deepagents vs swarmclaw
AI agent frameworks compared
deepagents provides a Python harness with built-in planning, file operations, delegation, and context management. swarmclaw is a TypeScript runtime for self-hosting and coordinating agents, with deployment options and operational controls such as schedules and background jobs.
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.
swarmclaw: Run Self-Hosted AI Agent Swarms
SwarmClaw is a self-hosted AI agent runtime and multi-agent framework built with TypeScript for Node.js. It coordinates agents with persistent memory, tools, schedules, and delegation across supported model providers and runtimes.
| deepagents | swarmclaw | |
|---|---|---|
| Language | Python | TypeScript |
| License | MIT | MIT |
| Stars | 29.9k | 697 |
| Forks | 4.2k | 141 |
| Last analyzed | Oct 3, 2026 | Oct 26, 2026 |
Key differences
- deepagents is built on LangGraph and focuses on a ready-to-extend agent harness; swarmclaw provides a control plane for running agents and teams.
- deepagents is written in Python, while swarmclaw is written in TypeScript for Node.js.
- deepagents emphasizes file tools, sandboxed shell commands, and context management; swarmclaw emphasizes persistent memory, scheduled execution, and runtime coordination.
- deepagents supports tool-calling models and customizable components; swarmclaw describes support for multiple model providers and agent runtimes.
- deepagents can be used through LangGraph deployments; swarmclaw can run as a desktop app, server, or Docker deployment.
- Both use the MIT license. The supplied project data lists 29.9k stars for deepagents and 697 for swarmclaw.
Choose deepagents if you…
- need a Python harness with planning, file operations, and context management built in.
- want sub-agent delegation with isolated context windows and configurable memory.
- prefer to customize an agent structure built on LangGraph.
Choose swarmclaw if you…
- want to self-host and operate agent workflows as a desktop app, server, or Docker deployment.
- need schedules, background jobs, and persistent memory for agents.
- want to coordinate agents across supported providers and runtimes, including OpenClaw.
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.