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Everyday DevTools MCP

Everyday DevTools MCP

by Deependra12349
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

base64_encode

Encodes plain text into Base64 format for safe transmission, storage, or embedding in data URLs and API payloads.

Instructions

Encode text to Base64.

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_encode"
  }
}

Input Schema

NameRequiredDescriptionDefault
textYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.8/5.0
Behavior2/5

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

With no annotations, the description carries the full behavioral burden, yet it discloses nothing about the encoding variant (standard vs URL-safe), padding, or character set handling (UTF-8 vs binary). For an encoding transformation these details determine whether the output will round-trip correctly.

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 filler. It is efficient, though the same brevity is the root cause 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 one-parameter utility the output type (a Base64 string) is obvious without an output schema, so the description is close to sufficient. However, the encoding variant and charset questions are exactly what an agent needs for correct invocation and are left unanswered.

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?

Schema description coverage is 0% for the single 'text' parameter, and the description only restates that text is encoded. It does not clarify expected character set, whether newlines/binary are accepted, or size limits, so it fails to compensate for the coverage gap.

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 ('Encode text to Base64'), which is unambiguous and trivially distinguishes it from the sibling base64_decode. It stops short of an explicit sibling differentiation, but the operation itself is unmistakable.

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?

There is no when-to-use guidance, no mention of when to prefer url_encode or hash_text instead, and no note about input constraints. The agent must infer usage entirely from the tool name.

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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