MCP Server1

Provides a Postman-based API test automation server with asset uploads, test execution, and collection management for multiple AI models.

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GitHub Stars

python

Language

7 months ago

First Indexed

3 months ago

Catalog Refreshed

Documentation & install

Readme and setup notes from the catalogue, plus a client-ready config you can copy for your MCP host.

Installation

Add the following to your MCP client configuration file.

Configuration

View docs

You can run a versatile MCP server that manages and tests Postman-based API collections in a local, secure environment. It stores uploaded Postman Collection, Environment, and Data json files, runs API test cases, and tracks results across multiple AI model backends. This setup lets you validate API flows quickly and keep test data organized in a lightweight SQLite database.

How to use

You will connect your MCP client to a local server that exposes an HTTPS API on port 8610. Start the server and then upload Postman Collection, Environment, and Data json files to create test assets. Run API test cases, review results, and manage test collections from the MCP client. The server supports multiple AI models and lets you view test runs and outcomes for each collection.

Available tools

upload_assets

Upload Postman Collection, Environment, and Data JSON files to be stored in the local SQLite database.

execute_tests

Run API test cases defined in uploaded collections and track results.

manage_collections

Create, update, or delete test collections and link them to test runs.

model_support

Interact with multiple AI model backends (e.g., Claude, OpenAI, or user-defined models) for test contexts.