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mcp-sympy

mcp-sympy

by daedalus
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

sympy_lucas

Calculate the Lucas number for a given non-negative integer using SymPy's symbolic computation.

Instructions

Lucas number.

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": {
      "n": "<n>"
    },
    "name": "sympy_lucas"
  }
}

Input Schema

NameRequiredDescriptionDefault
nYesNon-negative integer

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.2/5.0
Behavior2/5

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

With no annotations, the description carries full burden for behavioral disclosure. It does not mention whether the tool handles large n, potential errors, or the return type. The single sentence conveys only the result, not the behavior.

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

Conciseness2/5

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

While extremely short, the description is underspecified. A concise description should still include an action verb; 'Lucas number' is a fragment. The sentence should be 'Computes the nth Lucas number.' or similar.

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 that the tool has an output schema but the description does not hint at the return value or any edge cases, it is incomplete. For a simple mathematical function, the description should at least mention that it returns the Lucas number and possibly the recurrence relation.

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 description adds no meaning beyond the input schema, which already documents n as 'Non-negative integer'. Since schema coverage is 100% and there is only one parameter, the description does not need to compensate, but it also provides no extra context such as range limits or formatting.

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

Purpose2/5

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

The description 'Lucas number' is a noun phrase that fails to specify the action. It does not state that the tool computes or returns the Lucas number for a given n, making it unclear whether the tool represents a constant or performs a computation. The sibling sympy_fibonacci likely has a similar minimal description but this one lacks a verb.

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 alternatives like sympy_fibonacci. There is no mention of use cases, prerequisites, or context where this tool is preferred.

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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