Skip to main content
Glama
Ching-Chiang

comsol-mcp

by Ching-Chiang

ensure_geometry

Ensure a geometry sequence exists in a server-side COMSOL model by specifying component, geometry name, and spatial dimension.

Instructions

Ensure a geometry sequence exists in the selected server-side model.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
componentNocomp1
geometryNogeom1
dimensionNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The `ensure_geometry` MCP tool function decorated with @mcp.tool(). It defines the handler that wraps the inner _impl function and calls _run_tool to execute the tool logic.
    @mcp.tool()
    def ensure_geometry(component: str = "comp1", geometry: str = "geom1", dimension: int = 2) -> str:
        """Ensure a geometry sequence exists in the selected server-side model."""
    
        def _impl() -> dict[str, Any]:
            return _ensure_geometry_java(
                _require_model(),
                component.strip() or "comp1",
                geometry.strip() or "geom1",
                int(dimension),
            )
    
        return _run_tool("ensure_geometry", _impl)
  • The `_ensure_geometry_java` helper function that performs the actual COMSOL Java API calls: ensures a component exists, then ensures a geometry sequence with the given dimension exists within that component.
    def _ensure_geometry_java(model: Any, component: str, geometry: str, dimension: int) -> dict[str, Any]:
        java = model.java
        if component not in list(java.component().tags()):
            java.component().create(component, True)
        if dimension <= 0:
            dimension = 2
        if geometry not in list(java.component(component).geom().tags()):
            java.component(component).geom().create(geometry, dimension)
        return {"component": component, "geometry": geometry, "dimension": dimension}
  • The inner `_impl` closure inside ensure_geometry that calls _ensure_geometry_java with the current model and validated arguments.
    def _impl() -> dict[str, Any]:
        return _ensure_geometry_java(
            _require_model(),
            component.strip() or "comp1",
            geometry.strip() or "geom1",
            int(dimension),
        )
  • The docstring/description and parameter definitions (component, geometry, dimension) for the ensure_geometry tool.
    def ensure_geometry(component: str = "comp1", geometry: str = "geom1", dimension: int = 2) -> str:
        """Ensure a geometry sequence exists in the selected server-side model."""
  • The @mcp.tool() decorator on ensure_geometry registers this function as an MCP tool with the FastMCP server instance.
    @mcp.tool()
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, and description fails to disclose behavioral traits such as idempotency, side effects, or what 'ensure' means (create vs check). Minimal transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Single sentence is concise but lacks structure; it is minimally informative but not wasteful. Could benefit from additional context without being verbose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given three parameters, no annotations, and an output schema, the description is incomplete. It does not explain parameter roles, output meaning, or behavioral details.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the description adds no meaning to any of the three parameters (component, geometry, dimension). The defaults exist in schema but are unexplained.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states the tool ensures a geometry sequence exists in a server-side model, using specific verb and resource. It distinguishes from siblings like ensure_component and ensure_mesh by naming geometry, but lacks explicit differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives, no prerequisites, no exclusions. The description is purely declarative without usage context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Ching-Chiang/comsol-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server