tars

module
v0.12.0 Latest Latest
Warning

This package is not in the latest version of its module.

Go to latest
Published: Mar 27, 2026 License: MIT

README

TARS

CI codecov Go Release

TARS is a local-first AI project autopilot.

Unlike Claude Code, Aider, or Cursor, which mostly operate at the file and conversation level, TARS manages long-running projects autonomously: it plans phases with you, executes backlog work inside each phase, coordinates tools and worker agents, and only brings you back for approvals or real blockers. All in a single Go binary running on your machine.

Key Features

Project Autopilot

The killer feature. Describe what you want to build, and TARS handles the rest:

  1. Plan — Collects requirements through a short interview and turns them into a phase plan
  2. Phase Loop — Builds a backlog, selects the next task, executes it, evaluates the result, and replans when needed
  3. Capabilities — Combines built-in tools, skills, MCP servers, web research, and worker agents in one runtime
  4. Human-in-the-Loop — Escalates at phase approvals and real blockers instead of asking for every routine retry
  5. Dashboard — Live phase status, run status, pending decisions, blockers, and worker reports in a browser
tars init && tars serve
# In the TUI:
> todo 앱 만드는 프로젝트 시작해줘
Agent Runtime
  • Terminal client with a Bubble Tea TUI + local HTTP API (tars serve)
  • Session lifecycle, transcript storage, and structured context compaction
  • Agent loop with built-in file, process, scheduling, memory, and ops tools
  • Built-in file tools with 2,000-line read pagination, continuation hints, and safe atomic writes
  • Structured session compaction with identifier-preserving summaries, a safer recent-tail preserve policy, and manual /compact [instructions]
  • Parallel read-only chat subagents through the built-in explorer gateway agent
  • MCP transports for local stdio servers and remote HTTP/WebSocket endpoints, with bearer or OAuth auth for remote servers
  • Semantic memory recall with Gemini embeddings (optional)
  • Playwright-based browser automation
Extensibility
  • Skill Hubtars skill search, tars plugin install, and tars mcp install from a vetted registry
  • Plugins — Bundle skills and MCP servers with manifest metadata, runtime gating, and default project profiles
  • Managed MCP Hub — Install checksum-verified MCP packages hosted in tars-skills
  • Skills — LLM instruction files (SKILL.md) with companion scripts and runtime gating by plugin, binary, env, and platform requirements

Install

Homebrew:

brew tap devlikebear/tap
brew install devlikebear/tap/tars

Curl:

curl -fsSL https://raw.githubusercontent.com/devlikebear/tars/main/install.sh | sh

Quick Start

# 1. Initialize workspace and config
tars init

# 2. Set your LLM provider
export OPENAI_API_KEY="your-api-key"
# Or use Claude Code CLI: set llm_provider: claude-code-cli in config

# 3. Validate setup
tars doctor --fix

# 4. Start the server
tars serve --config ./workspace/config/tars.config.yaml
# Or as a macOS background service:
tars service install && tars service start

# 5. Launch the TUI client
tars

Kick off a project from chat, or use the TUI commands directly:

/project board <project-id>
/project autopilot start <project-id>
/project autopilot advance <project-id>

The recommended path is planning first, then controlled phase advancement. advance runs one synchronous autopilot step so you can inspect approvals, blockers, and replans explicitly.

For read-heavy codebase research in chat, TARS can now fan out parallel explorer subagents and merge back compact summaries. The runtime defaults are:

gateway_subagents_max_threads: 4
gateway_subagents_max_depth: 1

Open the dashboard: http://127.0.0.1:43180/dashboards

Install trusted MCP packages from the hub:

tars mcp search
tars mcp install safe-time

Local stdio MCP servers still respect mcp_command_allowlist_json. For example, a Node-based MCP package requires a config allowlist such as:

mcp_command_allowlist_json: ["node"]

Requirements

  • Go 1.25.6+ (for building from source)
  • LLM provider credentials, or a local Claude Code CLI install
  • Optional: Gemini API key for semantic memory embeddings
  • Optional: Node.js for Playwright browser automation

Build

make build-bins
bin/tars version

Documentation

Status

Pre-1.0.0 — Module path: github.com/devlikebear/tars

Jump to

Keyboard shortcuts

? : This menu
/ : Search site
f or F : Jump to
y or Y : Canonical URL