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@@ -136,90 +136,6 @@ Please see the Node.js [compatibility guidance on Webflow's developer docs.](htt
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## Local Installation
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You can also configure the MCP server to run locally. This requires:
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- Creating and registering your own MCP Bridge App in a Webflow workspace with Admin permissions
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- Configuring your AI client to start the local MCP server with a Webflow API token
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### 1. Create and publish the MCP bridge app
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Before connecting the local MCP server to your AI client, create and publish the Webflow MCP Bridge App in your workspace.
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1. Register a Webflow App in your Workspace. Follow the [Register an App](https://developers.webflow.com/data/v2.0.0/docs/register-an-app) guidance for more details.
- Set your Client ID and Client Secret in an `.env` file for the App you registered.
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- See the app repo’s README for exact variables and build steps.
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4. Build and publish the Designer Extension to your workspace:
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- Build per the repo instructions.
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- Publish the App to your workspace via the Webflow Dashboard → Workspace settings → Apps & Integrations → Develop→ your App → “Publish Extension Version” and upload your `bundle.zip` file.
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Once published to your workspace, open your MCP Bridge App in a site on your workspace from the Designer’s Apps panel.
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### 2. Configure your AI client
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#### Cursor
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Add to `.cursor/mcp.json`:
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```json
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{
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"mcpServers": {
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"webflow": {
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"command": "npx",
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"args": ["-y", "webflow-mcp-server@latest"],
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"env": {
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"WEBFLOW_TOKEN": "<YOUR_WEBFLOW_TOKEN>"
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}
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}
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}
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}
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```
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#### Claude desktop
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Add to `claude_desktop_config.json`:
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```json
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{
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"mcpServers": {
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"webflow": {
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"command": "npx",
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"args": ["-y", "webflow-mcp-server@latest"],
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"env": {
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"WEBFLOW_TOKEN": "<YOUR_WEBFLOW_TOKEN>"
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}
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}
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}
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}
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```
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### 3. Use the MCP server with the Webflow Designer
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- Open your site in the Webflow Designer.
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- Open the Apps panel (press `E`) and launch your published “Webflow MCP Bridge App”.
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- Wait for the app to connect to the MCP server, then use tools from your AI client.
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- If the Bridge App prompts for a local connection URL, call the `get_designer_app_connection_info` tool from your AI client and paste the returned `http://localhost:<port>` URL.
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