A curated, verified, cross-vendor directory of AI agent harnesses — the runtime scaffolding that turns a model into an agent.
◆ 74 harnesses profiled · 9-axis capability schema · last verified 2026-07-08
Mario Zechner's radically minimal MIT/TypeScript harness (~68k stars): four tools (read/write/edit/bash), a ~300-word system prompt, deliberately no built-in MCP/subagents/permission-popups, with everything else added via TypeScript extensions, skills, and npm/git-shareable packages across interactive, print/JSON, RPC, and SDK modes.
Block's Rust-built, Apache-2.0 general engineering agent — now stewarded by the Linux Foundation's Agentic AI Foundation — distinguished by the deepest MCP integration in the ecosystem (70+ extensions, can also act as an MCP server) and shareable YAML 'Recipes' that scaled agent workflows to 60% of Block.
Low-level graph-based agent orchestration runtime with automatic checkpointing, durable execution, human-in-the-loop interrupts, and streaming (v1.2 in May 2026 added typed streaming, per-node timeouts, and distributed runtime), used in production by Klarna, LinkedIn, Uber, and Replit and serving as the substrate under Deep Agents.
The original open deep-research harness (Apache-2.0, 28k stars): a planner/executor multi-agent pipeline that fans out parallel web and local-document searches into cited reports, with recursive tree-like 'Deep Research', MCP data-source integration, and any-LLM support.
The leading TypeScript agent framework (Apache 2.0 core since July 2025; some enterprise features commercial) offering agents, type-safe workflows with suspend/resume human-in-the-loop, memory, a unified router to 3,300+ models across ~94 providers, guardrails/scorers/tracing, Mastra Studio for interactive testing, and file-based agent definitions added July 2026.