Which one you need
Use MCP when a person is asking for something conversationally: pull last week’s conversion numbers, publish a page, shift A/B traffic weights. Use the REST API when a system needs to do it repeatedly and reliably without anyone watching.MCP for AI assistants
Manage landing pages, variants, leads, and analytics in plain English from any MCP-compatible assistant.
REST API
Programmatic access to landers, variants, leads, integrations, folders, domains, and analytics.
Getting an API key
Both paths start here. Keys are scoped to your organization and passed in theX-API-Key header.
Generate a LanderLab API key
Create a key, find your existing keys, and keep them secure.
Connecting an AI assistant
Setup takes a few minutes and differs slightly per client. Pick yours:Claude
Claude.ai, Claude Desktop, and Claude Code.
ChatGPT
Add LanderLab as a connector and manage pages from a chat.
Coding assistants
Cursor, Windsurf, and Gemini CLI.
Manus
Add your key through the settings UI or a JSON config.
What you can do through MCP
Once connected, you can ask for things directly instead of clicking through the dashboard:- Read workspaces, landing pages, variants, leads, and analytics
- Publish pages and edit variants
- Adjust A/B test traffic weights
- Update leads and configure integrations
Tool permissions are set in your assistant, not in LanderLab. Review what you allow before granting write access, since mutation tools can publish and modify live pages.
What you can do through the API
The REST API covers the same surface with finer control. Common uses:- Create landing pages programmatically, including importing from a URL
- Publish and unpublish pages from your own deployment process
- Pull leads into an internal database or data warehouse
- Query unified analytics across workspaces, pages, and variants
- Manage A/B variants and weights automatically based on performance
API overview
How authentication works, what resources exist, and how the endpoints are organized.