Question 1

What is the Testmcp Python API library?

Accepted Answer

The Testmcp Python API library provides a convenient way to access the Testmcp REST API from Python applications. It includes type definitions for request params and response fields and offers both synchronous and asynchronous clients.

Question 2

What is MCP (Model Context Protocol)?

Accepted Answer

MCP is an open protocol that standardizes how applications provide context to Large Language Models (LLMs), enabling AI models to access and interact with external data sources and tools.

Question 3

What are the key features of the Testmcp Python API library?

Accepted Answer

Key features include a Pythonic interface, type safety, asynchronous support, comprehensive error handling, retries and timeouts, logging, access to raw response data, streaming support, and a customizable HTTP client.

Question 4

How do I install the Testmcp Python API library?

Accepted Answer

You can install it from PyPI using pip: `pip install --pre testmcpapi`

Question 5

How do I use the library in synchronous mode?

Accepted Answer

Import `Testmcp` and create a client instance, providing your API key. Then, use the client to call API methods, such as `client.product.list()`.

Question 6

How do I use the library in asynchronous mode?

Accepted Answer

Import `AsyncTestmcp` instead of `Testmcp` and use `await` with each API call. You'll need to define an asynchronous function and use `asyncio.run()` to execute it.

Question 7

How do I handle errors with the library?

Accepted Answer

The library raises exceptions for various error conditions, such as `APIConnectionError`, `RateLimitError`, and `APIStatusError`. You can catch these exceptions and handle them accordingly.

Question 8

How do I configure retries and timeouts?

Accepted Answer

You can configure retries using the `max_retries` option when creating the client. Timeouts can be configured using the `timeout` option, which accepts a float or an `httpx.Timeout` object.

Question 9

How do I access raw response data, such as headers?

Accepted Answer

Use the `.with_raw_response` prefix to any HTTP method call, e.g., `client.product.with_raw_response.list()`. This returns an `APIResponse` object with access to the raw response.

Question 10

How do I stream responses?

Accepted Answer

Use `.with_streaming_response` and a context manager to stream the response body. You can then use methods like `.iter_lines()` to process the data.

Question 11

Can I customize the HTTP client?

Accepted Answer

Yes, you can override the `httpx` client to customize it for your use case, including support for proxies and custom transports.

Question 12

What is UBOS and how does it relate to Testmcp?

Accepted Answer

UBOS is a full-stack AI Agent Development Platform that complements the Testmcp library. UBOS provides tools for agent orchestration, data integration, custom agent development, and multi-agent systems, enhancing the development process.

Question 13

Where can I find more documentation and examples?

Accepted Answer

Refer to the [praxis-cloud.com](https://praxis-cloud.com/about-us) for REST API documentation and [api.md](api.md) for the full API of the library.

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