67 lines
2.0 KiB
Markdown
67 lines
2.0 KiB
Markdown
<!-- DOCTOC SKIP -->
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- [Model Context Protocol (MCP)](#model-context-protocol-mcp)
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- [Integration Options](#integration-options)
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- [Supported Applications](#supported-applications)
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<h1 align="center">
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<picture>
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<source media="(prefers-color-scheme: dark)" srcset="images/SkyvernMCP.png"/>
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<img src="images/SkyvernMCP.png" alt="Skyvern MCP Logo" width="75%"/>
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</picture>
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</h1>
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# Model Context Protocol (MCP)
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Skyvern's MCP server implementation helps connect your AI Applications to the browser. This allows your AI applications to do things like: Fill out forms, download files, research information on the web, and more.
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You can connect your MCP-enabled applications to Skyvern in two ways:
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1. **Local Skyvern Server**
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- Use your favourite LLM to power Skyvern
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2. **Skyvern Cloud**
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- Create an account at [app.skyvern.com](https://app.skyvern.com)
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- Get the API key from the settings page which will be used for setup
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## Quickstart
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1. **Install Skyvern**
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```bash
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pip install skyvern
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```
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2. **Configure Skyvern** Run the setup wizard which will guide you through the configuration process. You can connect to either [Skyvern Cloud](https://app.skyvern.com) or a local version of Skyvern.
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```bash
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skyvern init
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```
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3. **(Optional) Launch the Skyvern Server. Only required in local mode**
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```bash
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skyvern run server
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```
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## Supported Applications
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`skyvern init` helps configure the following applications for you:
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- Cursor
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- Windsurf
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- Claude Desktop
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- Your custom MCP App?
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Use the following config if you want to set up Skyvern for any other MCP-enabled application
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```json
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{
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"mcpServers": {
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"Skyvern": {
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"env": {
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"SKYVERN_BASE_URL": "https://api.skyvern.com", # "http://localhost:8000" if running locally
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"SKYVERN_API_KEY": "YOUR_SKYVERN_API_KEY" # find the local SKYVERN_API_KEY in the .env file after running `skyvern init` or in your Skyvern Cloud console
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},
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"command": "PATH_TO_PYTHON",
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"args": [
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"-m",
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"skyvern",
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"run",
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"mcp"
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]
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}
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}
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}
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``` |