# Testing Servers and Agents — Agent Frameworks and MCP Basics

Source: https://www.geekswithgeeks.com/en/agent-frameworks-mcp/ops-testing

> Unit-test tool functions and add a small end-to-end eval for the agent.

## Two layers of tests

Because MCP tools are plain functions, **unit-test them directly** like any code: normal input, bad input, edge cases. Then add a small **end-to-end eval**: a handful of realistic user requests, run through the real agent, with checks such as "called `search_issues` with a sensible keyword". Re-run it whenever you change a tool description, because that changes model behaviour.

## A pytest unit test

Tests call the function directly, with no model or protocol involved, so they are fast and deterministic.

```python
import pytest
from server import search_issues

def test_limit_must_be_in_range():
    with pytest.raises(ValueError):
        search_issues("crash", limit=0)

def test_returns_at_most_limit(fake_tracker):
    assert len(search_issues("crash", limit=3)) <= 3
```

**Quiz:** Why re-run evals after editing a tool description?

- [x] Descriptions affect how the model chooses and uses the tool
- [ ] Python requires it
- [ ] Descriptions are compiled
- [ ] It resets the server

*Answer:* Descriptions affect how the model chooses and uses the tool. The description is part of the prompt the model sees, so changing it can change behaviour.