Skip to main content
Glama
zencoderai

Slack

by zencoderai

Reply to Slack Thread

slack_reply_to_thread

Reply to a specific message thread in a Slack channel by providing the channel ID, thread timestamp, and reply text.

Instructions

Reply to a specific message thread in Slack

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
channel_idYesThe ID of the channel containing the thread
thread_tsYesThe timestamp of the parent message in the format '1234567890.123456'. Timestamps in the format without the period can be converted by adding the period such that 6 numbers come after it.
textYesThe reply text

Implementation Reference

  • The async handler function that executes the slack_reply_to_thread tool, calling slackClient.postReply() and returning the response.
    async ({ channel_id, thread_ts, text }) => {
      const response = await slackClient.postReply(channel_id, thread_ts, text);
      return {
        content: [{ type: "text", text: JSON.stringify(response) }],
      };
    }
  • The input schema for the slack_reply_to_thread tool, defining channel_id (string), thread_ts (string), and text (string) parameters with Zod validation.
    inputSchema: {
      channel_id: z.string().describe("The ID of the channel containing the thread"),
      thread_ts: z.string().describe("The timestamp of the parent message in the format '1234567890.123456'. Timestamps in the format without the period can be converted by adding the period such that 6 numbers come after it."),
      text: z.string().describe("The reply text"),
    },
  • index.ts:266-283 (registration)
    The registration call for the slack_reply_to_thread tool via server.registerTool(), including the name, metadata (title, description), inputSchema, and handler.
    server.registerTool(
      "slack_reply_to_thread",
      {
        title: "Reply to Slack Thread",
        description: "Reply to a specific message thread in Slack",
        inputSchema: {
          channel_id: z.string().describe("The ID of the channel containing the thread"),
          thread_ts: z.string().describe("The timestamp of the parent message in the format '1234567890.123456'. Timestamps in the format without the period can be converted by adding the period such that 6 numbers come after it."),
          text: z.string().describe("The reply text"),
        },
      },
      async ({ channel_id, thread_ts, text }) => {
        const response = await slackClient.postReply(channel_id, thread_ts, text);
        return {
          content: [{ type: "text", text: JSON.stringify(response) }],
        };
      }
    );
  • The SlackClient.postReply() helper method that makes the actual Slack API call (chat.postMessage) with channel_id, thread_ts, and text parameters.
    async postReply(
      channel_id: string,
      thread_ts: string,
      text: string,
    ): Promise<any> {
      const response = await fetch("https://slack.com/api/chat.postMessage", {
        method: "POST",
        headers: this.botHeaders,
        body: JSON.stringify({
          channel: channel_id,
          thread_ts: thread_ts,
          text: text,
        }),
      });
    
      return response.json();
    }
  • TypeScript interface ReplyToThreadArgs defining the type structure for the tool arguments (channel_id, thread_ts, text).
    interface ReplyToThreadArgs {
      channel_id: string;
      thread_ts: string;
      text: string;
    }
Behavior2/5

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

No behavioral traits beyond the action are disclosed. Without annotations, the description should mention permissions, rate limits, or error behavior, but it does not. The description adds no value beyond the input schema.

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?

The description is a single, front-loaded sentence that efficiently states the purpose. It could be slightly more informative without losing conciseness.

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?

The description does not mention return values or error handling. Since there is no output schema, the user/agent lacks context on what the tool returns (e.g., reply timestamp). Missing completeness for a write operation.

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?

The input schema covers all three parameters with descriptions (100% coverage). The description adds no new meaning; the baseline of 3 is appropriate.

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 verb 'Reply' and the resource 'message thread', distinguishing it from siblings like slack_post_message (new message) and slack_get_thread_replies (reading replies).

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?

No guidance is provided on when to use this tool versus alternatives (e.g., slack_post_message for new messages or slack_get_thread_replies for reading replies). The description lacks any usage context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/zencoderai/slack-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server