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Hono Rpc

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bobmatnyc
hono-rpc

Hono RPC - end-to-end type-safe API client generation with hc client and TypeScript inference

Overview

Publisherbobmatnyc
Repositoryclaude-mpm-skills
Skill namehono-rpc
Stars
75
Forks
19
Bundled files
1
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by bobmatnyc on GitHub. Read the source before you install it.

Installation

Install the Hono Rpc AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/bobmatnyc/claude-mpm-skills.git /tmp/claude-mpm-skills
mkdir -p .claude/skills
cp -r /tmp/claude-mpm-skills/toolchains/javascript/frameworks/hono/hono-rpc .claude/skills/hono-rpc
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Hono Rpc in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Hono Rpc on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Hono Rpc is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Hono RPC - Type-Safe Client

Overview

Hono RPC enables sharing API specifications between server and client through TypeScript's type system. Export your server's type, and the client automatically knows all routes, request shapes, and response types - no code generation required.

Key Features:

  • Zero-codegen type-safe client
  • Automatic TypeScript inference
  • Works with Zod validators
  • Status code-aware response types
  • Supports path params, query, headers

When to Use This Skill

Use Hono RPC when:

  • Building full-stack TypeScript applications
  • Need type-safe API consumption without OpenAPI/codegen
  • Want compile-time validation of API calls
  • Sharing types between client and server in monorepos

Basic Setup

Server Side

typescript
// server/index.ts
import { Hono } from 'hono'
import { zValidator } from '@hono/zod-validator'
import { z } from 'zod'

const app = new Hono()

// Define routes with validation
const route = app
  .get('/users', async (c) => {
    const users = [{ id: '1', name: 'Alice' }]
    return c.json({ users })
  })
  .post(
    '/users',
    zValidator('json', z.object({
      name: z.string(),
      email: z.string().email()
    })),
    async (c) => {
      const data = c.req.valid('json')
      return c.json({ id: '1', ...data }, 201)
    }
  )
  .get('/users/:id', async (c) => {
    const id = c.req.param('id')
    return c.json({ id, name: 'Alice' })
  })

// Export type for client
export type AppType = typeof route

export default app

Client Side

typescript
// client/api.ts
import { hc } from 'hono/client'
import type { AppType } from '../server'

// Create typed client
const client = hc<AppType>('http://localhost:3000')

// All methods are type-safe!
async function examples() {
  // GET /users
  const usersRes = await client.users.$get()
  const { users } = await usersRes.json()
  // users: { id: string; name: string }[]

  // POST /users - body is typed
  const createRes = await client.users.$post({
    json: {
      name: 'Bob',
      email: 'bob@example.com'
    }
  })
  const created = await createRes.json()
  // created: { id: string; name: string; email: string }

  // GET /users/:id - params are typed
  const userRes = await client.users[':id'].$get({
    param: { id: '123' }
  })
  const user = await userRes.json()
  // user: { id: string; name: string }
}

Route Chaining for Type Export

Important: Chain routes for proper type inference:

typescript
// CORRECT: Chain all routes
const route = app
  .get('/a', handlerA)
  .post('/b', handlerB)
  .get('/c', handlerC)

export type AppType = typeof route

// WRONG: Separate statements lose type info
app.get('/a', handlerA)
app.post('/b', handlerB)  // Types lost!

export type AppType = typeof app  // Missing routes!

Request Patterns

Path Parameters

typescript
// Server
const route = app.get('/posts/:postId/comments/:commentId', async (c) => {
  const { postId, commentId } = c.req.param()
  return c.json({ postId, commentId })
})

// Client
const res = await client.posts[':postId'].comments[':commentId'].$get({
  param: {
    postId: '1',
    commentId: '42'
  }
})

Query Parameters

typescript
// Server
const route = app.get(
  '/search',
  zValidator('query', z.object({
    q: z.string(),
    page: z.coerce.number().optional(),
    limit: z.coerce.number().optional()
  })),
  async (c) => {
    const { q, page, limit } = c.req.valid('query')
    return c.json({ query: q, page, limit })
  }
)

// Client
const res = await client.search.$get({
  query: {
    q: 'typescript',
    page: 1,
    limit: 20
  }
})

JSON Body

typescript
// Server
const route = app.post(
  '/posts',
  zValidator('json', z.object({
    title: z.string(),
    content: z.string(),
    tags: z.array(z.string()).optional()
  })),
  async (c) => {
    const data = c.req.valid('json')
    return c.json({ id: '1', ...data }, 201)
  }
)

// Client
const res = await client.posts.$post({
  json: {
    title: 'Hello World',
    content: 'My first post',
    tags: ['typescript', 'hono']
  }
})

Form Data

typescript
// Server
const route = app.post(
  '/upload',
  zValidator('form', z.object({
    file: z.instanceof(File),
    description: z.string().optional()
  })),
  async (c) => {
    const { file, description } = c.req.valid('form')
    return c.json({ filename: file.name })
  }
)

// Client
const formData = new FormData()
formData.append('file', file)
formData.append('description', 'My file')

const res = await client.upload.$post({
  form: formData
})

Headers

typescript
// Server
const route = app.get(
  '/protected',
  zValidator('header', z.object({
    authorization: z.string()
  })),
  async (c) => {
    return c.json({ authenticated: true })
  }
)

// Client
const res = await client.protected.$get({
  header: {
    authorization: 'Bearer token123'
  }
})

Response Type Inference

Status Code-Aware Types

typescript
// Server
const route = app.get('/user', async (c) => {
  const user = await getUser()

  if (!user) {
    return c.json({ error: 'Not found' }, 404)
  }

  return c.json({ id: user.id, name: user.name }, 200)
})

// Client - use InferResponseType
import { InferResponseType } from 'hono/client'

type SuccessResponse = InferResponseType<typeof client.user.$get, 200>
// { id: string; name: string }

type ErrorResponse = InferResponseType<typeof client.user.$get, 404>
// { error: string }

// Handle different status codes
const res = await client.user.$get()

if (res.status === 200) {
  const data = await res.json()
  // data: { id: string; name: string }
} else if (res.status === 404) {
  const error = await res.json()
  // error: { error: string }
}

Request Type Inference

typescript
import { InferRequestType } from 'hono/client'

type CreateUserRequest = InferRequestType<typeof client.users.$post>['json']
// { name: string; email: string }

// Use for form validation, state management, etc.
const [formData, setFormData] = useState<CreateUserRequest>({
  name: '',
  email: ''
})

Multi-File Route Organization

Organize Routes

typescript
// server/routes/users.ts
import { Hono } from 'hono'

export const users = new Hono()
  .get('/', async (c) => c.json({ users: [] }))
  .post('/', async (c) => c.json({ created: true }, 201))
  .get('/:id', async (c) => c.json({ id: c.req.param('id') }))

// server/routes/posts.ts
export const posts = new Hono()
  .get('/', async (c) => c.json({ posts: [] }))
  .post('/', async (c) => c.json({ created: true }, 201))

// server/index.ts
import { Hono } from 'hono'
import { users } from './routes/users'
import { posts } from './routes/posts'

const app = new Hono()

const route = app
  .route('/users', users)
  .route('/posts', posts)

export type AppType = typeof route
export default app

Client Usage

typescript
import { hc } from 'hono/client'
import type { AppType } from '../server'

const client = hc<AppType>('http://localhost:3000')

// Routes are nested
await client.users.$get()         // GET /users
await client.users[':id'].$get()  // GET /users/:id
await client.posts.$get()         // GET /posts

Error Handling

Handle Fetch Errors

typescript
async function fetchUser(id: string) {
  try {
    const res = await client.users[':id'].$get({
      param: { id }
    })

    if (!res.ok) {
      const error = await res.json()
      throw new Error(error.message || 'Failed to fetch user')
    }

    return await res.json()
  } catch (error) {
    if (error instanceof TypeError) {
      // Network error
      throw new Error('Network error')
    }
    throw error
  }
}

Type-Safe Error Responses

typescript
// Server
const route = app.get('/resource', async (c) => {
  try {
    const data = await fetchData()
    return c.json({ success: true, data })
  } catch (e) {
    return c.json({ success: false, error: 'Failed' }, 500)
  }
})

// Client
type ApiResponse<T> =
  | { success: true; data: T }
  | { success: false; error: string }

const res = await client.resource.$get()
const result: ApiResponse<DataType> = await res.json()

if (result.success) {
  console.log(result.data)  // Typed!
} else {
  console.error(result.error)
}

Configuration Options

Custom Fetch

typescript
const client = hc<AppType>('http://localhost:3000', {
  // Custom fetch (for testing, logging, etc.)
  fetch: async (input, init) => {
    console.log('Fetching:', input)
    return fetch(input, init)
  }
})

Default Headers

typescript
const client = hc<AppType>('http://localhost:3000', {
  headers: {
    'Authorization': 'Bearer token',
    'X-Custom-Header': 'value'
  }
})

Dynamic Headers

typescript
const getClient = (token: string) =>
  hc<AppType>('http://localhost:3000', {
    headers: () => ({
      'Authorization': `Bearer ${token}`
    })
  })

// Or with a function that returns headers
const client = hc<AppType>('http://localhost:3000', {
  headers: () => {
    const token = getAuthToken()
    return token ? { 'Authorization': `Bearer ${token}` } : {}
  }
})

Best Practices

1. Enable Strict Mode

json
// tsconfig.json
{
  "compilerOptions": {
    "strict": true  // Required for proper type inference!
  }
}

2. Use Explicit Status Codes

typescript
// CORRECT: Explicit status enables type discrimination
return c.json({ data }, 200)
return c.json({ error: 'Not found' }, 404)

// AVOID: c.notFound() doesn't work well with RPC
return c.notFound()  // Response type is not properly inferred

3. Split Large Apps

typescript
// For large apps, split routes to reduce IDE overhead
const v1 = new Hono()
  .route('/users', usersRoute)
  .route('/posts', postsRoute)

const v2 = new Hono()
  .route('/users', usersV2Route)

// Export separate types
export type V1Type = typeof v1
export type V2Type = typeof v2

4. Consistent Response Shapes

typescript
// Define standard response wrapper
type ApiSuccess<T> = { ok: true; data: T }
type ApiError = { ok: false; error: string; code?: string }
type ApiResponse<T> = ApiSuccess<T> | ApiError

// Use consistently
const route = app.get('/users/:id', async (c) => {
  const user = await findUser(c.req.param('id'))

  if (!user) {
    return c.json({ ok: false, error: 'User not found' } as ApiError, 404)
  }

  return c.json({ ok: true, data: user } as ApiSuccess<User>, 200)
})

Quick Reference

Client Methods

HTTP MethodClient Method
GETclient.path.$get()
POSTclient.path.$post()
PUTclient.path.$put()
DELETEclient.path.$delete()
PATCHclient.path.$patch()

Request Options

typescript
client.path.$method({
  param: { id: '1' },           // Path parameters
  query: { page: 1 },           // Query parameters
  json: { name: 'Alice' },      // JSON body
  form: formData,               // Form data
  header: { 'X-Custom': 'v' }   // Headers
})

Type Utilities

typescript
import { InferRequestType, InferResponseType } from 'hono/client'

// Extract request type
type ReqType = InferRequestType<typeof client.users.$post>

// Extract response type by status
type Res200 = InferResponseType<typeof client.users.$get, 200>
type Res404 = InferResponseType<typeof client.users.$get, 404>

Related Skills

  • hono-core - Framework fundamentals
  • hono-validation - Request validation
  • typescript-core - TypeScript patterns

Version: Hono 4.x Last Updated: January 2025 License: MIT

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Hono Rpc AI skill do?

Hono RPC - end-to-end type-safe API client generation with hc client and TypeScript inference

Why use Hono Rpc on TypingMind?

Because you install it once and use it with any model. Hono Rpc is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Hono Rpc in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/bobmatnyc/claude-mpm-skills/tree/main/toolchains/javascript/frameworks/hono/hono-rpc. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Hono Rpc?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Hono Rpc?

As many as you like. As long as a model supports skills, you can use Hono Rpc with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Hono Rpc AI skill free?

Yes. It is published on GitHub by bobmatnyc under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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