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Comparison with other agent frameworks

As of October 2026. This page is a short orientation, not a benchmark. The TypeScript agent space moves fast: most of the projects below now ship durable approvals, evals and coding-agent harnesses of their own, so check their documentation before deciding. Rows about lousho describe this repository and link to the page that documents each claim.

Each project in one row

Project What it is Approvals / human-in-the-loop Evals Coding agents Where it is ahead of lousho
lousho (@lousho/build-ai-agent) Self-hosted TypeScript agent SDK, one npm package, alpha needsApproval + resumeAfterApproval() on memory, file, SQLite or Cloudflare KV stores (Approvals) lousho eval: trajectory assertions, record/replay cassettes, drift reports (Evals) Workspace tools, permission rules, piAgent(), registry kits, ACP editor server (Build a coding agent) -
Vercel AI SDK 7 Model, agent and UI toolkit for TypeScript WorkflowAgent tools take needsApproval; runs are durable through the open-source Workflow DevKit Not built in HarnessAgent (experimental) wraps existing runtimes such as Claude Code behind one API By far the most providers and UI integrations; lousho uses it underneath for the standard providers
Mastra Full-stack TypeScript framework: agents, workflows, memory, RAG, dev UI Workflow suspend() / resume() with persisted snapshots Scorers, datasets and experiments, with results stored Build it from agents, tools and workflows Postgres and many other storage adapters, a local dev playground, a larger community
LangGraph.js Graph-shaped, stateful workflows with checkpointing interrupt() + Command({ resume }) on any checkpointer Through LangSmith (hosted) Build it as a graph Postgres checkpointer, explicit control flow, LangSmith tracing and evals
OpenAI Agents SDK (JS) Agents around OpenAI's APIs: handoffs, guardrails, tracing Tool approvals with run-state resume Through OpenAI's platform Sandbox agents (beta) that read files, run commands and apply patches First-class OpenAI hosted tools and sandboxes, OpenAI tracing dashboard
Claude Agent SDK The Claude Code agent loop as a library canUseTool callback, hooks, permission modes and rules Not built in It is a coding agent: file, shell and edit tools, sessions, subagents A production coding harness out of the box; Claude models
eve Vercel's filesystem-first agent framework (Apache-2.0, beta) Human-in-the-loop prompts on durable runs eve eval with defineEval, asserting on tool calls Sandboxes, channels (Slack, Discord, HTTP), schedules Deploy and operations on Vercel, AI Gateway models, channels. Its agent/ directory layout (instructions.md, tools/, skills/) mirrors lousho's agent directories
VoltAgent TypeScript framework: agents, memory, workflows Workflow suspend/resume Built-in evals Build it from agents and tools VoltOps observability console and dashboards
open-harness MIT TypeScript SDK on the AI SDK, modelled on Claude Code and Codex Tool permissions Not built in Filesystem and bash tools, subagents, skills, MCP, compaction Small, composable harness core focused on coding agents

What lousho still does differently

Each item is checkable in this repository.

  • Record/replay cassettes and trajectory drift in one CLI. lousho eval --record runs every case against the real provider once and writes a cassette, --replay runs them in CI with no network and no API key, and --drift re-records into a temp directory and reports how each case's tool-call trajectory changed (Evals, Testing).
  • Durable approvals on Cloudflare Workers KV as well as memory, file and SQLite, with the same needsApproval / resumeAfterApproval() code on each (Durable execution, Cloudflare Workers).
  • Editor and MCP surfaces from the same agent. lousho acp serves any agent to Zed and other Agent Client Protocol editors (ACP); serveMcp exposes it as an MCP server to Claude Code, Cursor and other clients (MCP).
  • Self-hosted, one package, no platform account. Runs in your Node process or a Worker; nothing calls home and there is no hosted control plane to sign up for.
  • Spans AI SDK majors. The ai peer dependency accepts ^4.3.19, ^6 and ^7, so an existing app can adopt lousho without first upgrading the AI SDK (Installation).

Where lousho is weaker

  • Alpha, one maintainer. The 1.0 line is still 1.0.0-alpha.*. Expect API churn, a small community and few third-party integrations.
  • No Postgres store. Checkpoint and approval stores ship for memory, file, SQLite and Cloudflare KV. Mastra and LangGraph ship Postgres; here you implement the small CheckpointStore / ApprovalStore interfaces yourself.
  • Fewer native providers. OpenAI, Anthropic, OpenRouter, Ollama and the Pi catalog are built in; anything else goes through fromAiSdk() (Providers).
  • No hosted dashboard. Traces are OpenTelemetry spans you send to your own backend (Observability); there is no equivalent of LangSmith, VoltOps or Mastra's playground.
  • The root entry point is not edge-safe. Cloudflare Workers use the dedicated worker build and subpaths (Cloudflare Workers).
  • Live runs are manual. CI runs offline tests and cassette replays; live-provider checks are run by hand.

Picking one

If you only need model calls with streaming UI, the Vercel AI SDK alone is the simpler choice. If you want a ready-made coding agent, start from the Claude Agent SDK or an AI SDK harness. If you want an all-in-one framework with a dev UI and Postgres, look at Mastra; if your control flow is a graph, LangGraph.js; if you deploy on Vercel, eve. Pick lousho when you want offline record/replay evals, approvals that survive a restart on your own stores (including Workers KV), and one self-hosted package you can also serve over ACP and MCP.