Open Source Coding Agents, Compared
Every agent below ships under a licence GitHub could identify, and every one carries the same FARS review, so the numbers are comparable rather than borrowed from each project's own README. The table leads with the review; the sections under it carry each agent's own positioning, including where its documentation says it is not the right fit.
| # | Agent | FARS | Trust | Stars | License | Language | Last commit |
|---|---|---|---|---|---|---|---|
| 1 | elizaOS | 88 | 24/25 | 19.2k | MIT | TypeScript | 2026-09-02 |
| 2 | Unlazy Completion Discipline | 86 | 25/25 | 3.0k | MIT | JavaScript | 2026-08-29 |
| 3 | Better Harness | 85 | 23/25 | 2.1k | MIT | JavaScript | 2026-09-02 |
| 4 | Apache Maka | 82 | 22/25 | 4.6k | Apache-2.0 | TypeScript | 2026-09-02 |
| 5 | JS Reverse MCP | 82 | 21/25 | 2.7k | Apache-2.0 | TypeScript | 2026-08-25 |
| 6 | NotebookLM Python Automation | 81 | 21/25 | 19.1k | MIT | Python | 2026-09-02 |
| 7 | ADK Agent Recipes ✓ Google | 81 | 23/25 | 10.3k | Apache-2.0 | Python | 2026-09-01 |
| 8 | Kungfu | 81 | 18/25 | 4.5k | Apache-2.0 | C++ | 2026-09-02 |
| 9 | Osaurus | 80 | 22/25 | 7.8k | MIT | Swift | 2026-09-02 |
| 10 | Chrome DevTools MCP | 79 | 17/25 | 50.6k | Apache-2.0 | TypeScript | 2026-09-02 |
| 11 | LangWatch | 78 | 19/25 | 3.5k | Apache-2.0 | TypeScript | 2026-09-02 |
| 12 | Harmonist | 78 | 21/25 | 2.3k | MIT | Python | 2026-06-09 |
The order is the FARS total; stars only break ties, because popularity measures attention rather than whether something holds up. Two limits are worth knowing before you read the order. These are static reviews — source, documentation and repository metadata, with no runtime reproduction — which caps reliability, effectiveness and verifiability and puts the achievable maximum at 77 rather than 100. And a gap of a few points sits inside the noise of that method. Read the table as a shortlist worth investigating, not as a verdict; every score links to its full dimension breakdown and the evidence behind it. Review method →
1. elizaOS
An open-source TypeScript system for building, running, and extending autonomous AI agents.
Where it differs
Compared with the optional Eliza Cloud path, the local runtime and direct-provider configuration remain first-class options: Eliza Cloud adds accounts, authentication, hosted model routing, application and agent deployment, remote connectivity, and cross-device services, while the other paths preserve more direct runtime and provider control. For whole-device delivery, this monorepo retains Eliza application shells and native runtime bridges, whereas the separate elizaOS/os repository owns bootable Linux and AOSP distributions, installers, release manifests, and OS toolchains.
2. Unlazy Completion Discipline
Keep AI agents from finishing early with deep decomposition, acceptance ledgers, and executable gates.
3. Better Harness
Diagnose and improve coding-agent workflows with verifiable evidence.
4. Apache Maka
A local-first agent workspace that performs project work while preserving recoverable execution records.
5. JS Reverse MCP
Continuous browser-side JavaScript debugging and replay for AI coding assistants.
Where it differs
Unlike exposing the Chrome DevTools API to a model unchanged, JS Reverse MCP groups scripts, breakpoints, traffic, WebSockets, state, and local files into primitives for sustained analysis. The default Patchright mode uses the installed Google Chrome and retains access to the Web Store, extensions, and sync; --cloak instead uses a CloakBrowser binary with C++-level fingerprint patches but no Google services or Web Store. The project positions anti-detection as support for the debugging chain, not as a general-purpose crawling framework.
6. NotebookLM Python Automation
Automate Gemini Notebook research, generation, and exports through Python, CLI, or coding agents.
Where it differs
Compared with the Gemini Notebook web interface, notebooklm-py emphasizes scripted control and local extraction. It supports batch downloads, structured quiz and flashcard exports, mind-map JSON, CSV data tables, source full text, individual slide revision, and programmatic sharing. That additional reach comes with greater maintenance risk because the client relies on undocumented endpoints rather than an official Google SDK.
7. ADK Agent Recipes
Start ADK agent projects from small, runnable reference implementations.
8. Kungfu
Keep one body of work moving across agents, sessions, and failures.
Where it differs
Compared with manually copying chats and re-explaining decisions when moving among Codex, Claude, OpenCode, or Amp, Kungfu keeps the Work objective, evidence, progress, and Attempt history outside those sessions. It complements rather than replaces these agents, and its TUI and GUI are optional sidecar views rather than substitutes for native agent consoles.
9. Osaurus
A native Mac harness for persistent, tool-using AI agents that can run with local or cloud models.
10. Chrome DevTools MCP
Give coding agents direct Chrome automation, debugging, and performance analysis.
Where it differs
Full mode targets deep debugging with automation, performance, network, console, and optional specialist categories; --slim exposes only navigation, script execution, and screenshots for basic browser work and a smaller tool surface. The MCP server is intended for structured integration with compatible coding clients, while the included CLI covers use without MCP. Launching a dedicated Chrome profile provides separation from everyday browsing, whereas attaching to an existing Chrome preserves logins and manual testing state at the cost of greater data-exposure risk.
11. LangWatch
Evaluate, test, trace, and monitor LLM applications and AI agents across development and production.
Where it differs
Compared with assembling separate tracing, dataset, evaluation, and prompt-optimization systems, LangWatch explicitly combines them into a trace → dataset → evaluate → optimize → re-test loop. Its OpenTelemetry foundation also allows compatible tracing libraries beyond the directly named framework integrations.
12. Harmonist
An IDE-hooked multi-agent workflow that enforces review, memory, and integrity checks for AI-assisted coding.
Where it differs
Harmonist positions itself as a project-local governance layer for AI-assisted coding, not as a replacement for LangChain, CrewAI, AutoGen, or MetaGPT. The repository describes those projects as orchestration primitives for building agentic applications, while Harmonist uses IDE hooks to govern review, memory, and completion behavior in the coding workflow; the two approaches can coexist.