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mcp-sympy

mcp-sympy

by daedalus
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

sympy_tanh

Compute the hyperbolic tangent of any mathematical expression with symbolic precision.

Instructions

Hyperbolic tangent.

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": {
      "expr": "<expr>"
    },
    "name": "sympy_tanh"
  }
}

Input Schema

NameRequiredDescriptionDefault
exprYesExpression

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.6/5.0
Behavior2/5

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

No annotations are provided, and the description gives no behavioral details (e.g., domain, range, or special values). It merely restates the function name without elaboration.

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?

The description is extremely concise (two words) but lacks structure. It is more of a label than a sentence. While concise, it could be slightly expanded without losing efficiency.

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 the presence of an output schema, the description does not need to explain return values, but it fails to provide any context about the operation. For a simple tool, a brief sentence like 'Computes the hyperbolic tangent of the given expression.' would improve completeness.

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

Parameters2/5

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

The input schema parameter 'expr' has a generic description 'Expression'. The tool description adds nothing beyond this, failing to clarify what type of expression is expected (e.g., a SymPy expression). Despite high schema coverage, the description underperforms.

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 'Hyperbolic tangent.' clearly identifies the mathematical function, distinguishing it from sibling functions like tan or sinh. However, it does not explicitly state that it computes the hyperbolic tangent of the input expression, leaving minor ambiguity.

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 such as sympy_tan, sympy_sinh, or other trigonometric functions. The agent must infer context from the name alone.

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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