deepagents vs harness-sdk
Python agent harnesses compared
deepagents and harness-sdk both help developers build AI agents with tools, state, and context management. deepagents provides an opinionated structure for multi-step work, while harness-sdk pairs ready-made harnesses with lower-level SDKs in Python and TypeScript.
deepagents: Build Agents with Planning and Tooling Built In
Deep Agents is a Python agent harness for building LLM agents with planning, delegation, file access, and context management built in. It suits developers who need a more capable starting point than a minimal agent loop, while retaining control over models and tools.
harness-sdk: Build and Run AI Agents in Python and TypeScript
Strands Agents provides Python and TypeScript tools for building AI agents, from a ready-made harness to a customizable agent SDK. It suits teams that want model flexibility and control over agent execution without a hosted control plane.
| deepagents | harness-sdk | |
|---|---|---|
| Language | Python | Python |
| License | MIT | Apache-2.0 |
| Stars | 29.9k | 8.6k |
| Forks | 4.2k | 1.3k |
| Last analyzed | Oct 3, 2026 | Oct 3, 2026 |
Key differences
- deepagents is built on LangGraph and bundles planning, file operations, sub-agent delegation, and context management; harness-sdk offers an assembled harness or lower-level SDKs for configuring the agent loop.
- deepagents is described as a Python project; harness-sdk supports Python and TypeScript.
- deepagents uses an MIT license, while harness-sdk uses Apache-2.0.
- deepagents highlights file and shell tools, sandbox choice, reusable skills, and human approval for tool calls; harness-sdk highlights provider integrations, execution limits, hooks, tracing, guardrails, and evaluation.
- deepagents is aimed at multi-step workflows that benefit from built-in planning and delegation; harness-sdk suits teams that want to choose how much of the agent setup and execution to control.
- Both run agents in developer-controlled environments; harness-sdk explicitly emphasizes running in your process without a hosted control plane.
Choose deepagents if you…
- need built-in planning, file operations, and sub-agent delegation for multi-step work.
- want an opinionated LangGraph-based structure that you can extend or customize.
- need persistent state, long-conversation management, or sandboxed shell access as part of an agent harness.
Choose harness-sdk if you…
- want to build in Python or TypeScript and choose between a ready-made harness and lower-level SDKs.
- need documented integrations for multiple model providers, including Bedrock, Anthropic, OpenAI, and Gemini.
- want lifecycle controls, hooks, tracing, guardrails, or evaluation features for agent execution.
Compare the numbers side by side, or add more projects
This comparison is generated with AI from the OSRepos analyses of both projects. Always check each project's repository and documentation before choosing.