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mcp-ai-agent-server

mcp-ai-agent-server

by elcaiseri
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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calculate

Evaluate mathematical expressions safely, such as '2 + 2' or 'sqrt(16)', and return the calculation result.

Instructions

Evaluate a mathematical expression safely.

Args: expression: Mathematical expression (e.g., "2 + 2", "sqrt(16)")

Returns: Calculation result

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": {
      "expression": "<expression>"
    },
    "name": "calculate"
  }
}

Input Schema

NameRequiredDescriptionDefault
expressionYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior2/5

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

No annotations are provided, so the description bears full burden. It mentions 'safely' but does not elaborate on what safety entails (e.g., sandboxing, no side effects). No information on error handling, edge cases, or return format details.

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

Conciseness5/5

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

The description is extremely concise: three short sentences plus a bullet-like list. It front-loads the purpose and wastes no words. Every sentence adds value.

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 (single parameter, no output schema), the description covers the input and basic output. However, it does not specify the return type (e.g., number or string) or describe limits, making it slightly incomplete for an agent to fully understand the behavior.

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

Parameters4/5

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

With 0% schema coverage, the description compensates by providing concrete examples like '2 + 2' and 'sqrt(16)', which imply support for operators and functions. This adds meaning beyond the schema's bare type string, though a comprehensive list of supported operations is absent.

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 evaluates mathematical expressions safely, with a specific verb 'evaluate' and resource 'mathematical expression'. This purpose is distinct from sibling tools like 'convert_units' or 'execute_command'.

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

Usage Guidelines3/5

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

The description implies the tool is for safe mathematics, but does not explicitly state when to use it instead of siblings like 'execute_command'. No guidance on exclusions or alternatives is provided.

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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