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Open-source alternatives to Cursor

The highest-scoring open-source projects in Coding agents and assistants. They are picks, not exact replacements, so read the weaknesses before you switch.

Open-source alternatives to Cursor
RankProjectScore
1opencodeTerminal coding agent with build and plan modesCoding agents and assistants, 212.5k stars, MIT77 out of 100
2orcaDesktop app that runs CLI coding agents in parallel git worktreesCoding agents and assistants, 89.1k stars, MIT75 out of 100
3ArchonYAML workflow engine that runs coding agents in isolated worktreesCoding agents and assistants, 23.7k stars, MIT73 out of 100
#4codexOpenAI's terminal coding agent that runs locallyCoding agents and assistants, 128.5k stars, Apache-2.071 out of 100
#5oh-my-openagentTerminal coding agent that runs parallel sub-agents and keeps git-based memoryCoding agents and assistants, 69.9k stars, custom license70 out of 100
#6deepseek-reasonixCoding agent for terminal, desktop, browser and VS Code, written in GoCoding agents and assistants, 35.8k stars, MIT70 out of 100
#7gemini-cliTerminal coding agent that runs Gemini models with file, shell and MCP toolsCoding agents and assistants, 107.3k stars, Apache-2.068 out of 100
#8OpenHandsWeb control center for running coding agents and scheduled automationsCoding agents and assistants, 90.5k stars, MIT68 out of 100
#9OpenChamberWorkspace for running and reviewing OpenCode coding agents across devicesCoding agents and assistants, 11.4k stars, MIT68 out of 100
#10Open SWELangChain coding agent that plans, implements and reviews pull requestsCoding agents and assistants, 11k stars, MIT68 out of 100

Reviews

177 out of 100

opencode

Terminal coding agent with build and plan modes

212.5k stars, MIT, last commit Oct 2026

Runs an AI coding agent in the terminal with two built-in agents: build (full access) and plan (read-only, asks before running bash), plus a general subagent for multi-step searches. Installs via a curl script, npm, Homebrew, Scoop, Chocolatey, pacman, mise or Nix, and ships a beta desktop app for macOS, Windows and Linux. For developers who want an open, configurable coding agent.

Strengths

  • MIT license; installable from npm, Homebrew, Scoop, Chocolatey, pacman, mise and Nix
  • Plan agent denies file edits and asks before bash, for safe codebase exploration
  • Desktop app (beta) for macOS, Windows and Linux alongside the terminal UI

Weaknesses

  • README covers install only; providers, config and server mode are in external docs
  • No Dockerfile or compose file in the repo
  • Desktop app is still beta
  • no GPU
Documentation ↗ (opens in a new tab)Website ↗ (opens in a new tab)Repository on GitHub ↗ (opens in a new tab)
275 out of 100

orca

Desktop app that runs CLI coding agents in parallel git worktrees

89.1k stars, MIT, last commit Oct 2026

Orca is a cross-platform desktop app (macOS, Windows, Linux) that runs several CLI coding agents side by side, each in its own isolated git worktree. It bundles terminals with splits, an editor, an embedded Chromium browser, GitHub and Linear task views, and diff annotation. A mobile companion app and an `orca` CLI let you monitor and script agent workflows.

Strengths

  • Works with any agent that runs in a terminal, including Claude Code, Codex, OpenCode, Pi
  • Each agent gets its own git worktree; fan one prompt across several and compare
  • Agents can run on a remote machine over SSH with port forwarding
  • MIT license; desktop builds for macOS, Windows, Linux plus Homebrew and AUR packages

Weaknesses

  • No Docker or self-hosted server install; it is a desktop app
  • Mobile pairing relay lives in a separate pnpm workspace under cloud/
  • Collects anonymous usage telemetry; opt-out is documented but not the default
  • Ships daily and the README says its feature list lags behind
  • no GPU
  • Needs git, CLI coding agent of your choice
Documentation ↗ (opens in a new tab)Website ↗ (opens in a new tab)Repository on GitHub ↗ (opens in a new tab)
373 out of 100

Archon

YAML workflow engine that runs coding agents in isolated worktrees

23.7k stars, MIT, last commit Oct 2026

Defines development processes (plan, implement, validate, review, PR) as YAML workflows and runs them through Claude Code, Codex or Pi, each run in its own git worktree. Deterministic nodes mix with AI nodes and human approval gates; runs start from the CLI, a web console, Slack, Telegram, Discord or GitHub webhooks, with state in SQLite or PostgreSQL. For teams standardizing how agents ship code.

Strengths

  • Every run isolated in a git worktree; parallel fixes without conflicts
  • Bundled sdlc pack: ship, triage, investigate, plan, deliver, review, validate, upkeep
  • Adapters for web, CLI, Slack, Telegram, Discord and GitHub webhooks
  • Telemetry documented field by field; DO_NOT_TRACK=1 or CI=true disables it

Weaknesses

  • Requires Claude Code (or Codex, Pi) installed separately; binaries need CLAUDE_BIN_PATH
  • Anonymous telemetry is on by default
  • x64 quick-install binaries require AVX2; older CPUs must build from source
  • Workflows from v0.11.1 and earlier no longer ship and must be copied manually
  • no GPU
  • Docker + Compose
  • Needs Bun, Claude Code (or Codex or Pi), GitHub CLI, SQLite or PostgreSQL
  • Models: Claude Code, Codex, Pi
Documentation ↗ (opens in a new tab)Repository on GitHub ↗ (opens in a new tab)
#471 out of 100

codex

OpenAI's terminal coding agent that runs locally

128.5k stars, Apache-2.0, last commit Oct 2026

Codex CLI is a coding agent from OpenAI that runs in the terminal on your machine. It installs through a shell script, npm, Homebrew, or prebuilt release binaries for macOS and Linux, and it signs in with a ChatGPT plan or an API key. The same project also covers IDE extensions and a desktop app.

Strengths

  • Prebuilt binaries for macOS and Linux on x86_64 and arm64
  • Multiple install paths: script, npm, Homebrew, or release archive
  • Sign-in with an existing ChatGPT Plus, Pro, Business, Edu, or Enterprise plan
  • Apache-2.0 license, written in Rust

Weaknesses

  • README documents only OpenAI sign-in or API key; other model providers are not mentioned
  • API key use requires extra setup beyond the quickstart
  • RAM and disk requirements are unknown
  • Install scripts fetch from OpenAI-hosted release URLs by default
  • no GPU
  • Needs ChatGPT account or OpenAI API key
  • Models: OpenAI models
Documentation ↗ (opens in a new tab)Website ↗ (opens in a new tab)Repository on GitHub ↗ (opens in a new tab)
#570 out of 100

oh-my-openagent

Terminal coding agent that runs parallel sub-agents and keeps git-based memory

69.9k stars, custom license, last commit Oct 2026

OmO ships a single `omo` command, a native binary built on senpi, the project's fork of pi. It takes a prompt and plans, runs and checks the work. Adding `ultrawork` or `mass ulw` makes it fan the job out to many agents, each on a model chosen for that step. Memory is stored as markdown files in a git repository, and `/login` supports Claude, ChatGPT, Kimi and GLM subscriptions.

Strengths

  • Native binary installs via curl script, bun or npm; no Docker needed
  • Logs in with Claude, ChatGPT, Kimi and GLM subscriptions
  • Memory is plain markdown in a git repo, so it can be inspected
  • `omo setup` migrates keys, MCP servers and skills from the OpenCode edition

Weaknesses

  • License is SUL-1.0, not a standard OSI license; check terms before commercial use
  • Install is a curl-pipe-to-bash script
  • Computer use is documented as experimental
  • Hardware needs and supported model list are not stated in the README
  • Models: Claude, ChatGPT, Kimi, GLM
Documentation ↗ (opens in a new tab)Website ↗ (opens in a new tab)Repository on GitHub ↗ (opens in a new tab)
#670 out of 100

deepseek-reasonix

Coding agent for terminal, desktop, browser and VS Code, written in Go

35.8k stars, MIT, last commit Oct 2026

Reasonix is a local coding agent that reads a project folder, edits files and runs commands and tests, asking for approval at a permission level you choose. DeepSeek is a built-in preset and any OpenAI-compatible endpoint is a config entry in reasonix.toml. The same engine backs the Studio desktop app, a terminal UI, a browser UI via `reasonix web`, and editors through ACP.

Strengths

  • Models are config entries in reasonix.toml; any OpenAI-compatible endpoint works
  • Static single binary built with CGO_ENABLED=0, cross-compiled to six targets
  • Per-turn rewind of files changed by its edit tools, independent of git
  • Same engine behind desktop, CLI, browser and ACP editor clients

Weaknesses

  • Rewind does not cover changes made by shell commands
  • Two release lines: 2.x is still changing quickly, 1.x is maintenance only
  • VS Code extension needs the separately installed 1.x CLI
  • Prompts and file contents go to whichever model provider you configure
  • no GPU
  • Needs Model provider API key, Go 1.25+ (build from source), Node 24+ and pnpm 10 (Studio build)
  • Models: DeepSeek (preset), OpenAI-compatible endpoints, MCP servers
Documentation ↗ (opens in a new tab)Website ↗ (opens in a new tab)Repository on GitHub ↗ (opens in a new tab)
#768 out of 100

gemini-cli

Terminal coding agent that runs Gemini models with file, shell and MCP tools

107.3k stars, Apache-2.0, last commit Oct 2026

Gemini CLI is a TypeScript terminal agent, installed from npm, Homebrew, MacPorts or conda, that sends prompts to Gemini models and can edit files, run shell commands, fetch web pages and ground answers with Google Search. It supports MCP servers, GEMINI.md context files, conversation checkpointing, a headless mode with JSON and stream-JSON output, and a GitHub Action for PR review and issue triage.

Strengths

  • Free tier with Google login: 60 requests/min, 1,000 requests/day
  • 1M token context window with Gemini 3 models
  • Headless mode emits plain text, JSON or newline-delimited stream-JSON
  • Auth via Google login, Gemini API key or Vertex AI

Weaknesses

  • Only talks to Gemini models; no other providers listed in the README
  • Needs a Google account, API key or Vertex AI credentials; no local models
  • Preview and nightly channels may contain regressions
  • Free-tier quotas and terms are governed by Google, not the project
  • no GPU
  • Docker
  • Needs Node.js, Gemini API, Google account login or Vertex AI
  • Models: Gemini 3, Gemini 2.5 Flash
Documentation ↗ (opens in a new tab)Website ↗ (opens in a new tab)Repository on GitHub ↗ (opens in a new tab)
#868 out of 100

OpenHands

Web control center for running coding agents and scheduled automations

90.5k stars, MIT, last commit Oct 2026

Agent Canvas is a web frontend that starts and manages conversations with coding agents. It runs the OpenHands agent by default and can drive Claude Code, Codex, Gemini CLI, Pi, OpenCode, or any ACP-compatible agent. It connects to one or more Agent Server backends (local, Docker, VM, or OpenHands Cloud) and pairs with an Automation Server for scheduled and webhook-triggered runs.

Strengths

  • Switches between local, remote and cloud Agent Server backends from one UI
  • Works with third-party agents through ACP, not only OpenHands
  • Option to run each conversation in its own Docker container
  • Automations can run on a schedule or on webhook events

Weaknesses

  • Marked beta in the README
  • Non-sandboxed install gives the agent full filesystem access
  • Needs Node.js 24+ and uv for non-Docker installs
  • Automation and agent server live in separate repositories
  • Docker
  • Needs Node.js 24+, uv, Docker (optional)
  • Models: Any LLM (via LLM profiles)
  • port 8000
Documentation ↗ (opens in a new tab)Repository on GitHub ↗ (opens in a new tab)
#968 out of 100

OpenChamber

Workspace for running and reviewing OpenCode coding agents across devices

11.4k stars, MIT, last commit Oct 2026

OpenChamber is a front end for OpenCode coding agents, shipped as a desktop app, web/PWA, VS Code extension, and iOS/Android clients. It adds session goals, multi-run comparison across up to five models, guided diff walkthroughs, GitHub issue and PR integration, and scheduled prompts. A CLI server runs on a workstation and can be reached through an encrypted relay, LAN, tunnels, or SSH.

Strengths

  • Multi-run sends one task to up to five models, each in its own worktree
  • Session Goals keep the agent working after a turn until the goal is met or blocked
  • Same sessions reachable from desktop, browser, VS Code, iOS and Android
  • Remote access via end-to-end encrypted relay needs no open ports

Weaknesses

  • Depends on OpenCode for agents; web and VS Code need a separate OpenCode install
  • CLI/Web requires Node.js 24.14 or newer
  • Docker deployment is not documented in the README
  • RAM, GPU needs and supported model providers are unknown
  • Docker + Compose
  • Needs OpenCode CLI, Node.js 24.14+
Documentation ↗ (opens in a new tab)Repository on GitHub ↗ (opens in a new tab)
#1068 out of 100

Open SWE

LangChain coding agent that plans, implements and reviews pull requests

11k stars, MIT, last commit Oct 2026

LangGraph-based agent that investigates a repository, implements changes in a per-thread Linux sandbox, validates them and opens a pull request, then reviews PRs and watches CI with /baby-sit. Work starts from a dashboard, GitHub issues or PR comments, Slack or Linear. Deploys into your infrastructure with a backend, dashboard, GitHub and Slack apps, for teams building an internal coding-agent service.

Strengths

  • Covers build, review, investigate and operate flows, with subagents for parallel work
  • Durable execution and thread state via LangGraph; sandboxes persist per thread
  • Configurable models, reasoning effort, skills, MCP integrations and sandbox providers
  • Push approvals gate detected git pushes; PR chat excludes mutation tools

Weaknesses

  • Production standalone Agent Server deployments require a license key
  • Maintainers are not accepting issues or contributions; breaking changes expected
  • LangSmith is the default sandbox and tracing provider; alternatives need configuration
  • CLI mode executes commands locally as you, with no sandbox isolation
  • no GPU
  • Docker + Compose
  • Needs LangSmith (default sandbox and tracing), GitHub App, Slack app (optional), model provider credentials
  • Models: configurable LLM providers
Repository on GitHub ↗ (opens in a new tab)