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Discord MCP - Discord server management MCP for AI agents

Discord MCP - Discord server management MCP for AI agents

Create emoji

create_emoji

Upload a custom emoji to a Discord server from an image URL, using PNG, JPEG, GIF, or WebP files within Discord's 256 KB size limit.

Instructions

Upload a custom emoji from an image URL. Discord's limit for emoji files is 256 KB; png, jpeg, gif, and webp work.

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": {
      "name": "<name>",
      "image_url": "<image_url>"
    },
    "name": "create_emoji"
  }
}

Input Schema

NameRequiredDescriptionDefault
nameYes
guildNoGuild (server) name or ID. Omit to use the default guild.
image_urlYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.4.2
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
  2. Changed1 schema field changedv1.3.0
    • removedInput schema / additionalProperties
      Removed value: -false
  3. First observedv1.0.2

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already declare this is a non-read-only, non-destructive write, so the safety profile is covered. The description adds genuinely useful constraints (256 KB limit, supported formats: png/jpeg/gif/webp) but says nothing about required permissions, emoji slot limits, or behavior on name collision.

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?

Two tight sentences with the core action front-loaded and the constraint immediately after. No redundant restatement of the title or schema.

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 simple three-parameter create tool with no output schema, this is close but leaves gaps: name rules, permission requirements, and expected result are unaddressed. The image constraints it does include are the most valuable part.

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 low at 33% — only the optional `guild` parameter is documented. The description compensates partially by explaining the image_url constraints (size and accepted formats), but gives no meaning for the required `name` parameter beyond the schema's pattern and length limits.

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 a specific verb and resource: 'Upload a custom emoji from an image URL.' Combined with the name, it is clearly distinguishable from delete_emoji and update_emoji, though it doesn't explicitly name those siblings.

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 by the tool name; there is no explicit statement of when to use this versus update_emoji or when creation would fail. The 256 KB and format notes are invocation constraints rather than selection guidance.

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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