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mcp-sympy

mcp-sympy

by daedalus
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

sympy_divisors

Compute all divisors of any positive integer using symbolic mathematics, enabling number theory analysis and factorization tasks.

Instructions

Return divisors of n.

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_divisors"
  }
}

Input Schema

NameRequiredDescriptionDefault
nYesPositive integer

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, the description carries full burden for behavioral disclosure. It does not mention return type (e.g., list of integers), edge cases (e.g., n=1), performance characteristics, or any other behavioral traits. The description adds minimal insight beyond the basic function.

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 (one sentence) and front-loaded with the key action. It is not verbose, but for such a simple tool, the length is acceptable. However, a slightly expanded description could improve clarity without sacrificing conciseness.

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's simplicity (one parameter, no annotations, but an output schema is indicated as present), the description is adequate but minimally complete. It does not describe the output format or provide any example. More context (e.g., 'Returns a sorted list of positive divisors') would enhance completeness.

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 describes the single parameter 'n' as 'Positive integer' and has 100% schema coverage. The description does not add any additional meaning beyond what the schema already provides, so the 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 'Return divisors of n.' clearly states the action (return) and the resource (divisors of n). It is specific enough to convey the tool's purpose, though it does not distinguish it from siblings like sympy_divisor_sigma. However, the minimal description is still clear and unambiguous.

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 (e.g., sympy_factorint, sympy_divisor_sigma). The agent receives no context about prerequisites or typical use cases, making it hard to select the right tool.

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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