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Build advanced AI agents with OpenAI. Connect 600+ integrations, automate workflows, and deploy with ease using Metorial.

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Configuring Server Deployments

Server deployments in Metorial define which integrations your AI agent can access. This guide explains how to set them up and use them effectively.

What are Server Deployments?

Server deployments are collections of integrations that you configure in your Metorial dashboard. Each deployment has a unique ID and contains specific tools and services your agent can use.

Finding Your Server Deployment ID

  1. Log in to your Metorial dashboard
  2. Navigate to the "Deployments" or "Servers" section
  3. Find or create a deployment
  4. Copy the deployment ID

Using a Single Deployment

await metorial.withProviderSession(
  metorialOpenAI.chatCompletions,
  { 
    serverDeployments: ['deployment-id-here']
  },
  async session => {
    // Your code here
  }
);

Using Multiple Deployments

You can combine tools from multiple deployments:

await metorial.withProviderSession(
  metorialOpenAI.chatCompletions,
  { 
    serverDeployments: [
      'github-deployment-id',
      'calendar-deployment-id',
      'crm-deployment-id'
    ]
  },
  async session => {
    // Agent now has access to tools from all three deployments
  }
);

Best Practices

Organize by Function

Create separate deployments for different purposes:

  • A "productivity" deployment with calendar and email tools
  • A "development" deployment with GitHub and Jira
  • A "customer-data" deployment with CRM and support tools

Use Environment Variables

Store deployment IDs in environment variables:

// .env
METORIAL_GITHUB_DEPLOYMENT=deployment-id-1
METORIAL_CALENDAR_DEPLOYMENT=deployment-id-2

// In your code
const deployments = [
  process.env.METORIAL_GITHUB_DEPLOYMENT,
  process.env.METORIAL_CALENDAR_DEPLOYMENT
].filter(Boolean);

await metorial.withProviderSession(
  metorialOpenAI.chatCompletions,
  { serverDeployments: deployments },
  async session => {
    // Your code
  }
);

Different Deployments for Different Environments

Use different deployments for development and production to control which integrations are available in each environment.

Troubleshooting

"No tools available" error: Check that your deployment ID is correct and that you've configured integrations in that deployment.

"Deployment not found" error: Verify the deployment ID exists in your Metorial dashboard and that your API key has access to it.

OpenAI on Metorial

Supercharge your OpenAI GPT applications with Metorial's extensive integration library featuring over 600 tools and services. Our MCP-powered platform makes it simple to connect GPT-4, GPT-4o, and other OpenAI models to the APIs your applications need. With Metorial's Python and TypeScript SDKs, adding integrations to your OpenAI-based agents and applications takes just a couple of lines of code—no more spending weeks building custom connectors. Whether you're creating chatbots, assistants, automation workflows, or AI-powered features with OpenAI's industry-leading language models, Metorial handles all the integration complexity. Connect to productivity tools like Google Workspace and Microsoft 365, CRMs like Salesforce and HubSpot, development tools like GitHub and Jira, and hundreds of other popular services instantly. Our open-source approach gives you full transparency and control while eliminating the burden of maintaining integration code, handling authentication, and managing API changes. Focus your team on building unique AI experiences and delivering value to users—let Metorial manage the integration infrastructure that powers your OpenAI applications.

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About Metorial

Metorial provides developers with instant access to 600+ MCP servers for building AI agents that can interact with real-world tools and services. Built on MCP, Metorial simplifies agent tool integration by offering pre-configured connections to popular platforms like Google Drive, Slack, GitHub, Notion, and hundreds of other APIs. Our platform supports all major AI agent frameworks—including LangChain, AutoGen, CrewAI, and LangGraph—enabling developers to add tool calling capabilities to their agents in just a few lines of code. By eliminating the need for custom integration code, Metorial helps AI developers move from prototype to production faster while maintaining security and reliability. Whether you're building autonomous research agents, customer service bots, or workflow automation tools, Metorial's MCP server library provides the integrations you need to connect your agents to the real world.

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