--- title: 'Quick Start' description: 'Follow these steps to get your Open Agent Platform up and running quickly.' --- **Prerequisites:** - Clone the [Open Agent Platform Repository](https://github.com/langchain-ai/open-agent-platform) - [LangSmith](https://smith.langchain.com/) Account (free tier is sufficient) - [Supabase](https://supabase.com/) Account - MCP Server (e.g. [Arcade](https://arcade-ai.com/)) - An LLM API Key (e.g. [OpenAI](https://platform.openai.com/), [Anthropic](https://console.anthropic.com/), [Google](https://aistudio.google.com/)) ## 1. Authentication Setup Open Agent Platform uses Supabase for authentication by default. Create a new project in [Supabase](https://supabase.com/). Set the following environment variables inside the `apps/web/` directory: ```bash NEXT_PUBLIC_SUPABASE_URL="" NEXT_PUBLIC_SUPABASE_ANON_KEY="" ``` Enable Google authentication in your Supabase project, or set `NEXT_PUBLIC_GOOGLE_AUTH_DISABLED=true` in your environment variables to disable showing Google as an authentication option in the UI. ## 2. Deploying Agents The next step in setting up Open Agent Platform is to deploy and configure your agents. We've released two pre-built agents specifically for Open Agent Platform: - [Tools Agent](https://github.com/langchain-ai/oap-langgraph-tools-agent) - [Supervisor Agent](https://github.com/langchain-ai/oap-agent-supervisor) For each agent repository: 1. Clone the repository 2. Follow the instructions in the README 3. Deploy the agents to LangGraph Platform After deployment, create a configuration object for each agent: ```json { "id": "The project ID of the deployment", "tenantId": "The tenant ID of your LangSmith account", "deploymentUrl": "The API URL to your deployment", "name": "A custom name for your deployment", "isDefault": "Whether this deployment is the default deployment (only one can be default)", "defaultGraphId": "The graph ID of the default graph (optional, only required if isDefault is true)" } ``` You can find your project & tenant IDs with a GET request to the `/info` endpoint on your LangGraph Platform deployment. Combine your agent configurations into a JSON array and set the `NEXT_PUBLIC_DEPLOYMENTS` environment variable inside the `apps/web/` directory: ```bash NEXT_PUBLIC_DEPLOYMENTS=[{"id":"bf63dc89-1de7-4a65-8336-af9ecda479d6","deploymentUrl":"http://localhost:2024","tenantId":"42d732b3-1324-4226-9fe9-513044dceb58","name":"Local deployment","isDefault":true,"defaultGraphId":"agent"}] ``` ## 3. RAG Server Setup Follow the instructions in the [LangConnect README](https://github.com/langchain-ai/langconnect) to set up and deploy a LangConnect RAG server. Set the RAG server URL inside the `apps/web/` directory: ```bash NEXT_PUBLIC_RAG_API_URL="http://localhost:8080" ``` ## 4. MCP Server Setup Open Agent Platform only supports connecting to MCP servers which support Streamable HTTP requests. Set your MCP server URL inside the `apps/web/` directory (ensure it does not end with `/mcp`. This will be auto-applied by OAP): ```bash NEXT_PUBLIC_MCP_SERVER_URL="" ``` For authenticated MCP servers: ```bash NEXT_PUBLIC_MCP_AUTH_REQUIRED=true ``` ## 5. Run Your Platform Start the application with your configured environment variables: ```bash # Navigate to the web app directory cd apps/web # Install dependencies yarn install # Start the development server yarn dev ``` Your Open Agent Platform should now be running at http://localhost:3000!