A smaller, lighter-weight version of OpenClaw—natively multi-agent, compiles to Rust, and built on the Swarms framework and Swarms ecosystem. One API, unified messaging across Telegram, Discord, and WhatsApp with optional Claude-powered reasoning. Production-ready: gRPC gateway, prompts in code (claw_swarm.prompts), and 24/7 operation. Dockerfile included (Python 3.12).
ClawSwarm is a streamlined, multi-agent alternative to OpenClaw. It delivers natively multi-agent AI that responds to users on Telegram, Discord, and WhatsApp through a centralized Messaging Gateway. The gateway normalizes incoming messages; the ClawSwarm Agent (Swarms framework, configurable system prompt, Claude as a tool) processes each message and replies via a Replier back to the originating channel. Built on the Swarms ecosystem for reliability, security, and minimal operational overhead—with a path to compile to Rust for performance and deployment flexibility.
Key capabilities
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Lighter than OpenClaw — Smaller footprint and simpler stack; same multi-channel vision without the full OpenClaw surface area.
-
Natively multi-agent — Designed from the ground up for multi-agent orchestration on the Swarms framework and Swarms ecosystem.
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Unified ingestion — One gRPC API for all supported channels; add or remove platforms without changing agent logic.
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Swarms-native agent — Industry-standard orchestration, configurable model and system prompt, Claude available as a tool for deep reasoning and code.
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Compiles to Rust — Build path to Rust for performance and deployment flexibility.
-
Prompts in code — Agent and Claude-tool prompts are Python strings in
claw_swarm.prompts; override viacreate_agent(system_prompt=...)or edit the module. -
Production-ready — Optional TLS, environment-based configuration, long-running agent loop suitable for systemd, Docker, or managed runtimes.
Telegram Discord WhatsApp
\ | /
\ v /
+--------------+
| Gateway | unified ingest (gRPC)
+------+-------+
|
v
+--------------+
| Agent | Swarms + Claude tool
+------+-------+
|
v
+--------------+
| Replier | send back to each channel
+------+-------+
|
Telegram Discord WhatsApp
Flow: User messages arrive on any channel → Gateway normalizes and exposes via gRPC → Agent processes (optionally calling Claude) → Replier sends the response to the correct channel.
OpenClaw is a full-featured personal AI assistant (gateway, many channels, voice, canvas, nodes, skills). ClawSwarm is a smaller, lighter-weight take on that vision: natively multi-agent, built on the Swarms framework and Swarms ecosystem, with a path to compile to Rust. Use ClawSwarm when you want a lean, multi-agent messaging layer; use OpenClaw when you need the full product (companion apps, voice, canvas, etc.).
- Python 3.10+
- Dependencies listed in
requirements.txt(no version pins; use a venv and pin locally if needed) - Swarms framework and Swarms ecosystem; Claude Code (for the Claude tool)
- Platform credentials for the channels you enable: Telegram Bot Token, Discord Bot Token and Channel IDs, and/or WhatsApp Cloud API credentials
pip3 install -U claw-swarmSet these in your shell or in a .env file (e.g. --env-file .env with Docker). Omit a platform’s credentials to disable that channel.
| Variable | Purpose | Default |
|---|---|---|
| Gateway | ||
GATEWAY_HOST |
Bind address (gateway) or gateway host (agent) | [::] (server), localhost (agent) |
GATEWAY_PORT |
gRPC port | 50051 |
GATEWAY_TLS |
Enable TLS: 1, true, or yes |
— |
GATEWAY_TLS_CERT_FILE |
Path to TLS certificate file | — |
GATEWAY_TLS_KEY_FILE |
Path to TLS private key file | — |
| Channels | ||
TELEGRAM_BOT_TOKEN |
Telegram Bot API token | — |
DISCORD_BOT_TOKEN |
Discord bot token | — |
DISCORD_CHANNEL_IDS |
Comma-separated Discord channel IDs | — |
WHATSAPP_ACCESS_TOKEN |
WhatsApp Cloud API access token | — |
WHATSAPP_PHONE_NUMBER_ID |
WhatsApp Cloud API phone number ID | — |
WHATSAPP_QUEUE_PATH |
Optional WhatsApp queue path | — |
| Agent | ||
AGENT_MODEL |
Swarms agent model | gpt-4o-mini |
OPENAI_API_KEY |
OpenAI API key (for agent model) | — |
ANTHROPIC_API_KEY |
Anthropic API key (for Claude tool) | — |
| Memory | ||
AGENT_MEMORY_FILE |
Agent memory markdown filename (project root) | agent_memory.md |
AGENT_MEMORY_MAX_CHARS |
Max characters of memory to load into context | 100000 |
1. Set environment variables for the channels you use (see Environment variables above for the full table).
2. Run the full stack (gateway + agent in one process group):
./run.shOr run each component in a separate terminal:
python -m claw_swarm.gateway # terminal 1
python -m claw_swarm.main # terminal 2Use Ctrl+C to stop; run.sh stops both processes. For 24/7 operation, run under systemd or Docker.
Docker:
docker build -t clawswarm .
docker run --env-file .env clawswarmPass channel tokens and AGENT_MODEL via --env-file .env or -e.
See the Environment variables table above for the full list. The gateway and agent both read GATEWAY_HOST and GATEWAY_PORT (gateway binds on that address; agent connects to it). Replies use the same platform tokens as the gateway.
gRPC service:
- PollMessages — Fetch messages since a timestamp (used by the agent runner).
- StreamMessages — Server-streaming delivery of new messages.
- Health — Liveness and version.
Messages are normalized to a single schema: UnifiedMessage (id, platform, channel_id, thread_id, sender, text, attachments, timestamp). Use TLS and restrict network access in production.
- Secrets — Do not commit tokens or API keys. Use environment variables or a secrets manager.
- Transport — Enable gateway TLS in production (
GATEWAY_TLS=1and valid certificate and key). - Access control — Restrict which clients can reach the gRPC port (firewall, VPC, or mTLS as required).
See the repository LICENSE for terms of use.