Skip to main content
The Mastra adapter allows you to use AgentMark prompts with Mastra’s agentic workflow framework.

​
Installation

npm install @agentmark/mastra-v0-adapter mastra

​
Setup

Create your AgentMark client with Mastra’s model registry:
agentmark.client.ts
import { createAgentMarkClient } from '@agentmark/sdk';
import { MastraModelRegistry } from '@agentmark/mastra-v0-adapter';
import { Anthropic } from 'mastra/llms';

export const client = createAgentMarkClient({
  models: new MastraModelRegistry({
    'claude-3-5-sonnet-20241022': new Anthropic({
      model: 'claude-3-5-sonnet-20241022',
      apiKey: process.env.ANTHROPIC_API_KEY!,
    }),
  }),
});

​
Running Prompts

AgentMark prompts return Mastra agents via formatAgent(), which you can then use with formatMessages(): 
import { client } from './agentmark.client';

const prompt = await client.loadTextPrompt('greeting.prompt.mdx');
const agent = await prompt.formatAgent({
  props: { name: 'Alice' }
});

const [messages, options] = agent.formatMessages();
const result = await agent.generate(messages, options);

console.log(result.text);

​
Object Generation

For structured output, use object prompts: 
import { client } from './agentmark.client';
import { z } from 'zod';

const prompt = await client.loadObjectPrompt('extract.prompt.mdx', {
  schema: z.object({
    sentiment: z.enum(['positive', 'negative', 'neutral']),
    confidence: z.number(),
  }),
});

const agent = await prompt.formatAgent({
  props: { text: 'This product is amazing!' }
});

const [messages, options] = agent.formatMessages();
const result = await agent.generate(messages, options);

console.log(result.object);
// { sentiment: 'positive', confidence: 0.95 }

​
Tools

Configure tools in your client:
agentmark.client.ts
import { createAgentMarkClient } from '@agentmark/sdk';
import { MastraModelRegistry, MastraToolRegistry } from '@agentmark/mastra-v0-adapter';
import { createTool } from 'mastra/tools';
import { z } from 'zod';

const weatherTool = createTool({
  id: 'weather',
  description: 'Get current weather for a location',
  inputSchema: z.object({
    location: z.string(),
  }),
  execute: async ({ context }) => {
    const { location } = context;
    return `The weather in ${location} is sunny and 72°F`;
  },
});

export const client = createAgentMarkClient({
  models: new MastraModelRegistry({ /* ... */ }),
  tools: new MastraToolRegistry({
    weather: weatherTool,
  }),
});
Then use tools in your prompts:
weather.prompt.mdx
---
name: weather
text_config:
  model_name: claude-3-5-sonnet-20241022
  tools:
    - weather
---

<System>You are a helpful weather assistant.</System>
<User>What's the weather in {props.location}?</User>

​
Next Steps

Prompts

Learn about prompt syntax

Testing

Test your prompts with datasets

Observability

Monitor your agents in production

Other Integrations

Explore other AI frameworks

​
Have Questions?

We’re here to help! Choose the best way to reach us: