mastra-hono

📁 jwynia/agent-skills 📅 Jan 20, 2026
41
总安装量
41
周安装量
#5134
全站排名
安装命令
npx skills add https://github.com/jwynia/agent-skills --skill mastra-hono

Agent 安装分布

claude-code 33
opencode 31
codex 28
gemini-cli 26
antigravity 22
windsurf 22

Skill 文档

Mastra + Hono Development

Build production-ready AI agents, tools, and workflows using Mastra v1 Beta with Hono API servers. This skill covers the complete stack from agent definition to deployment.

Target version: Mastra v1 Beta (stable release expected January 2026)

When to Use This Skill

Use when:

  • Creating Mastra agents with tools and memory
  • Defining tools with Zod input/output schemas
  • Building workflows with multi-step data flow
  • Setting up Hono API servers with Mastra adapters
  • Implementing agent networks for multi-agent collaboration
  • Authoring MCP servers to expose agents/tools
  • Integrating RAG and conversation memory

Do NOT use when:

  • Working with Mastra stable (0.24.x) – patterns differ significantly
  • Building non-AI web APIs (use Hono directly)
  • Simple LLM calls without agents/tools

Prerequisites

  • Node.js 22.13.0+ (required for v1 Beta)
  • Package manager: npm, pnpm, or bun
  • API keys: OpenAI, Anthropic, or other supported providers
# Install v1 Beta packages
npm install @mastra/core@beta @mastra/hono@beta
npm install @ai-sdk/openai  # or other provider
npm install zod hono @hono/node-server

Quick Start

Minimal Agent + Tool + Hono Server

// src/mastra/tools/weather-tool.ts
import { createTool } from "@mastra/core/tools";
import { z } from "zod";

export const weatherTool = createTool({
  id: "get-weather",
  description: "Fetches current weather for a location",
  inputSchema: z.object({
    location: z.string().describe("City name, e.g., 'Seattle'"),
  }),
  outputSchema: z.object({
    temperature: z.number(),
    conditions: z.string(),
  }),
  // v1 Beta signature: (inputData, context)
  execute: async (inputData, context) => {
    const { location } = inputData;
    const { abortSignal } = context;

    if (abortSignal?.aborted) throw new Error("Aborted");

    // Fetch weather data...
    return { temperature: 72, conditions: "sunny" };
  },
});
// src/mastra/agents/weather-agent.ts
import { Agent } from "@mastra/core/agent";
import { openai } from "@ai-sdk/openai";
import { weatherTool } from "../tools/weather-tool.js";

export const weatherAgent = new Agent({
  name: "weather-agent",
  instructions: "You are a helpful weather assistant.",
  model: openai("gpt-4o-mini"),
  tools: { weatherTool },  // Object, not array
});
// src/mastra/index.ts
import { Mastra } from "@mastra/core/mastra";
import { weatherAgent } from "./agents/weather-agent.js";

export const mastra = new Mastra({
  agents: { weatherAgent },
});
// src/index.ts
import { serve } from "@hono/node-server";
import { Hono } from "hono";
import { MastraServer } from "@mastra/hono";
import { mastra } from "./mastra/index.js";

const app = new Hono();
const server = new MastraServer({ app, mastra });
await server.init();

app.get("/", (c) => c.text("Mastra + Hono Server"));

serve({ fetch: app.fetch, port: 3000 });
console.log("Server running at http://localhost:3000");
// Agent endpoint: POST /api/agents/weather-agent/generate

Core Patterns

Agent Definition

import { Agent } from "@mastra/core/agent";

const agent = new Agent({
  name: "my-agent",                           // Required: unique identifier
  instructions: "You are a helpful assistant.", // Required: system prompt
  model: openai("gpt-4o-mini"),               // Required: LLM model
  tools: { weatherTool, searchTool },         // Optional: object with named tools
});

// Model routing (1113+ models from 53 providers)
model: "openai/gpt-4o-mini"
model: "anthropic/claude-3-5-sonnet"
model: "google/gemini-2.5-flash"

// Model fallbacks for resilience
model: [
  { model: "anthropic/claude-3-opus", maxRetries: 3 },
  { model: "openai/gpt-4o", maxRetries: 2 },
  { model: "google/gemini-pro", maxRetries: 1 },
]

// Agent execution with memory
const response = await agent.generate("Remember my name is Alex", {
  memory: {
    thread: "conversation-123",   // Isolates conversation
    resource: "user-456",         // Associates with user
  },
});

Tool Signatures (v1 Beta – CRITICAL)

// v1 Beta: execute(inputData, context)
execute: async (inputData, context) => {
  const { location } = inputData;  // First parameter: parsed input
  const { mastra, runtimeContext, abortSignal } = context;  // Second: context

  // Access nested agents via mastra
  const helper = mastra?.getAgent("helperAgent");

  // Always check abort signal for long operations
  if (abortSignal?.aborted) throw new Error("Aborted");

  return { temperature: 72, conditions: "sunny" };
}

// WRONG for v1 Beta:
execute: async ({ context }) => { ... }  // This is stable 0.24.x signature

Workflow Data Flow (CRITICAL)

This is where most errors occur. See references/workflow-data-flow.md for complete patterns.

import { createWorkflow, createStep } from "@mastra/core/workflows";

const step1 = createStep({
  id: "step-1",
  inputSchema: z.object({ message: z.string() }),
  outputSchema: z.object({ formatted: z.string() }),
  execute: async ({ inputData }) => {
    // inputData = workflow input (for first step)
    return { formatted: inputData.message.toUpperCase() };
  },
});

const step2 = createStep({
  id: "step-2",
  inputSchema: z.object({ formatted: z.string() }),  // MUST match step1 output
  outputSchema: z.object({ emphasized: z.string() }),
  execute: async ({ inputData }) => {
    // inputData = step1's return value directly
    return { emphasized: `${inputData.formatted}!!!` };
  },
});

const workflow = createWorkflow({
  id: "my-workflow",
  inputSchema: z.object({ message: z.string() }),     // MUST match step1 input
  outputSchema: z.object({ emphasized: z.string() }), // MUST match final output
})
  .then(step1)
  .then(step2)
  .commit();

Schema matching rules:

Rule Description
Workflow input → Step 1 input Must match exactly
Step N output → Step N+1 input Must match exactly
Final step output → Workflow output Must match exactly

Data access in steps:

execute: async ({
  inputData,      // Previous step's output (or workflow input for step 1)
  getStepResult,  // Access ANY step's output by ID
  getInitData,    // Get original workflow input
  mastra,         // Access agents, tools, storage
}) => {
  const step1Result = getStepResult("step-1");
  const originalInput = getInitData();
  return { result: inputData.formatted };
}

Hono Server Setup

import { MastraServer } from "@mastra/hono";

const app = new Hono();
const server = new MastraServer({ app, mastra });
await server.init();

// Endpoints auto-registered:
// POST /api/agents/{agent-name}/generate
// POST /api/agents/{agent-name}/stream
// POST /api/workflows/{workflow-id}/start

Custom route prefix:

const server = new MastraServer({
  app,
  mastra,
  prefix: "/v1/ai"  // Routes at /v1/ai/agents/...
});

Custom API routes:

import { registerApiRoute } from "@mastra/core/server";

registerApiRoute("/my-custom-route", {
  method: "POST",
  handler: async (c) => {
    const mastra = c.get("mastra");
    const agent = mastra.getAgent("my-agent");
    const result = await agent.generate("Hello");
    return c.json({ response: result.text });
  },
});

Common Mistakes Quick Reference

Topic Wrong Correct
Imports import { Agent } from "@mastra/core" import { Agent } from "@mastra/core/agent"
Tools array tools: [tool1, tool2] tools: { tool1, tool2 }
Memory context { threadId: "123" } { memory: { thread: "123", resource: "user" } }
Workflow data context.steps.step1.output inputData or getStepResult("step-1")
After parallel inputData.result inputData["step-id"].result
After branch inputData.result inputData["step-id"]?.result (optional)
Nested agents import agent; agent.generate() mastra.getAgent("name").generate()
State mutation state.counter++ setState({ ...state, counter: state.counter + 1 })
v1 tool exec execute: async ({ context }) execute: async (inputData, context)

Scripts Reference

Script Purpose Usage
scaffold-project.ts Create new Mastra+Hono project deno run --allow-all scripts/scaffold-project.ts --name my-project
scaffold-agent.ts Create agent with tools deno run --allow-all scripts/scaffold-agent.ts --name weather
scaffold-workflow.ts Create workflow with steps deno run --allow-all scripts/scaffold-workflow.ts --name process-data
scaffold-tool.ts Create tool with schemas deno run --allow-all scripts/scaffold-tool.ts --name fetch-weather
validate-workflow-schemas.ts Validate step schema matching deno run --allow-read scripts/validate-workflow-schemas.ts ./src/mastra/workflows/
check-version-patterns.ts Detect v1/stable pattern mixing deno run --allow-read scripts/check-version-patterns.ts ./src/mastra/

Additional Resources

Reference Files

  • references/workflow-data-flow.md – Complete data flow patterns (CRITICAL)
  • references/common-mistakes.md – Extended anti-patterns and fixes
  • references/agent-patterns.md – Agent definition deep-dive
  • references/tool-patterns.md – Tool signatures, wrappers
  • references/hono-server-patterns.md – Server setup, routes, middleware
  • references/testing-patterns.md – Vitest setup, mocking LLMs
  • references/mcp-server-patterns.md – Model Context Protocol authoring
  • references/agent-networks.md – Multi-agent collaboration, A2A
  • references/rag-memory-patterns.md – Vector stores, embeddings, memory
  • references/context-network-memory.md – Context networks for agent memory

Asset Templates

  • assets/agent-template.ts – Agent boilerplate
  • assets/tool-template.ts – Tool boilerplate (v1 signature)
  • assets/workflow-template.ts – Workflow boilerplate
  • assets/hono-server-template.ts – Hono+Mastra server setup
  • assets/vitest-setup-template.ts – Test configuration

External Documentation


Limitations

  • Targets v1 Beta only; stable (0.24.x) patterns differ significantly
  • Scripts require Deno runtime with appropriate permissions
  • MCP server patterns require MCP-compatible clients
  • Agent networks require all participating agents to be registered in same Mastra instance

Related Skills

  • research-workflow – Deep dive research for AI agent design
  • web-search – Real-time information retrieval for agents