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mcp-server-sensory

mcp-server-sensory

by jaspertvdm
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

transcode

Convert input data between text, Morse code, Braille, Morse visual, or punchcard formats by specifying source and target encoding.

Instructions

Convert between different sensory encodings

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": {
      "input": "<input>",
      "from_format": "<from_format>",
      "to_format": "<to_format>"
    },
    "name": "transcode"
  }
}

Input Schema

NameRequiredDescriptionDefault
inputYesInput data
from_formatYesSource format
to_formatYesTarget format

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.1

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 should disclose behavioral traits like error handling, performance, or whether conversions are reversible. It only says 'convert', omitting any details about side effects or constraints, such as unsupported format pairs.

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 a single, front-loaded sentence that directly states the action. It is concise but could benefit from a brief example or usage note without becoming verbose.

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 lack of output schema, the description should explain the return format or behavior (e.g., returns a string). It also fails to differentiate from siblings or address potential conversion failures, leaving the agent underinformed.

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?

Schema coverage is 100%, so the description inherits clarity from parameter descriptions. However, it adds no additional meaning, e.g., explaining that 'from_format' and 'to_format' determine conversion direction, or that not all combinations are valid.

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 states 'Convert between different sensory encodings' which clearly indicates the tool's function—transcoding between formats like text, morse, and braille. This distinguishes it from sibling encode/decode tools that handle single conversions.

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?

The description provides no guidance on when to use this tool versus specific encode/decode siblings, nor does it mention limitations or prerequisites. For instance, it doesn't clarify that this tool should be used for cross-format conversion rather than simple encoding.

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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