Eigenwise/atomic-agents

Health v2 · maintenance only

Adoption not part of the score

6202 stars · 535 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

Atomic Agents is a lightweight, modular Python framework for building agentic AI pipelines and applications from small, composable components (agents, tools, context providers). It is built on Instructor and Pydantic, emphasizing schema-validated, predictable outputs and strong developer experience.

Use cases

• build ai agents in python
• create multi-agent orchestration pipelines
• build a rag chatbot
• add tools and memory to an llm application
• get structured json outputs from llms
• build an mcp agent
• summarize youtube videos with ai

When to choose

• you want a lightweight, composable alternative to heavyweight agent frameworks
• you value Pydantic-based schema validation and predictable agent outputs
• you need modular pipelines with hooks, tools, and context providers
• you prefer software-engineering-first patterns for LLM apps

When to avoid

• you need a batteries-included all-in-one agent platform with a UI
• your stack is not Python
• you need built-in vector database or hosting rather than library-level composition

Facets

framework · maturity active

agent-framework llm-inference rag prompt-engineering mcp chatbot serialization artificial-intelligence large-language-models developer-tools python cross-platform pydantic instructor modular multi-agent structured-outputs openai ai-agents retrieval-augmented-generation

Member repositories

For agents

markdown · JSON · MCP: product_card(name="Eigenwise/atomic-agents")