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mcp-sympy

mcp-sympy

by daedalus
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

sympy_matrix_determinant

Calculate the determinant of a symbolic matrix by providing a SymPy matrix string.

Instructions

Compute matrix determinant.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "matrix": "<matrix>"
    },
    "name": "sympy_matrix_determinant"
  }
}

Input Schema

NameRequiredDescriptionDefault
matrixYesA SymPy matrix string, e.g., "Matrix([[1, 2], [3, 4]])"

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
Behavior2/5

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 only states 'compute' without details on side effects, performance, or error conditions. This is insufficient for an agent to fully understand the tool's behavior.

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 extremely concise at just three words, which is efficient. However, it may be too minimal, missing opportunities to add value. Still, it is front-loaded and to the point.

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

Completeness3/5

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

Given the tool has an output schema (as per context signals), the description does not need to explain return values. However, for a mathematical tool, mentioning that the result is a scalar or expression would improve completeness. The current description is adequate but minimal.

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

Parameters3/5

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

The input schema already provides a detailed description for the only parameter (matrix). The tool description adds no additional semantic information beyond what the schema offers, so baseline score of 3 is appropriate.

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?

The description clearly states the action ('compute') and the resource ('matrix determinant'), which is specific among sibling matrix tools. However, it doesn't explicitly differentiate from similar tools like sympy_matrix_inverse or sympy_matrix_rank, but the purpose is still evident.

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 is provided on when to use this tool versus alternative tools such as sympy_matrix_rank or sympy_matrix_inverse. The description lacks context for decision-making.

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

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