Postman Tool Generation MCP Server
LocalAbout Postman Tool Generation MCP Server
An MCP server for developers who want to turn Postman requests into tools for AI agents. It generates type-safe JavaScript or TypeScript for several agent frameworks, with error handling and response validation.
Key features
- 01Generate code from Postman collections
- 02Support JavaScript and TypeScript
- 03Support multiple agent frameworks
- 04Generate type-safe code
- 05Include error handling and response validation
Use cases
- 01Convert Postman API requests into agent tools
- 02Generate API integration code for different agent frameworks
MCP support
MCP clients can call `generate_ai_tool` with a collection, request, programming language, and agent framework to generate tool code.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEPostman Tool Generation MCP Server
An MCP server that generates AI agent tools from Postman collections and requests. This server integrates with the Postman API to convert API endpoints into type-safe code that can be used with various AI frameworks.
Model Context Protocol (MCP) is a new, standardized protocol for managing context between large language models (LLMs) and external systems. In this repository, we provide an installer as well as an MCP Server for Postman Tool Generation API.
This lets you use Claude Desktop, or any MCP Client like Cline, to use natural language to accomplish things on your Postman account, e.g.:
Create an AI tool for: collectionID: 12345-abcde requestID: 67890-fghij typescript openai
Features
- Generate TypeScript/JavaScript code from Postman collections
- Support for multiple AI frameworks (OpenAI, Mistral, Gemini, Anthropic, LangChain, AutoGen)
- Type-safe code generation
- Error handling and response validation
Demo
Setup
- Install dependencies:
npm install
- Build the server:
npm run build
- Configure the MCP settings by adding the following to your Claude settings file (
cline_mcp_settings.json):
{
"mcpServers": {
"postman-ai-tools": {
"command": "node",
"args": [
"/path/to/postman-tool-generation-server/build/index.js"
],
"env": {
"POSTMAN_API_KEY": "your-postman-api-key"
},
"disabled": false,
"autoApprove": []
}
}
}
Usage
The server provides a single tool called generate_ai_tool with the following parameters:
{
collectionId: string; // The Public API Network collection ID
requestId: string; // The public request ID
language: "javascript" | "typescript"; // Programming language to use
agentFramework: "openai" | "mistral" | "gemini" | "anthropic" | "langchain" | "autogen"; // AI framework
}
Example
// Using the tool through MCP
const result = await use_mcp_tool({
server_name: "postman-ai-tools",
tool_name: "generate_ai_tool",
arguments: {
collectionId: "your-collection-id",
requestId: "your-request-id",
language: "typescript",
agentFramework: "openai"
}
});
Generated Code
The tool generates type-safe code that includes:
- Type definitions for request/response
- Error handling
- API integration
- OpenAI function definitions
- Documentation and examples
Development
- Install dependencies:
npm install
-
Make changes to
src/index.ts -
Build the server:
npm run build
- Restart the Claude app to load the updated server
Environment Variables
POSTMAN_API_KEY: Your Postman API key (required)
Error Handling
The server includes comprehensive error handling for:
- Invalid parameters
- API failures
- JSON parsing errors
- Network issues
Error responses include detailed messages to help diagnose issues.
Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
License
MIT License
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.