Evaluate AI models and MCP servers with Postman

With Postman, you can experiment, test, and evaluate AI models and Model Context Protocol (MCP) servers. Use Postman to add an AI model of your choice to your project, such as one from OpenAI, Anthropic, or Google. Or, add an MCP server from the community—or build your own.

Start by sending requests to AI models. You can compare models based on their responses, response times, and token counts. Then, send requests to MCP servers. You can compare servers based on their tools, resources, and prompts. You can also combine the two and see how an AI model uses an MCP server to enhance a response.

With Postman's MCP Generator, you can create your own MCP server with public APIs from the Postman API Network, and use Postman to improve your server's developer experience.

If you prefer a visual, low-code editor, you can use Postman Flows to experiment, test, and evaluate AI models and MCP servers. Or use Flows to build your own MCP server.

Send requests to AI models

You can create AI requests to interact with AI models. You can then prompt the model, review the response details, and manage your conversations with them. In addition, you can add an MCP server to your request to give the model added context.

To learn more, see Create AI requests and add them to your collections.

Send requests to MCP servers

You can use Postman as your MCP client and send requests to MCP servers. You can use these requests to experiment, test, and evaluate your MCP server, or one from the community.

To learn more, see Create MCP requests and add them to your collections.

Generate MCP servers

With Postman's MCP Generator, you can create an MCP server with public APIs from the Postman API Network. Then, you can use Postman to experiment, test, and evaluate your MCP server together with an AI model of your choice.

To learn more, see Create MCP servers with the Postman API Network.

Send requests to AI models with Postman Flows

With the Postman Flows, you can use a visual, low-code editor to build API-first AI agents on an infinite, drag-and-drop canvas.

To learn more, see Create AI request blocks and add them to your flows.

Create MCP servers with Postman Flows

You can also create MCP servers using Postman Flows.

To learn more, see MCP servers in Postman Flows.

Watch demos and see examples

See Postman's developer tools in action in the Postman AI Tool Builder public workspace. Then, explore the following guided demos and start building your next AI agent.

• Streamline LLM Integration with Postman's AI Protocol
• Evaluate LLM Performance in Postman
• Build Multi-Stage AI Agents: Vector Search + LLMs in Postman Flows
• Build Event-Driven AI Workflows in Postman
• Build Autonomous AI Agents for Incident Management in Postman Flows
• What Is MCP? The Matrix for AI Tools Explained in 60 Seconds