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Everyday DevTools MCP

Everyday DevTools MCP

by Deependra12349
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

base64_decode

Decode Base64 strings back to plain text to inspect encoded data or recover original content.

Instructions

Decode a Base64 string back to text.

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": "base64_decode"
  }
}

Input Schema

NameRequiredDescriptionDefault
textYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.2/5.0
Behavior2/5

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

No annotations are supplied, so the description carries the full burden of behavioral disclosure, and it discloses almost nothing. It does not state what happens with invalid Base64, whether errors are thrown or empty output returned, or how non-UTF-8/binary bytes are handled. For a decode operation those failure semantics are the main thing an agent needs to predict.

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?

One short, front-loaded sentence with no wasted words and the operation stated immediately. The economy is appropriate for a single-parameter utility, though the brevity is also the source of the missing behavioral detail.

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?

For a trivial one-parameter tool with no output schema and no annotations, the description is close to sufficient but leaves error behavior and output encoding undefined. Complexity is low, so the gap is modest rather than disqualifying.

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 description coverage is 0% for the single parameter, so the description must compensate. It does partly: calling the input a 'Base64 string' resolves the mismatch between the parameter name 'text' and the actual expected content. It adds no further detail on format, padding, or whitespace tolerance.

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 gives a specific verb and resource ('Decode a Base64 string') and clearly contrasts with the sibling base64_encode through the encode/decode distinction. It stops short of naming siblings explicitly, but an agent can still tell them apart without opening the schema.

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?

Usage is only implied: use it when you have Base64 that you want as text. There is no explicit when-to-use framing, no mention of alternatives such as url_decode or jwt_decode for other encoded formats, and no note about when this tool would be the wrong choice.

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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