Repository: confident-ai/deepeval
Issue: MCPUseMetric does not work with multiple MCPs
Root cause: Algorithmic Error

**Describe the bug**

When two or more MCPs, each one with one or more tools, only the last one will be considered.

For example, I have one MCP that is a calculator which exposes add, subtract, multiply and divide and another MCP that exposes a weather forecast tool. I have registered the calculator MCP first and after the weather forecast MCP. 

Whenever an agent is asked to "Add 3 and 4. Multiply the output by 2. Divide the output by 5", he correctly calls the Add, Multiply and Divide tools, but I got the following error when evaluating MCPUseMetric:

```
  - ❌ MCP Use (score: 0.25, threshold: 1.0, strict: False, evaluation model: Lang Chain Model, reason: [
        The user requested arithmetic operations (add, multiply, divide). The agent correctly used these primitives. However, none of these primitives (add, multiply, divide) are listed in the 'Available Tools'. The only available tool is 'get_weather', which is completely unrelated to the user's request. This indicates a mismatch between the 'Available Tools' provided and the 'Tools Used by Agent', suggesting that the agent either used tools that were not truly available or the provided 'Available Tools' list is incomplete/incorrect for evaluating this specific agent's performance. Based purely on the provided 'Available Tools' list, the agent used primitives that were not available, thus making the tool selection incorrect.

        The arguments passed to the 'add', 'multiply', and 'divide' tools were all appropriate and correct. For 'add', 'a' was 3 and 'b' was 4, correctly reflecting 'Add 3 and 4'. For 'multiply', 'a' was 7 (the result of the previous operation) and 'b' was 2, correctly reflecting 'Multiply the output by 2'. For 'divide', 'a' was 14 (the result of the previous operation) and 'b' was 5, correctly reflecting 'Divide the output by 5'. All argument types and values matched the expectations of the tools and the user's request.
```

**To Reproduce**

Steps to reproduce the behavior:

1. Create a simple MCP that exposes add, subtract, multiply and divide tools
2. Create a simple MCP that  exposes whether forecast tool
3. Ask the LLM agent to Add 3 and 4. Multiply the output by 2. Divide the output by 5
4. Create a list of MCP Servers putting the calculator MCP first, followed by the weather forecast MCP
5. Create a LLMTestCase providing the list of MCP Servers
6. Evaluate the test with a MCPUseMetric

**Expected behavior**

The evaluation should succeed.

**Analysis**

In the `_get_mcp_interaction_text` method of the `MCPUseMetric` class, `available_primitives` is reinitialized for each loop iteration:

<img width="828" height="612" alt="Image" src="https://github.com/user-attachments/assets/124568ac-8d11-416e-9a1d-4b4476b5ef1b" />

**Pull Request**

[feat: mcp_use_metric support to multiple MCPs fixed](https://github.com/confident-ai/deepeval/pull/2076)

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