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AgentMark works with multiple AI SDKs through adapters. Choose the adapter that fits your tech stack, or build your own.

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What Are Adapters?

Adapters connect AgentMark prompts to AI SDKs. They translate AgentMark’s prompt format into the format your AI SDK expects. The pattern is always the same:
  1. Load prompt: client.loadTextPrompt() / loadObjectPrompt()
  2. Format with props: await prompt.format({ props: {...} })
  3. Pass to your AI SDK’s generation function

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Available Adapters

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AI SDK (Recommended)

The most popular adapter for Next.js and Node.js applications. Supports text, object, image, and speech generation with streaming. 
import { createAgentMarkClient, VercelAIModelRegistry } from "@agentmark-ai/ai-sdk-v5-adapter";
import { openai } from "@ai-sdk/openai";
import { generateText } from "ai";

const modelRegistry = new VercelAIModelRegistry()
  .registerModels(["gpt-4o"], (name) => openai(name));

const client = createAgentMarkClient({ loader: fileLoader, modelRegistry });
const prompt = await client.loadTextPrompt("greeting.prompt.mdx");
const input = await prompt.format({ props: { name: "Alice" } });
const result = await generateText(input);
Learn more →

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Claude Agent SDK

Run AgentMark prompts as agentic tasks with Anthropic’s Claude Agent SDK. Supports tool use, budget controls, and tracing. 
import { createAgentMarkClient, ClaudeAgentModelRegistry } from "@agentmark-ai/claude-agent-sdk-adapter";

const modelRegistry = new ClaudeAgentModelRegistry()
  .registerModels(["claude-sonnet-4-20250514"]);

const client = createAgentMarkClient({ loader: fileLoader, modelRegistry });
const prompt = await client.loadTextPrompt("task.prompt.mdx");
const input = await prompt.format({ props: { task: "Refactor auth module" } });
const result = await runAgent(input);
Learn more →

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Mastra

Built for agentic workflows and multi-step LLM applications with Mastra’s framework. 
import { createAgentMarkClient, MastraModelRegistry } from "@agentmark-ai/mastra-v0-adapter";

const modelRegistry = new MastraModelRegistry()
  .registerModels(["claude-3-5-sonnet-20241022"], (name) => createModel(name));

const client = createAgentMarkClient({ loader: fileLoader, modelRegistry });
const prompt = await client.loadTextPrompt("greeting.prompt.mdx");
const agent = await prompt.formatAgent({ props: { name: "Alice" } });
const result = await agent.generate(...agent.formatMessages());
Learn more →

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Pydantic AI

The recommended adapter for Python applications. Supports text, object generation, streaming, and type-safe outputs via Pydantic models. 
from agentmark_pydantic_ai_v0 import create_pydantic_ai_client, create_default_model_registry, run_text_prompt
from agentmark.prompt_core import FileLoader

loader = FileLoader(base_dir="./")
client = create_pydantic_ai_client(model_registry=create_default_model_registry(), loader=loader)
prompt = await client.load_text_prompt("greeting.prompt.mdx")
params = await prompt.format(props={"name": "Alice"})
result = await run_text_prompt(params)
Learn more →

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LlamaIndex (Coming Soon)

Use AgentMark prompts with LlamaIndex’s data framework and agent capabilities. Learn more →

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Default (Fallback)

Returns raw prompt configuration without SDK-specific formatting. Useful for mapping to any provider directly. 
import { createAgentMarkClient } from "@agentmark-ai/fallback-adapter";

const client = createAgentMarkClient({ loader: fileLoader });
const prompt = await client.loadTextPrompt("greeting.prompt.mdx");
const result = await prompt.format({ props: { name: "Alice" } });
// Returns raw config — pass to your own provider
Learn more →

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Custom Adapter

Build your own adapter for any AI SDK by implementing the model registry interface. Learn more →

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How to Choose

AdapterBest ForLanguageStreamingImage/Speech
AI SDKNext.js, Node.js apps with broad model supportTypeScriptYesYes
Claude Agent SDKAgentic tasks with Claude (tool use, budget controls)TypeScriptNoNo
MastraComplex agentic workflows and orchestrationTypeScriptYesNo
Pydantic AIPython applications with type-safe outputsPythonYesNo
LlamaIndexData-heavy apps with indexing and retrievalPythonTBDTBD
DefaultDirect provider mapping or unsupported SDKsTypeScriptN/AN/A
CustomAny SDK with specific requirementsTypeScriptYou decideYou decide

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For Python Developers

Recommended: Pydantic AI — Best for most Python projects. Provides:
  • Type-safe outputs via Pydantic models
  • Streaming support
  • Sync and async tool functions
  • All major LLM providers (OpenAI, Anthropic, Google)
Alternative: Claude Agent SDK — Use when you need agentic capabilities with Claude:
  • Multi-turn tool use
  • Budget controls
  • Permission management
Image and speech generation are not available in Python adapters. If you need these features, consider using the AI SDK adapter via a Node.js service, or use provider SDKs directly.

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Switching Adapters

Switch between adapters without changing your prompts. Only your client configuration changes: 
// Switch from AI SDK to Mastra — your prompts stay exactly the same
import { createAgentMarkClient, MastraModelRegistry } from "@agentmark-ai/mastra-v0-adapter";
Your prompts are adapter-agnostic. The same .prompt.mdx files work with any adapter. Only your client configuration (agentmark.client.ts or agentmark_client.py) needs to change.

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Package Versioning

Adapter packages use a -v0 suffix (e.g., agentmark-pydantic-ai-v0, @agentmark-ai/mastra-v0-adapter). This indicates the adapter API version, not stability:
  • v0 = current stable API
  • Future breaking changes would be released as v1, v2, etc.
This allows you to pin to a specific adapter API version while still receiving bug fixes.

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Next Steps

AI SDK

Next.js and Node.js apps

Claude Agent SDK

Agentic tasks with Claude

Mastra

Agentic workflows

Pydantic AI

Python type-safe integration

LlamaIndex

Data framework integration

Default Adapter

Raw config pass-through

Custom Adapter

Build your own