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CrabAgent - AI Agent Platform with dual-mode (CLI + Serve)

Project description

๐Ÿฆ€ CrabAgent

AI Team Command Center โ€” Build a team of specialized AI agents that learn and improve over time. Delegate, parallelize, and watch them work in real-time from terminal or browser.

CrabAgent is a local-first AI agent platform. Run it from any project directory via CLI or browser. Your data stays local, your API keys are encrypted, and you pick any LLM provider.


Why CrabAgent

Unlike other agent platforms where agents are "temporary workers who forget everything," CrabAgent's agents learn and evolve:

Capability What it means
๐Ÿง  Self-Evolving Agents Agents auto-extract lessons from every task โ€” rule engine catches patterns, LLM reflection analyzes strategies. The more you use them, the smarter they get.
๐Ÿค– AI Team Custom agent profiles with per-agent tool whitelists and model overrides. Delegate, parallelize, or run multi-step pipelines.
๐Ÿ“Š Agent Growth Tracking View each agent's stats: task count, success rate, lessons learned, common task categories. ctrl+space agent_stats
โฑ Scheduled + Real-time Agents run on cron schedules or react to @mentions. Real-time streaming of every agent's output.
๐Ÿฆ€ Snapshots Auto-snapshot files before changes. Roll back anytime without Git.
๐Ÿ”’ Local-first All data stays on your machine. API keys encrypted at rest. No telemetry.

Quick Start

pip install 'crabagent[serve]'

crabagent init

# TUI โ€” interactive REPL with slash commands
crabagent

# TUI (legacy single-panel)
crabagent --old

# Web UI
crabagent --serve          # โ†’ http://localhost:5210
                           # Default login: admin / xcl1989

# Single-query CLI
crabagent "organize this directory"
crabagent -p deepseek -m deepseek-chat "write a Python script"

Self-Evolving Agents

This is CrabAgent's core differentiator. Agents don't just execute tasks โ€” they learn from every execution.

How it works

Sub-agent completes task
    โ”‚
    โ”œโ”€ Rule Engine (instant)
    โ”‚   โ””โ”€ High iterations (>80% max) โ†’ "Decompose complex tasks, use fewer tools per step"
    โ”‚
    โ””โ”€ LLM Reflection (~1-3s)
        โ”œโ”€ Extracts concrete, actionable insights:
        โ”‚   "When searching Chinese news, use English keywords on DuckDuckGo for better results"
        โ”‚   "For error-prone sites, prefer web_scrape with direct URLs over web_search"
        โ”œโ”€ Auto-filters generic/noise responses ("completed in X steps")
        โ”œโ”€ Also learns from failures: captures what went wrong and how to avoid it
        โ””โ”€ Source: llm

Knowledge persistence

  • Team Knowledge: Tech stack, architecture decisions, user preferences โ€” auto-injected into every session
  • Agent Lessons: Per-agent concrete insights grouped by category (Pitfalls / What Worked) โ€” loaded before similar tasks
  • Task Records: Every execution logged (success, elapsed time, tokens, iterations)

Tracking growth

# TUI
/agent_stats coder
# โ†’ ๆ€ปไปปๅŠก: 23  ๆˆๅŠŸ็އ: 91%  ๅนณๅ‡่€—ๆ—ถ: 14s
# โ†’ lessons: 18 (่ง„ๅˆ™: 3, LLM: 15)

# Web UI
# โ†’ Agent Team โ†’ Learning Stats: click agent name to see stats + all lessons

---

## AI Team

### Built-in agents

| Agent | Role | Best For |
|-------|------|----------|
| ๐Ÿ” Researcher | Web research | Search, browse, data collection |
| ๐Ÿ“Š Analyst | Data analysis | Comparison, pattern detection, reports |
| ๐Ÿ’ป Coder | Code expert | Write, review, debug, refactor |
| ๐Ÿ“ Writer | Content writer | Write, edit, translate, format |

### Delegation

- `@researcher find competitor pricing` โ€” @mention auto-delegates
- Click an agent from the toolbar to insert a mention
- `/delegate` command for interactive agent selection
- `delegate_parallel` runs multiple agents simultaneously
- `run_pipeline` chains agents with dependencies

### Session Agent Switching

Switch your current agent identity mid-session without losing conversation history:

```bash
# TUI
/agent                  # Popup menu: select from 5 agents
/agent researcher       # Direct switch
/agent default          # Back to all tools

# Web API
POST /api/sessions/{id}/agent  {"agent": "researcher"}
  • Each agent has different tool sets (researcher gets web tools, coder gets bash+edit, etc.)
  • System prompt stays unchanged โ€” LLM KV cache preserved across switches
  • All messages are tagged with agent info for history tracking
  • Model auto-switches if the agent profile specifies one
  • Status bar shows current agent: [deepseek/chat โ†’ researcher] Msgs:5 Tok:1234

Real-time monitoring

  • ๐ŸŸฃ Running โ€” live step count and timer
  • ๐ŸŸข Done โ€” elapsed time, tokens, iterations
  • ๐Ÿ”ด Error โ€” error summary
  • Web: right-side Task Board with split-pane result comparison

More Features

๐Ÿ–ผ๏ธ Multimodal

Paste, upload, or drag images. Auto-detects vision models.

๐ŸŒ Browser Automation

pip install 'crabagent[browser]' + playwright install chromium

> Open https://news.ycombinator.com and show top 5 stories
> Search "Python async" on Google

๐Ÿ”Œ MCP Client

Connect external MCP servers (stdio + HTTP). Tools auto-discover.

๐Ÿ“‹ Scheduled Tasks

> Remind me every day at 11:00 to drink water
> Check product page every 30 minutes, notify if price drops

๐Ÿฆ€ Snapshots

Auto-snapshot before file changes. Roll back with /molt rollback <id>.

๐Ÿ”ง Custom Plugins

Drop a .py file in .crabagent/tools/:

name = "hello"
description = "Say hello"
parameters = {"type": "object", "properties": {"name": {"type": "string"}}, "required": ["name"]}
requires_permission = False

def run(name: str) -> str:
    return f"Hello, {name}!"

Or let agents create tools themselves โ€” Your agent can write and register custom tools during a session. Tell it what you need and it will generate, validate, and save the tool:

> Create a tool that parses CSV files and extracts a column
> Create a tool to fetch weather for a city

Tools are saved to .crabagent/tools/, auto-registered, and persist across sessions. The agent remembers its created tools via team memory.


CLI / TUI Commands

Command Description
/exit, /quit Exit
/help Show help
/clear Clear context
/model [name] Switch model
/models List models
/provider [cmd] Manage providers
/sessions / /session [id] List / load sessions
/new New conversation
/agents [cmd] Agent team management
/agent [name] Switch current agent
/agent_stats <name> Agent growth stats
/delegate [@agent] [task] Delegate task
/memory [list|search|clear] Team memory
/skills / /skill <name> List / show skills
/molt [cmd] Snapshots
/todo [cmd] Task list
/export Export to Markdown
/image <path> [msg] Send image
/runs [agent] View agent run history
/abort Abort current agent (Ctrl+C)

Configuration

Variable Default Description
CRAB_DB_URL sqlite+aiosqlite:///./crabagent.db Database URL
CRAB_JWT_SECRET Auto-generated JWT signing key
CRAB_SERVE_HOST 0.0.0.0 Serve host
CRAB_SERVE_PORT 5210 Serve port
CRAB_MAX_ITERATIONS 50 Max agent iterations
CRAB_MAX_TOKENS 4096 Max response tokens
CRAB_BROWSER_HEADLESS true Browser headless mode
CRAB_WEB_PROXY (empty) HTTP proxy for web_search & web_scrape

v0.7.4 Highlights

  • ๐Ÿ”„ Session Agent Switching โ€” Switch agent identity mid-session with /agent (TUI) or POST /api/sessions/{id}/agent (API). Each agent has different tool sets, and messages are tagged with agent info for history tracking.
  • ๐Ÿ› ๏ธ Agent-Created Custom Tools โ€” Agents can now write and register their own reusable tools via create_tool/update_tool/delete_tool. Code is validated, saved to .crabagent/tools/, registered immediately, and auto-loads across sessions.
  • ๐Ÿ› TUI Queue & History Fixes โ€” Fixed race condition where queued inputs were sent before previous rendering completed. Fixed message ordering in DB when loading sessions with queued messages via persistence flush improvements.
  • ๐Ÿ”ค TUI CJK & Thinking Fixes โ€” Fixed CJK character rendering freeze in dual-panel TUI. Fixed thinking text display bugs (off-by-one, cache miss on content update, prefix loss on flush).

v0.7.2 Highlights

  • ๐Ÿ–ฅ๏ธ Dual-Panel TUI โ€” New prompt_toolkit-based full-screen TUI: scrollable output panel (mouse wheel + PageUp/Down/Home/End), persistent input area that auto-grows with content, and real-time status bar. Default mode (crabagent), use --old for legacy TUI.
  • ๐Ÿ–ฑ๏ธ Mouse Text Selection โ€” Hold Shift + mouse drag to select text in the output area. Ctrl+C copies to clipboard (macOS pbcopy / Linux xclip).
  • ๐Ÿ’ฌ Interactive Popup Menus โ€” /model, /sessions, /provider now show scrolling selection popups with arrow key navigation, instead of printing long lists.
  • ๐Ÿง  Streaming Thinking โ€” Agent reasoning (THINKING_DELTA) streams in real-time to the output panel, dim italic style.
  • ๐Ÿ’ก Completions Menu โ€” Slash command autocomplete appears as a floating completions menu above the input area.

v0.7.1 Highlights

  • ๐Ÿ“Š Pipeline Dashboard โ€” Real-time pipeline visualization: see active pipelines with step progress, agent cards with running counts, and growth charts. History pipelines auto-collapsed.
  • ๐Ÿ”„ AgentRun Persistence โ€” New agent_runs table tracks every agent/pipeline execution with full metadata (tool calls, elapsed time, tokens, iterations). API endpoints for run history and per-agent growth stats.
  • ๐Ÿ› Streaming Fix โ€” TEXT_DELTA and THINKING_DELTA events are no longer throttled/dropped by SSE forwarder. TEXT_DONE handler now uses full text from backend to ensure complete message display.
  • ๐Ÿ›  Tool Display Fix โ€” delegate_parallel arguments with nested objects no longer show [object Object] in the UI.
  • ๐Ÿ“ก RunRecorder โ€” EventBus subscriber that creates agent_runs records for pipeline, main, and sub-agent executions in real-time.

v0.7.0 Highlights

  • ๐Ÿง  Learning quality overhaul โ€” LLM reflection now extracts actionable insights (tool tricks, pitfalls, domain tips), no more "completed in X steps" noise. Failure learning added โ€” agents learn from mistakes too.
  • ๐ŸŒ Web proxy support โ€” CRAB_WEB_PROXY=http://127.0.0.1:7890 for web_search/web_scrape (critical for users behind firewalls).
  • ๐Ÿ“Š Learning Dashboard โ€” View each agent's task stats and past lessons directly in the Web UI Agent Team panel.
  • ๐Ÿ“ก Sub-agent persistence โ€” Completed sub-agents stay visible in the Dashboard for 30 minutes after finishing.

Installation

pip install 'crabagent[serve]'          # Web UI + API
pip install 'crabagent[browser]'        # Browser automation
pip install 'crabagent[dev]'            # Testing + linting
# Development
make install            # Build frontend + install (editable)
ruff check src/ tests/  # Lint
ruff format src/ tests/ # Format
pytest                   # Run tests

Project Structure

CrabAgent/
โ”œโ”€โ”€ src/crabagent/
โ”‚   โ”œโ”€โ”€ cli/           # CLI entrypoint + TUI
โ”‚   โ”œโ”€โ”€ core/agent/    # Agent loop, tools, compression, agents
โ”‚   โ”œโ”€โ”€ core/mcp/      # MCP client manager
โ”‚   โ””โ”€โ”€ serve/         # FastAPI + API + scheduler
โ”œโ”€โ”€ frontend/          # React SPA
โ””โ”€โ”€ crabagent.db       # SQLite database

License

GNU Affero General Public License v3 (AGPLv3) for non-commercial use. Commercial use requires a separate license. Contact the author.

See LICENSE.

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