Postmancer

Postmancer is an MCP (Model Context Protocol) server that turns any AI assistant into a full‑featured API testing and management tool.
Instead of relying on external IDEs or command line utilities, developers can ask an assistant to send a GET request, save a POST payload, or list all endpoints in a collection and receive the results instantly. This tight integration eliminates context switching, allowing teams to prototype, debug, and document APIs directly within the conversational interface they already use for code reviews or design discussions.

The server exposes a rich set of tools that mirror the core functionality of popular desktop clients like Postman or Insomnia. Users can create and organize collections, define environment variables with automatic substitution, and choose from a variety of authentication schemes—including Basic, Bearer tokens, API keys, and OAuth2. Each request’s history is stored, enabling quick re‑execution or comparison of responses without leaving the chat. The tool is generic enough to target any RESTful endpoint, while helper tools such as and provide convenient navigation through a developer’s API catalog.

Key capabilities in plain language:

• Send any HTTP request by specifying method, URL, headers, and body.
• Organize requests into collections, making it easy to group related endpoints (e.g., user service, payment gateway).
• Manage environment variables that can be injected into request templates, supporting dynamic values like tokens or base URLs.
• Support multiple authentication types, so secure APIs can be accessed without manual header crafting.
• Persist request history for quick debugging and audit trails.

These features translate into several real‑world use cases. During a sprint, a developer can ask the assistant to “run the latest login endpoint with the current auth token” and immediately see the JSON response, all without opening a separate tool. QA engineers can validate edge cases by instructing the assistant to “execute the POST /orders endpoint with an empty payload” and review error handling. Documentation writers can generate up‑to‑date API examples on the fly, pulling live responses to include in spec files.

Integration with AI workflows is seamless: the MCP server runs as a background process that the assistant can invoke via its tool set. Developers can configure it through simple JSON in their desktop client or launch a Docker container that mounts persistent collections. Once connected, the assistant can orchestrate complex sequences—such as authenticating, fetching a token, setting it in an environment variable, and then calling multiple endpoints—using natural language commands. This removes the friction of manual scripting and lets teams iterate faster.

What sets Postmancer apart is its native MCP design. Unlike generic HTTP libraries, it exposes a curated API surface that aligns with conversational intent, ensuring that the assistant can interpret and execute tasks reliably. The built‑in encryption support for credentials and secrets further guarantees that sensitive data remains protected even when stored in collections. For developers looking to embed robust API testing directly into their AI‑powered workflows, Postmancer offers a lightweight, secure, and highly expressive solution.