Claude-skill-registry-data mastra-hono
Develop AI agents, tools, and workflows with Mastra v1 Beta and Hono servers. This skill should be used when creating Mastra agents, defining tools with Zod schemas, building workflows with step data flow, setting up Hono API servers with Mastra adapters, or implementing agent networks. Keywords: mastra, hono, agent, tool, workflow, AI, LLM, typescript, API, MCP.
install
source · Clone the upstream repo
git clone https://github.com/majiayu000/claude-skill-registry-data
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/majiayu000/claude-skill-registry-data "$T" && mkdir -p ~/.claude/skills && cp -r "$T/data/mastra-hono" ~/.claude/skills/majiayu000-claude-skill-registry-data-mastra-hono && rm -rf "$T"
manifest:
data/mastra-hono/SKILL.mdsource content
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 | | |
| Tools array | | |
| Memory context | | |
| Workflow data | | or |
| After parallel | | |
| After branch | | (optional) |
| Nested agents | | |
| State mutation | | |
| v1 tool exec | | |
Scripts Reference
| Script | Purpose | Usage |
|---|---|---|
| Create new Mastra+Hono project | |
| Create agent with tools | |
| Create workflow with steps | |
| Create tool with schemas | |
| Validate step schema matching | |
| Detect v1/stable pattern mixing | |
Additional Resources
Reference Files
- Complete data flow patterns (CRITICAL)references/workflow-data-flow.md
- Extended anti-patterns and fixesreferences/common-mistakes.md
- Agent definition deep-divereferences/agent-patterns.md
- Tool signatures, wrappersreferences/tool-patterns.md
- Server setup, routes, middlewarereferences/hono-server-patterns.md
- Vitest setup, mocking LLMsreferences/testing-patterns.md
- Model Context Protocol authoringreferences/mcp-server-patterns.md
- Multi-agent collaboration, A2Areferences/agent-networks.md
- Vector stores, embeddings, memoryreferences/rag-memory-patterns.md
- Context networks for agent memoryreferences/context-network-memory.md
Asset Templates
- Agent boilerplateassets/agent-template.ts
- Tool boilerplate (v1 signature)assets/tool-template.ts
- Workflow boilerplateassets/workflow-template.ts
- Hono+Mastra server setupassets/hono-server-template.ts
- Test configurationassets/vitest-setup-template.ts
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