| name | postman-mcp-connector |
| description | MCP connector for Postman API platform – enables AI-powered API testing, collection management, and documentation generation through Claude |
| license | Proprietary/API |
| tags | ["dev","api","mcp","postman","testing"] |
| difficulty | intermediate |
| time_to_master | 4-8 weeks |
| version | 1.0.0 |
Postman MCP Connector
Overview
This skill enables Claude to interact with Postman through the Model Context Protocol (MCP). It provides a bridge between Claude's AI capabilities and Postman's REST API, allowing natural language control of Postman operations, intelligent automation, and AI-powered assistance for Postman workflows.
When to Use This Skill
- Collection and request generation from API specs
- Test script creation and automation
- Environment and variable management
- API documentation generation
- Monitor and mock server configuration
Architecture
┌─────────────┐ ┌─────────────────┐ ┌──────────────────┐
│ Claude │────▶│ MCP Server │────▶│ Postman │
│ (Client) │◀────│ (TypeScript) │◀────│ (REST API )│
└─────────────┘ └─────────────────┘ └──────────────────┘
Core Concepts
MCP Server Setup
The connector implements an MCP server that exposes Postman operations as tools Claude can invoke. The server translates natural language intentions into REST API calls.
Key Endpoints/Interfaces
/collections, /environments, /mocks, /monitors, /workspaces
Implementation
import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js";
import { z } from "zod";
const server = new McpServer({
name: "postman-mcp-connector",
version: "1.0.0",
});
server.tool(
"list_resources",
"List and query Postman resources with optional filters",
{
query: z.string().optional().describe("Search query or filter"),
limit: z.number().optional().describe("Max results to return"),
},
async ({ query, limit }) => {
const response = await fetch(`${BASE_URL}/collections`, {
headers: { "Authorization": `Bearer ${API_KEY}` },
});
const data = await response.json();
return {
: [{ : , : .(data, , ) }],
};
}
);
server.(
,
,
{
: z.().(),
: z.({}).().().(),
},
({ name, config }) => {
response = (, {
: ,
: {
: ,
: ,
},
: .({ name, ...config }),
});
data = response.();
{
: [{ : , : }],
};
}
);
server.(
,
,
{
: z.().(),
: z.().().(),
},
({ , timeframe }) => {
response = (, {
: { : },
});
data = response.();
{
: [{ : , : .(data, , ) }],
};
}
);
transport = ();
server.(transport);
Claude Desktop Configuration
{
"mcpServers": {
"postman-mcp-connector": {
"command": "node",
"args": ["path/to/postman-mcp-connector/index.js"],
"env": {
"POSTMAN_API_KEY": "your-api-key",
"POSTMAN_BASE_URL": "https://your-instance-url"
}
}
}
}
Best Practices
- Authentication: Store API keys securely using environment variables; never hardcode credentials
- Rate Limiting: Implement request throttling to respect Postman API rate limits
- Error Handling: Provide clear, actionable error messages for common failure scenarios
- Pagination: Handle paginated responses for large datasets efficiently
- Caching: Cache frequently accessed read-only data to reduce API calls
- Security: Validate all inputs before passing to the Postman API; sanitize outputs
- Logging: Log all API interactions for debugging and audit purposes
Example Prompts
"Generate a Postman collection from this OpenAPI spec with test scripts for all endpoints"
Security Considerations
- All API credentials must be stored as environment variables
- Implement input validation and sanitization for all tool parameters
- Use HTTPS for all API communications
- Follow the principle of least privilege for API token permissions
- Audit log all write operations for compliance tracking
Resources
Changelog
| Version | Date | Changes |
|---|
| 1.0.0 | 2026-04-01 | Initial MCP connector skill |
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