Welcome Contributing! Windows First!

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Lightweight • Secure • Practical Agent

🔥 CloseClaw is a lightweight, security-focused and practical OpenClaw-style Python framework. It is an personal agent for local and channel-based automation, with built-in guardrails, task scheduling, and memory infrastructure.

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🤔 Why CloseClaw

• ⚡ Fast to Deploy

• Lightweight, Easy-to-Deploy, and equipped with a guarded orchestration loop to ensure robust performance. Practical personal AI agents, ready in a minute.

• 🧠 Structured Memory Management

• A structured Memory Management System, including long-term memory constrcution and vectorized memory retrieval support. Long-term memory guaranteed. Fully customizable cognition.

• 🛡️ Effective Security Assurance

• A clear and rigorous Sandbox Permission System, including an Guardian-Review mechanism and lightweight Windows OS-level Sandbox. Stop worrying about AI hallucinations deleting your inbox.

• 💓 Proactive Execution

• Equipped with Heartbeat and Cron services to support handling any scheduled tasks and wake up periodically to deal with long-term tasks automatically. Proactive Agent, always be with you.

• 🔌 MCP Extensibility

• Supporst MCP-Native Extensibility, Being compatible with any OpenClaw skills and tools. Massive ecosystem. Easy to arm your agent.

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✨ Key Features

[!IMPORTANT] Guardian Mechanism Traditional sandboxes mainly protect local files. CloseClaw Guardian Agent also protects connected assets (mailboxes, cloud repos, third-party APIs) and any MCP touchable content.

👮 Guardian Monitor Design

• Guardian Agent reviews actions intelligently and intercepts high-impact connected actions before execution.
• Keeps MCP/network tools under the same safety policy, allowing to configure freely the High-risk tool supervision pool in config.yaml.

🔒 Consensus Mode = Safer Automation

• In consensus mode, Guardian Agent can auto-review sensitive calls first.
• Reduces constant approval fatigue while preserving strict control.

🧱 Solid Local Foundation

• PathSandbox enforces hard local boundaries inside workspace_root.
• Blocks path traversal and out-of-workspace writes before tool execution.

🪟 OS-Level Lightweight Sandbox

• Restricted Token, Low Integrity and Job-Object constraints enforce OS-level restricted execution for protected tools (default: shell).
• Higly customizable: only tools in os_sandbox_protected_tools pay the isolation cost; low-risk tools (e.g. read_file) stay fast.
• Fail-safe option supported: os_sandbox_fail_closed: true blocks execution when sandbox backend is unavailable.

Tool Call
  -> SafetyGuard 
  -> PathSandbox 
  -> Guardian/Auth 
  -> OS-Level Sandbox
  -> Execute

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📡 Channel Support

Channel	Positioning	Startup Hint
CLI	💻 Fast, local, and pipe-friendly	Local interactive terminal
Telegram	✈️ Mobile command center (Recommended)	Polling started
Feishu / Lark	🏢 Professional workflow	Prints webhook address (host/port)
Discord	🎮 Rich markdown support	Gateway started
WhatsApp	🟢 Reachable on networks via bridge	Prints bridge URL
QQ	🐧 Classic Chinese social ecosystem	Gateway started

WhatsApp bridge protocol details:

• docs/WhatsApp_Bridge_Protocol.md

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🤖 LLM Providers

Provider	Runtime Path	Notes
openai / openai-compatible	Native provider path	Default-friendly, quick setup
gemini	LiteLLM runtime	Requires .[providers] extra
anthropic	LiteLLM runtime	Requires .[providers] extra

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🚀 Quick Start

1) Install

git clone https://github.com/closeclaw/closeclaw.git
cd closeclaw
pip install -e .

Optional extras:

pip install -e ".[telegram]"
pip install -e ".[discord]"
pip install -e ".[whatsapp]"
pip install -e ".[qq]"
pip install -e ".[voice]"
pip install -e ".[fastapi]"
pip install -e ".[providers]"

📝 .[providers] installs litellm, required for gemini and anthropic provider modes. 📝 .[voice] installs faster-whisper for channel voice transcription. You also need ffmpeg available in PATH.

2) Create config

cp config.example.yaml config.yaml

Minimal config:

agent_id: "closeclaw-main"
workspace_root: "your/workspace"

llm:
  provider: "openai-compatible"
  model: "gpt-4"
  api_key: "sk-..."
  base_url: "https://api.openai.com/v1"

channels:
  - type: "cli"
    enabled: true

safety:
  admin_user_ids: ["cli_user"]
  default_need_auth: false

3) Run

Agent mode (CLI only):

closeclaw agent --config config.yaml

Gateway mode:

closeclaw gateway --config config.yaml

✨And that's your agent!

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🐳 Docker (Optional)

Docker support is optional. If you want a reproducible runtime and easier deployment handoff, use this section.

1) One-time prep (copy/paste)

macOS/Linux:

cp .env.example .env
cp config.example.yaml config.yaml
mkdir -p workspace runtime-data

Windows PowerShell:

Copy-Item .env.example .env
Copy-Item config.example.yaml config.yaml
New-Item -ItemType Directory -Force -Path workspace, runtime-data

2) Minimal required config check

In config.yaml, make sure:

• workspace_root: "/workspace" (important for Linux containers)
• At least one channel is enabled for your target mode:
  • agent mode: cli can be enabled
  • gateway mode: at least one non-CLI channel must be enabled
• Your provider/channel dependencies are included in .env INSTALL_EXTRAS
  • Example for Telegram gateway: INSTALL_EXTRAS=[providers,telegram]

3) Build and start (docker compose recommended)

docker compose build
docker compose up -d closeclaw-gateway
docker compose ps
docker compose logs -f closeclaw-gateway

4) Health verification (important)

Gateway container health:

docker compose exec closeclaw-gateway closeclaw runtime-health --config /app/config.yaml --mode gateway --json

CLI profile health:

docker compose run --rm closeclaw-cli runtime-health --config /app/config.yaml --mode agent --json

Expected result:

• Exit code 0
• JSON contains "healthy": true

5) Common mistakes (quick fix)

• workspace_root does not exist: /app/D:
  • Cause: Windows path in config.yaml inside Linux container.
  • Fix: set workspace_root: "/workspace".
• No channels enabled for mode=gateway
  • Cause: only CLI enabled while running gateway mode.
  • Fix: enable at least one non-CLI channel.
• python-telegram-bot is required
  • Cause: channel dependency not installed in image.
  • Fix: set .env INSTALL_EXTRAS=[providers,telegram], then rebuild.
• docker compose run --rm closeclaw-cli closeclaw ... fails
  • Cause: duplicated closeclaw command.
  • Fix: use docker compose run --rm closeclaw-cli runtime-health ....

6) Stop and cleanup

docker compose down

7) Optional smoke test script

Run with Bash:

bash tests/test_docker.sh

On PowerShell, call Bash explicitly:

bash tests/test_docker.sh

Operational hardening details are documented in docs/Docker_Runbook.md.

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🎯 Run Modes

Mode	What runs	Typical usage
agent	CLI only	Local interactive debugging / development
gateway	Non-CLI channels only	Bot gateway deployment
all	CLI + all enabled channels	Full local integration run

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🧱 Architecture Overview

closeclaw/
├─ runner.py                              # Runtime entry + channel/heartbeat/cron orchestration
├─ agents/
│  └─ core.py                             # AgentCore: orchestration loop and execution lifecycle
├─ services/
│  ├─ tool_execution_service.py           # Tool routing + middleware + auth handling
│  └─ context_service.py                  # Context shaping, compaction, transcript windowing
├─ memory/
│  └─ memory_manager.py                   # Memory retrieval and persistence coordination
├─ channels/                              # CLI / Telegram / Feishu / Discord / WhatsApp / QQ adapters
├─ tools/                                 # File / Shell / Web / Scheduler / Memory helper tools
└─ mcp/                                   # MCP transport, pool, bridge, and health integration

Core responsibilities

• runner: startup orchestration (channels, heartbeat, cron, agent lifecycle)
• AgentCore: orchestration loop + tool decision and execution flow
• ToolExecutionService: tool routing, middleware, auth interactions
• ContextService: transcript shaping and compaction policy
• MemoryManager: memory retrieval and persistence layer

Main modules

• closeclaw/runner.py
• closeclaw/agents/core.py
• closeclaw/services/tool_execution_service.py
• closeclaw/services/context_service.py
• closeclaw/memory/memory_manager.py

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🔐 Security Model

CloseClaw applies layered controls:

1. ✅ Human authorization
   • Tools with need_auth=True require explicit approval.
2. ✅ Workspace sandbox
   • File paths normalized and constrained to workspace_root.
3. ✅ Command blacklist
   • High-risk shell patterns blocked before execution.
4. ✅ Audit logging
   • Runtime operations logged to safety.audit_log_path.

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🧰 Built-in Tooling

Tool groups:

• 📁 File tools: read/write/edit/delete/list/exists/size/line-range ops
• 🖥️ Shell tools: shell execution + pwd
• 🌍 Web tools: web_search + fetch_url
• ⏲️ Scheduler helper: call_cron
• 🧠 Memory helpers: write/edit memory file

Web search behavior:

• Provider currently targets Brave Search API
• Disabled by default until web_search.enabled=true and key is configured

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⚙️ Configuration Reference

llm

Key fields: provider, model, api_key, base_url, temperature, max_tokens, timeout_seconds

Gemini example:

llm:
  provider: "gemini"
  model: "gemini-2.5-flash"
  api_key: "YOUR_GEMINI_API_KEY"
  temperature: 0.2
  max_tokens: 4096

Anthropic example:

llm:
  provider: "anthropic"
  model: "claude-3-7-sonnet"
  api_key: "YOUR_ANTHROPIC_API_KEY"
  temperature: 0.2
  max_tokens: 4096

web_search

web_search:
  enabled: false
  provider: "brave"
  brave_api_key: "BSA-..."
  timeout_seconds: 30

Other high-impact sections

• safety: admins, default auth, blacklist, audit settings
• context_management: token windows, thresholds, retention
• orchestrator: steps, wall-time, no-progress limits
• heartbeat: interval, quiet-hours, queue guards, routing
• cron: store path, timezone, enable/disable

Memory and Soul (workspace personalization)

After first run, go to your workspace-local folder:

<workspace_root>/CloseClaw Memory/

You can personalize runtime behavior by editing these files:

• AGENTS.md: agent policy/persona and collaboration preferences
• SOUL.md: long-term identity, tone, and behavioral style
• USER.md: user-specific preferences and constraints
• TOOLS.md: tool usage conventions and boundaries
• SKILLS.md: skill-level guidance and trigger conventions
• HEARTBEAT.md: periodic proactive behavior instructions
• memory/YYYY-MM-DD.md: day-level memory notes and context snapshots

Tips:

• Keep instructions concise, explicit, and conflict-free.
• Prefer stable rules in SOUL.md and task-scoped guidance in daily memory/ notes.
• If behavior drifts, review AGENTS.md + SOUL.md first, then prune conflicting notes.

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📦 MCP Setup Tutorial

CloseClaw supports:

• MCP server health diagnostics
• MCP tool projection via MCPBridge

Step 0: Plan server layout

<repo-root>/
  mcp_servers/
    weather_server/
    docs_server/

Step 1: Prepare servers

• Python server in repo, or
• npm-hosted server via npx / npx.cmd

Step 2: Configure in config.yaml

mcp:
  servers:
    - id: "local-stdio"
      transport: "stdio"
      command: "python"
      args: ["-m", "your_mcp_server"]
      timeout_seconds: 30

    - id: "remote-http"
      transport: "http"
      base_url: "https://example.com"
      endpoint: "/mcp"
      timeout_seconds: 15
      max_retries: 2
      retry_backoff_seconds: 0.2

Step 3: Verify health

closeclaw mcp --config config.yaml
closeclaw mcp --config config.yaml --json

Step 4: Start runtime

closeclaw agent --config config.yaml

✅ Runner auto-loads configured MCP servers and syncs tool schemas into runtime.

Step 5: Troubleshoot quickly

• stdio unhealthy: verify command and args manually
• http unhealthy: verify base_url + endpoint reachability
• config ignored: verify same file passed via --config
• tools not selected: check bootstrap path and tool-name conflicts

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🧠 Memory Layout

<workspace_root>/
  CloseClaw Memory/
    state.json
    audit.log
    memory.sqlite
    HEARTBEAT.md
    MEMORY.md
    AGENTS.md
    SOUL.md
    USER.md
    TOOLS.md
    SKILLS.md
    memory/
      YYYY-MM-DD.md

Why this layout:

• Keeps operational artifacts out of source roots
• Makes backup and migration easier
• Supports deterministic upgrades from legacy scattered paths

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🧪 Testing

Focused suites:

python -m pytest tests/test_config.py -q
python -m pytest tests/test_tools.py tests/test_tool_execution_service.py -q
python -m pytest tests/test_runner.py tests/test_heartbeat_service.py tests/test_cron_service.py -q

Full suite:

python -m pytest tests -q

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🔁 Migration Notes

Compatibility behavior includes:

• legacy state.json upgrade to CloseClaw Memory/state.json
• legacy phase5 config key mapped to orchestrator
• memory artifacts migrated into unified layout when possible

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🩺 Troubleshooting

1. Web search key missing

• set web_search.enabled=true
• set web_search.provider=brave
• set valid web_search.brave_api_key

2. Tool calls require approval unexpectedly

• check safety.default_need_auth
• check tool-level need_auth behavior

3. Heartbeat not firing

• check heartbeat.enabled
• check CloseClaw Memory/HEARTBEAT.md
• check quiet-hours + queue guard settings

4. Cron inactive

• check cron.enabled
• check cron.store_file write permissions
• use cron list/run-now diagnostics

🪟 Windows Notes (Entry Command Not Found)

If PowerShell says closeclaw is not recognized:

1. Activate your virtual environment.
2. Reinstall editable package so scripts are generated.
3. Use module mode as fallback.

pip install -e .
python -m closeclaw agent --config config.yaml
Get-Command closeclaw

ℹ️ If Get-Command closeclaw returns nothing, current shell PATH does not include the generated entrypoint.

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🤝 Contributing Guide

Contributions are welcome and appreciated.

1) Fork and create a feature branch

git checkout -b feat/your-change-name

2) Run tests locally before opening a Pull Request

Focused suites:

python -m pytest tests/test_config.py -q
python -m pytest tests/test_tools.py tests/test_tool_execution_service.py -q
python -m pytest tests/test_runner.py tests/test_heartbeat_service.py tests/test_cron_service.py -q

Full suite:

python -m pytest tests -q

3) Submit a Pull Request

Please include:

• clear problem statement and scope
• what changed and why
• test evidence (commands + results)
• migration notes if behavior/config changed

4) What we currently welcome most

• 🐞 bug discovery, issue reports, and direct fixes
• 🧪 stronger test coverage for channels/providers/integration paths
• 🪟🍎 cross-platform hardening, including macOS compatibility improvements
• 📚 documentation clarity, onboarding improvements, and examples

5) Issue quality checklist

For bug reports, please attach:

• runtime command used and full error output
• minimal config (redacted secrets)
• environment details (OS, Python version, optional dependencies)

Thanks for helping improve CloseClaw.

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CloseClaw: Small runtime, strong guardrails, serious automation.