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mcp-server-sensory

mcp-server-sensory

by jaspertvdm
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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sstv_encode_text

Encode text into SSTV audio using Robot36, Martin, or Scottie modes. Returns base64 WAV for multi-modal AI communication.

Instructions

Encode text to SSTV audio (Robot36/Martin/Scottie). Returns base64 WAV. Multi-modal bridge for small LLMs!

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": {
      "text": "<text>"
    },
    "name": "sstv_encode_text"
  }
}

Input Schema

NameRequiredDescriptionDefault
textYesText to encode into image then SSTV audio
modeNoSSTV mode (robot36 is fastest)robot36

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.1

TDQS

A3.8/5.0
Behavior3/5

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

No annotations are provided, so the description carries full burden. It discloses the return format (base64 WAV) and mentions modes, but does not cover limitations like text length, audio duration, or performance characteristics.

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 (17 words) and front-loaded with the action. Every sentence adds value without repetition.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the simple tool with 2 well-described parameters and no output schema, the description covers the return format and purpose. It lacks details about limitations (e.g., text length) but is largely complete for the complexity level.

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% with descriptions already. The description adds 'Robot36/Martin/Scottie' as examples and the phrase 'multi-modal bridge', but does not significantly enhance parameter understanding beyond the schema.

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's function: 'Encode text to SSTV audio', specifies modes (Robot36/Martin/Scottie), and mentions output format (base64 WAV). This distinguishes it from siblings like sstv_encode_ponskaart and other encoding tools.

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 hints at use via 'Multi-modal bridge for small LLMs', but lacks explicit when-to-use or when-not-to-use guidance compared to sibling tools like sstv_encode_ponskaart or other modes. No alternatives or exclusions are mentioned.

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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