type: 'http', url: 'http://localhost:3000/mcp' },
    })
    try {
      const result = await generateText({
        model: 'openai/gpt-4o',
        prompt: input,
        tools: await mcp.tools(),
      })
      return result.toolCalls ?? []
    }
    finally {
      await mcp.close()
    }
  },
  scorers: [
    ({ output, expected }) => toolCallAccuracy({
      actualCalls: output,
      expectedCalls: expected,
    }),
  ],
})

Running

# Start server
pnpm dev

# Run tests (in another terminal)
pnpm eval

# Or with UI
pnpm eval:ui  # http://localhost:3006

See detailed testing guide →

Quick Reference

Common Commands

# Setup
npx nuxt module add mcp-toolkit

# Dev
pnpm dev

# Test endpoint
curl http://localhost:3000/mcp

# Regenerate types
pnpm nuxt prepare

# Run evals
pnpm eval

Configuration

// nuxt.config.ts
export default defineNuxtConfig({
  mcp: {
    name: 'My Server',
    route: '/mcp',
    enabled: true,
    dir: 'mcp',
  },
})

Debug Tools

• DevTools: Shift+Alt+D → MCP tab
• Logs: Check terminal
• curl: Test endpoint

Learn More

• Documentation
• Tools Guide
• Resources Guide
• Prompts Guide
• MCP Protocol