OmniGems MCP + OpenClaw: Run AI-Influencer Ops from WhatsApp, Telegram, and Slack

OpenClaw is the open-source personal-AI daemon that lives on your machine and talks to you over the chat apps you already use — WhatsApp, Telegram, Slack, Discord, Signal, Google Chat, and ~20 others. It supports Model Context Protocol natively, which means any MCP server (including OmniGems' 16-tool viral-content surface) becomes a chat command in any of those channels.

This guide is the working setup. It covers what OpenClaw is, how to wire OmniGems MCP into it, the auth gotcha you need to know up front, and five workflow patterns that genuinely compound.

Why this combination matters

OpenClaw and OmniGems solve adjacent halves of the same problem:

• OpenClaw gives you a persistent assistant that lives in chat. You can ping it from your phone via Telegram, from your laptop via Slack, from Signal at midnight. It has memory across sessions and supports scheduled "heartbeats" for periodic tasks.
• OmniGems gives you the AI-influencer operations surface — persona lifecycle, content generation, multi-platform posting, BURNS-aligned creator economics — exposed via MCP.

Wired together, you get AI-creator ops from any chat channel: "create a new beauty persona for Q3" via Telegram, "what's my BURNS balance?" via Slack, "queue 5 listing videos for @miami_condos" via WhatsApp. The persona pipeline runs in the background; the chat is just the steering wheel.

For the OmniGems-only setup (Claude Code, Cursor, ChatGPT-style clients), see OmniGems MCP Guide.

What OpenClaw actually is, in 2026

Open-source personal AI assistant (MIT-licensed; github.com/openclaw/openclaw). Distinct product class from Claude Code:

• OpenClaw: daemon-resident multi-channel assistant with persistent memory and scheduled heartbeats. Designed for life automation — inbox, calendar, posting, ops.
• Claude Code: terminal-resident pair-programmer. Designed for development work in editor.

Both support MCP. They have different audiences and different strengths. OpenClaw runs on macOS, Linux, and Windows (via WSL2), with Node 24 recommended (22.16+ minimum). Install:

npm install -g openclaw@latest && openclaw onboard --install-daemon

OpenClaw's MCP support is native — openclaw mcp is a first-class CLI subcommand. Transports supported: stdio, sse, streamable-http. The CLI accepts type: "http" as an alias and normalizes to the canonical transport field via openclaw doctor --fix.

The auth gotcha you need to know first

OpenClaw does not run the MCP OAuth Authorization-Code+PKCE dance for remote MCP servers. Auth for MCP endpoints is static-headers only — Bearer tokens, API keys, custom headers. OAuth flows in OpenClaw are reserved for model providers (Anthropic, OpenAI/Codex), not for MCP servers themselves.

Practically, this means wiring OmniGems MCP into OpenClaw requires a manual token paste:

1. Sign in to omnigems.ai in a browser
2. Generate a personal access token from your account settings (https://app.omnigems.ai/settings/tokens)
3. Paste it into OpenClaw's MCP config as a Bearer header
4. Rotate it periodically (recommended: every 30–90 days)

This is fine for a single operator running their own persona pipeline. For team / studio scenarios where multiple operators share access, the OmniGems MCP from Claude Code (which runs the full PKCE flow per-client) is the better fit. See OmniGems MCP Guide for that setup.

Wiring OmniGems MCP into OpenClaw

The exact command:

openclaw mcp set omnigems '{
  "url": "https://app.omnigems.ai/api/mcp",
  "transport": "streamable-http",
  "headers": { "Authorization": "Bearer ${OMNIGEMS_TOKEN}" },
  "connectionTimeoutMs": 10000
}'

Equivalent config block in ~/.openclaw/config under mcp.servers:

"omnigems": {
  "url": "https://app.omnigems.ai/api/mcp",
  "transport": "streamable-http",
  "headers": { "Authorization": "Bearer ${OMNIGEMS_TOKEN}" }
}

After setting, verify:

openclaw mcp show omnigems
openclaw doctor

doctor will normalize type → transport and confirm the entry parses cleanly. If you see a redaction warning on the Authorization header, that's expected — OpenClaw redacts sensitive header values from logs by design.

Token security

The token lives in plaintext in the OpenClaw config file. Two recommendations:

• Use ${OMNIGEMS_TOKEN} interpolation rather than pasting the literal token in the JSON — that way the token sits in your shell environment (or a .env file with restrictive perms) instead of the OpenClaw config.
• Rotate on suspected leak — OmniGems supports token revocation via the same settings page. After revocation, generate a new one and update the env var.

Avoid putting the token in the URL userinfo (https://user:token@…) — it works and is redacted in logs, but it breaks some HTTP proxies that strip userinfo.

Verifying the connection

After openclaw mcp set, ping the connection from any of your registered chat channels:

"List my OmniGems agents."

OpenClaw routes this to the viral_list_agents tool, returns the structured response, and renders it in the channel. If you see your agents, you're wired in.

If the call fails, run openclaw doctor --fix and check:

• transport: "streamable-http" (not "http" or "sse")
• Authorization header reaches the server (check openclaw mcp show omnigems for redaction-confirmed value)
• Your token has the scopes you need — mcp:read for queries, mcp:write for content creation
• connectionTimeoutMs is at least 10000 — large persona/video generations can take that long

Five workflows that compound

These are the patterns that actually justify wiring OmniGems into OpenClaw rather than just using the OmniGems web UI.

1. Telegram morning standup

Telegram message at 8am: "Daily ops report for all my agents"

OpenClaw heartbeat fires the prompt, runs viral_activity_daily + viral_active_processes + viral_list_user_tasks, and renders the report back into Telegram. You read it with your coffee. No tab-flipping, no dashboard.

2. Slack persona launch

Slack message: "Create a new persona — coral-gables real estate, mid-30s licensed agent, podcast voice, English + Spanish."

OpenClaw routes to viral_parse_influencer_description to convert free-form into structured config, then viral_estimate_cost for the BURNS quote, then viral_create_influencer after you confirm in-channel. Three tool calls; one chat thread.

3. WhatsApp content batch

WhatsApp message: "Queue 5 listing videos for @miami_condos with hooks based on this week's top post."

OpenClaw composes viral_get_post (top performer this week) → viral_estimate_cost → viral_start_content. The hooks come from the AI client; the orchestration comes from the MCP. Result: 5 videos queued from a 30-second message exchange.

4. Discord cost guardrails

Discord scheduled heartbeat (hourly): check balance + active processes; if balance < 1000 BURNS, cancel any in-progress long-form generations and DM owner.

OpenClaw's persistent heartbeats are the right substrate for this. Wire it as a recurring task with viral_get_balance + viral_active_processes + (conditional) viral_cancel_process + DM. The cost guardrail runs even when you're asleep.

5. Signal hand-off to a human reviewer

Signal message: "Review pending tasks for @miami_condos."

OpenClaw fetches viral_list_user_tasks, picks the oldest, calls viral_get_process_status to load form fields, drafts a response in your voice, and waits for your approval in-channel. After "yes", it commits via viral_complete_user_task. End-to-end human-in-the-loop in a single Signal thread.

For more on these multi-platform patterns, see How AI Agents Post on Social Media. For the broader BURNS economics that back viral_get_balance and viral_estimate_cost, see BURNS Token Glossary.

Where this combination genuinely shines

Three patterns where OpenClaw + OmniGems delivers more than either tool alone:

Persona ops without leaving chat

If you spend 4+ hours a day in WhatsApp/Telegram/Slack already (most operators do), the chat-channel surface eliminates the dashboard tab. Operations that previously required logging into the OmniGems UI now happen in the same threads where you discuss strategy with your team. Lower context-switching cost = more decisions per hour.

Multi-platform from one prompt

OpenClaw's channel router + OmniGems' publishing tools = "post this clip to TikTok, IG Reels, and X" as a single instruction. The same posting agents documented in How AI Agents Post on Social Media, now triggerable from any channel you already live in.

Cost-aware scheduled generation

OpenClaw's heartbeats can run nightly cost-budgeted generations: pick the top-performing posts of the day, queue 5 follow-up clips per top performer up to your nightly BURNS budget, render overnight, post in the morning. You wake up to a ranked-by-ROI batch of content drafts instead of either an empty queue or a surprise bill.

When this combination is the wrong fit

Be honest about where it doesn't help:

• Single-operator on a desktop already using Claude Code. The OAuth-handled flow in Claude Code is more secure than OpenClaw's manual-token model. Stick with Claude Code unless you specifically want chat-channel triggering.
• Team / studio with multiple operators sharing the persona pipeline. Each operator should authenticate separately via Claude Code's PKCE flow, not share an OpenClaw config with a static token.
• Compliance-strict niches (crypto, finance) where the auth audit trail matters. OmniGems' OAuth 2.1 + PKCE flow via Claude Code produces cleaner audit logs than the manual-token model OpenClaw currently supports.

For those scenarios, see OmniGems MCP Guide instead.

Roadmap awareness

OpenClaw's MCP-OAuth support is on the project's tracker. When it lands (no committed date as of this writing), the manual-token flow above can migrate to the same PKCE flow used by Claude Code, removing the rotation overhead. Until then, the static-token approach is the supported path.

OmniGems tracks the MCP spec; protocol bumps land first in canary then graduate to production within ~2 weeks. New tools land monthly. If you have a specific tool you want exposed for the OpenClaw workflow, request it via the open-source MCP-server spec.

How to get started

1. Install OpenClaw: npm install -g openclaw@latest && openclaw onboard --install-daemon
2. Generate an OmniGems personal access token at https://app.omnigems.ai/settings/tokens
3. Export it: export OMNIGEMS_TOKEN=ogm_…
4. Wire it: run the openclaw mcp set omnigems … command above
5. Verify: openclaw mcp show omnigems and openclaw doctor
6. Test from your favorite channel: ping OpenClaw with "list my OmniGems agents"
7. Layer in the workflows from this guide

The chat channels you already live in become the operations surface for your AI-creator pipeline. That's the structural win.

What to Read Next

• OmniGems MCP Guide — full setup and 16-tool reference (Claude Code path)
• OmniGems MCP vs Higgsfield — asset-generation comparison
• OmniGems MCP vs Arcade — productivity-SaaS comparison
• How AI Agents Post on Social Media — multi-platform posting layer
• BURNS Token Glossary — the token economy backing viral_get_balance