Skip to main content
Glama
IBM

Physics MCP Server

by IBM

calculate_momentum

Calculate momentum from mass and velocity to analyze collisions, impacts, and motion conservation in physics problems.

Instructions

Calculate momentum from mass and velocity (p = mv).

Computes the momentum vector, which represents "quantity of motion."
Momentum is conserved in collisions, making it crucial for analyzing
impacts, explosions, and rocket propulsion.

Args:
    mass: Mass in kilograms (must be positive)
    velocity_x: X component of velocity in m/s
    velocity_y: Y component of velocity in m/s
    velocity_z: Z component of velocity in m/s

Returns:
    MomentumResponse containing:
        - momentum: Momentum vector [x, y, z] in kg⋅m/s
        - magnitude: Momentum magnitude in kg⋅m/s

Tips for LLMs:
    - Momentum is a vector (has direction), unlike kinetic energy
    - Total momentum before collision = total momentum after (conservation)
    - Large mass × small velocity can equal small mass × large velocity
    - Use to analyze: collisions, recoil, rocket thrust

Example:
    # Momentum of a 70kg person running at 5 m/s
    result = await calculate_momentum(
        mass=70.0,
        velocity_x=5.0,
        velocity_y=0.0,
        velocity_z=0.0
    )
    print(f"Momentum: {result.magnitude:.1f} kg⋅m/s")

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
massYes
velocity_xYes
velocity_yYes
velocity_zYes
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does well by explaining the physics concept (momentum conservation), the vector nature of the output, and providing practical examples. However, it doesn't mention computational limitations, error handling, or performance characteristics that would be useful for an agent.

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

Conciseness4/5

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

The description is well-structured with clear sections (formula, explanation, args, returns, tips, example) and every sentence adds value. It could be slightly more concise in the physics explanation section, but overall it's efficiently organized and front-loaded with the core functionality.

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

Completeness4/5

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

For a 4-parameter physics calculation tool with no annotations and no output schema, the description provides excellent context including the return structure, practical examples, and usage guidance. The main gap is the lack of explicit output schema documentation, but the 'Returns' section partially compensates for this.

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

Parameters5/5

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

Given 0% schema description coverage, the description fully compensates by providing detailed parameter documentation in the 'Args' section, including units (kilograms, m/s), constraints (mass must be positive), and the physical meaning of each velocity component. This adds significant value beyond what the bare schema provides.

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

Purpose5/5

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

The description clearly states the tool's purpose with a specific formula (p = mv) and distinguishes it from siblings by focusing on momentum calculation. It explicitly mentions this is for computing the momentum vector, differentiating it from related tools like calculate_kinetic_energy or calculate_angular_momentum.

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

Usage Guidelines5/5

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

The 'Tips for LLMs' section provides explicit guidance on when to use this tool versus alternatives, noting that 'momentum is a vector (has direction), unlike kinetic energy' and listing specific applications like collisions, recoil, and rocket thrust. This clearly distinguishes it from other physics calculation tools in the sibling list.

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/IBM/chuk-mcp-physics'

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