If you're searching for "how to connect Make to OpenClaw", the real question is usually not just whether the connection is possible. It's how to make Make usable inside an OpenClaw workflow with the right model, the right context, and the right level of control.
That's the practical framing.
OpenClaw gives you the orchestration layer: connectors, skills, tools, prompts, approvals, and the ability to run workflows where your team already works. Make provides the domain context. The integration becomes valuable when those two pieces are connected cleanly.
What “Connect Make to OpenClaw” Actually Means
In practice, connecting Make to OpenClaw usually involves four layers:
- Authentication so OpenClaw can securely access Make
- Tooling or proxy endpoints that expose the right Make actions and data
- Skills/instructions that tell OpenClaw how to reason over Make context
- Model selection so the assistant uses the right LLM for the job
That last piece matters more than most people expect.
Which Models Can You Use?
OpenClaw is model-flexible, so a Make integration does not need to be tied to a single provider. Depending on your setup, teams commonly want to use:
- OpenAI models like GPT-4o, GPT-4.1, and o3 for broad reasoning and tool use
- Anthropic models like Claude 3.5 Sonnet, Claude Sonnet 4/4.5, and Claude Opus for strong writing, analysis, and long-context work
- Google models like Gemini 1.5 Pro or newer Gemini models for multimodal and large-context workflows
- Other model backends if your OpenClaw environment exposes them
The practical point: you can connect Make to OpenClaw once, then run different workflows with different models depending on the job.
For example:
- Use Claude for nuanced summarisation or drafting
- Use OpenAI for structured extraction, tool-heavy workflows, or general-purpose copiloting
- Use Gemini when multimodal or very large context windows matter
A Good Integration Pattern for Make
A strong Make + OpenClaw setup usually looks like this:
- OpenClaw receives a request in chat or from an automation
- It calls the right Make endpoint or proxy
- The selected model reasons over the returned context
- OpenClaw returns an answer, draft, classification, or action
- High-risk actions stay behind approvals or structured guardrails
That is what makes the setup operational rather than just experimental.
Step-by-Step: Connect Make to OpenClaw
Step 1: Create a Webhook in a Make Scenario
In Make, add a Webhooks module as the trigger for a new scenario. Copy the webhook URL. In your OpenClaw skill file, document this URL and the expected payload structure. When Claude triggers the webhook, Make's scenario executes the subsequent modules.
Step 2: Use the Make API for Scenario Management
Make's Management API (https://eu1.make.com/api/v2/ or us1.make.com depending on your region) lets you list scenarios, activate/deactivate them, and view execution history. Authentication uses an API token from your Make profile settings. Add these endpoints to your proxy for monitoring queries.
Step 3: Build the Proxy and Skill File
Wrap the webhook trigger URLs and the Management API in your proxy. Write ~/.openclaw/skills/make.md with your scenario names and what they do, the webhook URLs for triggerable scenarios, and what execution data is available from the API.
Model-Specific Workflow Ideas
Make + OpenAI
Use this when you want a strong general-purpose setup for extraction, classification, action planning, and tool-driven workflows around Make.
Make + Claude
Use this when you want better writing quality, clearer summaries, stronger nuance, and reliable long-context reasoning over Make data.
Make + Gemini
Use this when the workflow benefits from large context windows, multimodal inputs, or Google-native ecosystem alignment.
Common Mistakes
Most teams do not fail because the model is bad. They fail because:
- the Make connection is too thin
- the model lacks the right live context
- prompts are vague
- no structured outputs are enforced
- permissions and approvals are skipped
- one model is forced to do every job, even when another would be a better fit
The best setup is usually one integration layer, multiple model options, and clear guardrails.
Challenges and Caveats
API Region Varies
Make has separate API servers for EU and US regions (eu1.make.com vs us1.make.com). Using the wrong region returns authentication errors. Check your Make workspace URL to determine which region you're on.
Webhook Execution Is Asynchronous
Like Zapier, Make scenarios triggered by webhook run asynchronously. OpenClaw can confirm the trigger but can't wait for scenario completion. For feedback on results, design your scenario to POST a callback to OpenClaw's endpoint (if you have one exposed).
Want Make Connected to OpenClaw Without Building the Whole Stack Yourself?
Cody connects natively to your tools without requiring Make as middleware. Get direct integrations without building scenario workflows.
Related OpenClaw Guides
Looking for a more workflow-first angle? See: Make AI Automation and Make AI Assistant.