ekoProduction JavaScript framework for agentic workflows: one sentence becomes a dependency-aware multi-agent plan that runs in browser, Node, or extension — with pause/resume and snapshot recovery.
Why switchBoth are TypeScript-first agent frameworks you embed in a Node backend. Eko adds a planner and dependency-aware multi-agent workflows across browser and Node; AgentDock stops at a single run loop with a tool registry and leaves orchestration to your app.
Full comparison → deepagentsLangChain's batteries-included agent harness on LangGraph — planning, sub-agents with isolated context, filesystem, shell, skills, human-in-the-loop and persistent memory out of the box.
Why switchSame 'library, not product' position, opposite scope. DeepAgents ships planning, sub-agents with isolated context and a virtual filesystem on LangGraph; AgentDock ships a loop and expects the consuming app to own tools, prompts, auth and persistence.
Full comparison → swiftideRust framework for LLM apps: an agent harness, compile-time-typed task graphs, and streaming RAG pipelines — MCP toolboxes, human-in-the-loop approval, tracing with Langfuse support.
Why switchBoth are typed, in-process agent runtimes aimed at application developers rather than CLI users. Swiftide is Rust with compile-time task graphs and streaming RAG; AgentDock is a minimal TypeScript loop over the AI SDK.
Full comparison → OpenRathPyTorch-shaped multi-agent framework: Session is the tensor, Agent the layer, Workflow the module — plus a v2 durable runtime with checkpoints, leases, an effect ledger and human interrupts.
Why switchBoth answer 'embed an agent runtime in my own backend' rather than 'run a harness'. OpenRath is Python with PyTorch-style composition, a durable runtime, effect ledger and Postgres underneath; AgentDock is a TypeScript loop over the AI SDK small enough to read end to end. Opposite ends of the same decision — reach for OpenRath when runs must survive restarts, AgentDock when they must not add dependencies.
Full comparison →