Capability · Framework — orchestration
Mirascope
Mirascope from Mirascope AI (formerly Mirascope Inc.) provides a minimal but complete Python interface for LLM apps: prompt templates as decorated functions, typed responses via Pydantic, tools, streaming, async, and a uniform API across OpenAI, Anthropic, Google, Groq, Cohere, Mistral, and local providers. It's intentionally lean — closer to requests for LLMs than to a large framework.
Framework facts
- Category
- orchestration
- Language
- Python
- License
- MIT
- Repository
- https://github.com/Mirascope/mirascope
Install
pip install "mirascope[anthropic]"Quickstart
from mirascope.core import anthropic, prompt_template
@anthropic.call('claude-opus-4-7')
@prompt_template('Recommend a {genre} book.')
def recommend_book(genre: str): ...
response = recommend_book('science fiction')
print(response.content)Alternatives
- Instructor — structured outputs only
- Pydantic AI — full agent framework
- LangChain — larger ecosystem
- LlamaIndex — RAG-focused alternative
Frequently asked questions
How does Mirascope compare to LangChain?
Mirascope is much smaller and more Pythonic — it's closer to writing regular Python functions with decorators than to composing chains. If LangChain feels too heavy, Mirascope is a popular minimalist alternative.
Does Mirascope support tools and agents?
Yes. It supports tool/function calling, streaming, async, and you can build agent loops with ordinary Python control flow. It leans on Pydantic for structured outputs rather than inventing its own primitives.
Sources
- Mirascope — docs — accessed 2026-04-20
- Mirascope — GitHub — accessed 2026-04-20