[tamohannes]

Summary

• Reopened from an internal NVIDIA-NeMo/Skills branch so CI can access repository secrets.
• Replaces Add CoolProp MCP tool #1413.
• Add a built-in CoolProp MCP tool for thermophysical fluid property lookup.
• Document the new built-in tool and add focused MCP client tests.

Test plan

• python -m py_compile nemo_skills/mcp/servers/coolprop_tool.py
• python -m pytest tests/test_mcp_clients.py::TestCoolPropTool -q --tb=short
• python -m pytest tests/test_mcp_clients.py -q --tb=short

Summary by CodeRabbit

• New Features

  • Added a CoolProp-based tool for thermophysical fluid lookups: query fluid properties by temperature and pressure and list available fluids.

• Documentation

  • Updated the Built-in Tools reference to include the new CoolProp tool and usage notes.

• Tests

  • Added tests to verify tool configuration and that both property-lookup and fluid-list endpoints are exposed.

[coderabbitai]

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• tests/test_mcp_clients.py

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• tests/test_mcp_clients.py

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📝 Walkthrough

Walkthrough

Adds a new MCP tool module nemo_skills.mcp.servers.coolprop_tool.CoolPropTool that exposes fluid-property and fluid-list endpoints using the CoolProp library, adds tests verifying config and listed tools, and documents the tool in the Built-in Tools reference (notes CoolProp dependency).

Changes

CoolPropTool Feature

Layer / File(s)	Summary
Data / Utility functions nemo_skills/mcp/servers/coolprop_tool.py	Adds fluid_property(fluid, output_property, temperature, pressure) with positive-temperature/pressure validation, CoolProp PropsSI call, error handling, property descriptions, and markdown formatting.
Helper / Listing nemo_skills/mcp/servers/coolprop_tool.py	Adds fluid_list() that queries CoolProp.FluidsList(), sorts fluids, and returns a markdown list.
Core MCP wiring nemo_skills/mcp/servers/coolprop_tool.py	Adds CoolPropTool class implementing default_config, configure, async list_tools (JSON-schema for fluid-property and fluid-list), and async execute dispatcher routing to the two functions and returning an error for unknown tools.
Tests / Integration tests/test_mcp_clients.py	Adds TestCoolPropTool with test_coolprop_tool_config asserting default_config() == {} and test_coolprop_direct_list_tools (async) asserting list_tools() includes fluid-property and fluid-list after configure().
Documentation docs/agentic_inference/tool_calling.md	Adds Built-in Tools reference entry for nemo_skills.mcp.servers.coolprop_tool.CoolPropTool, describing CoolProp-based thermophysical property lookup and noting the CoolProp dependency.

sequenceDiagram
    participant Client
    participant MCP_Server as "CoolPropTool (MCP)"
    participant CoolProp as "CoolProp Library"
    Client->>MCP_Server: execute("fluid-property", {fluid, output_property, temperature, pressure})
    MCP_Server->>CoolProp: PropsSI(output_property, "T", temperature, "P", pressure, fluid)
    CoolProp-->>MCP_Server: value or error
    MCP_Server-->>Client: markdown-formatted result or error

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🚥 Pre-merge checks | ✅ 4 | ❌ 1

❌ Failed checks (1 warning)

Check name	Status	Explanation	Resolution
Docstring Coverage	⚠️ Warning	Docstring coverage is 30.00% which is insufficient. The required threshold is 80.00%.	Write docstrings for the functions missing them to satisfy the coverage threshold.

✅ Passed checks (4 passed)

Check name	Status	Explanation
Description Check	✅ Passed	Check skipped - CodeRabbit’s high-level summary is enabled.
Title check	✅ Passed	The title 'Add CoolProp MCP tool' clearly and concisely summarizes the main change: introducing a new CoolProp MCP tool for thermophysical fluid property lookup.
Linked Issues check	✅ Passed	Check skipped because no linked issues were found for this pull request.
Out of Scope Changes check	✅ Passed	Check skipped because no linked issues were found for this pull request.

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• Create PR with unit tests
• Commit unit tests in branch feat/coolprop-mcp-tool

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[coderabbitai]

Actionable comments posted: 1

🧹 Nitpick comments (1)

tests/test_mcp_clients.py (1)

1010-1025: ⚡ Quick win

Add a direct execute() smoke test for the new tool.

Right now the suite only checks config and tool names, so a broken dispatch path or CoolProp import would still pass. A single fluid-list call would cover the actual runtime entry point.

♻️ Proposed test addition

     tool = CoolPropTool()
     tool.configure()
     tool_names = {t["name"] for t in await tool.list_tools()}
     assert "fluid-property" in tool_names
     assert "fluid-list" in tool_names
+
+    result = await tool.execute("fluid-list", {})
+    assert "fluids available" in result

🤖 Prompt for AI Agents

Verify each finding against the current code and only fix it if needed.

In `@tests/test_mcp_clients.py` around lines 1010 - 1025, Add a smoke test that
actually calls the tool runtime entrypoint: instantiate CoolPropTool(), call
configure(), find the tool descriptor for "fluid-list" from await
tool.list_tools(), then call await tool.execute(tool_descriptor, {}) (or the
execute signature used by CoolPropTool) and assert the call returns a successful
result (e.g., non-empty list or expected keys). Update the TestCoolPropTool
class (near test_coolprop_direct_list_tools) to include a new async test method
that locates the "fluid-list" tool and exercises CoolPropTool.execute to catch
import/dispatch/runtime errors.

🤖 Prompt for all review comments with AI agents

Verify each finding against the current code and only fix it if needed.

Inline comments:
In `@docs/agentic_inference/tool_calling.md`:
- Around line 374-375: Remove the duplicated bullet for
nemo_skills.mcp.servers.coolprop_tool.CoolPropTool in the tool list: keep a
single entry for CoolPropTool (with the preferred description—e.g.,
"Thermophysical fluid property lookup via CoolProp (requires `CoolProp`)") and
delete the other identical line so the built-in-tools list contains only one
CoolPropTool entry.

---

Nitpick comments:
In `@tests/test_mcp_clients.py`:
- Around line 1010-1025: Add a smoke test that actually calls the tool runtime
entrypoint: instantiate CoolPropTool(), call configure(), find the tool
descriptor for "fluid-list" from await tool.list_tools(), then call await
tool.execute(tool_descriptor, {}) (or the execute signature used by
CoolPropTool) and assert the call returns a successful result (e.g., non-empty
list or expected keys). Update the TestCoolPropTool class (near
test_coolprop_direct_list_tools) to include a new async test method that locates
the "fluid-list" tool and exercises CoolPropTool.execute to catch
import/dispatch/runtime errors.

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• docs/agentic_inference/tool_calling.md
• nemo_skills/mcp/servers/coolprop_tool.py
• tests/test_mcp_clients.py

[gwarmstrong]

please fix the DCO check