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jar285

MCP-Discord

by jar285

discord_add_reaction

Add emoji reactions to Discord messages by specifying channel ID, message ID, and emoji. This tool enables AI assistants to interact with Discord platforms through the MCP-Discord server.

Instructions

Adds an emoji reaction to a specific Discord message

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
channelIdYes
messageIdYes
emojiYes

Implementation Reference

  • The handler logic for the discord_add_reaction tool. It validates input with AddReactionSchema, checks client readiness, fetches the channel and message, adds the emoji reaction using Discord.js message.react(), and returns success or error response.
    case "discord_add_reaction": {
      const { channelId, messageId, emoji } = AddReactionSchema.parse(args);
      try {
        if (!client.isReady()) {
          return {
            content: [{ type: "text", text: "Discord client not logged in. Please use discord_login tool first." }],
            isError: true
          };
        }
    
        const channel = await client.channels.fetch(channelId);
        if (!channel || !channel.isTextBased() || !('messages' in channel)) {
          return {
            content: [{ type: "text", text: `Cannot find text channel with ID: ${channelId}` }],
            isError: true
          };
        }
    
        const message = await channel.messages.fetch(messageId);
        if (!message) {
          return {
            content: [{ type: "text", text: `Cannot find message with ID: ${messageId}` }],
            isError: true
          };
        }
    
        // Add the reaction
        await message.react(emoji);
    
        return {
          content: [{ 
            type: "text", 
            text: `Successfully added reaction ${emoji} to message ID: ${messageId}` 
          }]
        };
      } catch (error) {
        return {
          content: [{ type: "text", text: `Failed to add reaction: ${error}` }],
          isError: true
        };
      }
    }
  • Zod schema for input validation of discord_add_reaction tool parameters: channelId, messageId, emoji.
    const AddReactionSchema = z.object({
        channelId: z.string(),
        messageId: z.string(),
        emoji: z.string()
    });
  • src/index.ts:331-343 (registration)
    Tool registration in the ListTools response, including name, description, and inputSchema matching the Zod schema.
    {
      name: "discord_add_reaction",
      description: "Adds an emoji reaction to a specific Discord message",
      inputSchema: {
        type: "object",
        properties: {
          channelId: { type: "string" },
          messageId: { type: "string" },
          emoji: { type: "string" }
        },
        required: ["channelId", "messageId", "emoji"]
      }
    },
  • Input schema definition in the tool registration for discord_add_reaction.
    inputSchema: {
      type: "object",
      properties: {
        channelId: { type: "string" },
        messageId: { type: "string" },
        emoji: { type: "string" }
      },
      required: ["channelId", "messageId", "emoji"]
    }
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It states the action but doesn't mention whether this requires specific permissions, rate limits, potential side effects (e.g., notification to message author), or what happens on success/failure. For a mutation tool with zero annotation coverage, this is a significant gap.

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 a single, clear sentence with zero wasted words. It's appropriately sized for a simple tool and front-loads the core functionality immediately.

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?

For a mutation tool with 3 parameters, 0% schema description coverage, no annotations, and no output schema, the description is inadequate. It doesn't compensate for the missing structured information about parameters, behavior, or results, leaving significant gaps for the agent.

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%, meaning none of the 3 parameters are documented in the schema. The description doesn't add any parameter information beyond what's implied by the tool name (emoji parameter). It doesn't explain what format 'emoji' should be in, how to obtain 'channelId' and 'messageId', or any constraints on these values.

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 clearly states the action ('Adds an emoji reaction') and target ('to a specific Discord message'), providing a specific verb+resource combination. However, it doesn't explicitly differentiate from its sibling 'discord_remove_reaction' or 'discord_add_multiple_reactions', which would be needed for a perfect score.

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 alternatives like 'discord_add_multiple_reactions' or 'discord_remove_reaction'. It also doesn't mention prerequisites (e.g., needing appropriate permissions) or contextual constraints, leaving the agent with minimal usage direction.

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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