Anthropic integration for Microsoft Agent Framework

1.0.0b260409 verified Wed Apr 15 auth: no en

The `agent-framework-anthropic` library provides seamless integration of Anthropic Claude models with the Microsoft Agent Framework. It enables developers to leverage Claude's advanced reasoning, context handling, and thoughtful responses within their AI agent applications. As part of the broader Microsoft Agent Framework ecosystem, it's under active development, with frequent updates given its current beta status.

pip install agent-framework --pre

Warnings

breaking The `agent-framework-anthropic` package is currently in a pre-release (beta) state. Breaking changes may occur frequently, especially as the broader Microsoft Agent Framework evolves towards stable releases. ↓

fix Refer to the official `microsoft/agent-framework` GitHub repository and documentation for specific migration guides and changelogs before upgrading. Test thoroughly.

gotcha The core `agent-framework` package often requires the `--pre` flag during `pip install` to get the latest compatible pre-release versions, as it is also under rapid development. Forgetting this can lead to version conflicts or outdated components. ↓

fix Always install `agent-framework` with `pip install agent-framework --pre` to ensure compatibility with the latest `agent-framework-anthropic` releases.

gotcha API keys (e.g., `ANTHROPIC_API_KEY`) should never be hardcoded or committed to source control. They must be managed securely, preferably through environment variables or a dedicated secret management service. ↓

fix Set `ANTHROPIC_API_KEY` as an environment variable (e.g., `export ANTHROPIC_API_KEY='sk-ant-...'`). The `AnthropicClient` will automatically detect it.

breaking A critical vulnerability has been identified in Anthropic's Model Context Protocol (MCP), which could allow arbitrary command execution on servers running MCP. Since Microsoft Agent Framework integrates with MCP, this is a significant security concern. ↓

fix Monitor official announcements from Anthropic and Microsoft regarding patches or mitigation strategies for the MCP vulnerability. Update dependencies as soon as fixes are available.

gotcha Long-running AI agents built with Claude models can face challenges with memory and context windows, potentially leading to agents 'forgetting' instructions or previous conversational turns over extended interactions. ↓

fix Implement explicit memory management strategies or leverage features like 'initializer agents' and 'coding agents' for incremental progress, as discussed by Anthropic for their SDK.

gotcha Integrating deeply with Anthropic's infrastructure or the Microsoft Agent Framework may lead to increased vendor lock-in, making it harder to switch underlying LLM providers or agent frameworks in the future. ↓

fix Evaluate the trade-offs between ease of integration and vendor flexibility. Design your agent architecture with modularity in mind where possible to abstract away provider-specific implementations.

gotcha Costs for Anthropic models vary significantly by model (e.g., Claude Haiku vs. Opus) and token usage (input/output). Inefficient prompting or long contexts can lead to unexpectedly high costs. ↓

fix Follow Anthropic's best practices for prompt engineering, choose appropriate models for the task, monitor token usage, and optimize prompts for conciseness and clarity.

Install

pip install agent-framework-anthropic

Imports

AnthropicClient

from agent_framework.anthropic import AnthropicClient

Quickstart

This quickstart demonstrates how to initialize an `AnthropicClient` and create a basic AI agent. It assumes the `ANTHROPIC_API_KEY` environment variable is set for authentication with the Anthropic API. The agent is then used to answer a simple question.

import asyncio
import os
from agent_framework.anthropic import AnthropicClient

async def main():
    # Ensure ANTHROPIC_API_KEY is set in your environment variables.
    # For a quick test, you can uncomment and set it directly, but avoid in production.
    # os.environ['ANTHROPIC_API_KEY'] = 'your_anthropic_api_key_here'

    if not os.environ.get('ANTHROPIC_API_KEY'):
        print("Error: ANTHROPIC_API_KEY environment variable is not set.")
        print("Please set it before running the quickstart.")
        return

    client = AnthropicClient()

    # Create an agent using the Anthropic client
    agent = client.as_agent(
        name="HelpfulAssistant",
        instructions="You are a helpful assistant that answers questions accurately.",
    )

    # Run the agent with a prompt
    response = await agent.run("What is the capital of France?")
    print(f"Assistant: {response}")

if __name__ == "__main__":
    asyncio.run(main())