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The-Focus-AI

Buttondown MCP Server

by The-Focus-AI

schedule_draft

Schedule an existing email draft for automated sending at a specified time using the Buttondown newsletter service.

Instructions

Schedule an existing email draft to be sent at a specific time. This tool requires explicit user confirmation before proceeding as it will modify the draft's status and schedule.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
draftIdYesThe ID of the email draft to schedule
scheduledTimeYesWhen to send the email (ISO 8601 datetime format)
confirmedYesMust be true to confirm the scheduling

Implementation Reference

  • Registration of the MCP 'schedule_draft' tool using this.server.tool(). Includes tool description, Zod input schema (draftId: string, scheduledTime: string, confirmed: boolean), and inline handler function that checks confirmation, ensures API key, calls api.scheduleDraft(draftId, scheduledTime), and returns JSON response.
    this.server.tool(
      "schedule_draft",
      "Schedule an existing email draft to be sent at a specific time. This tool requires explicit user confirmation before proceeding as it will modify the draft's status and schedule.",
      {
        draftId: z.string().describe("The ID of the email draft to schedule"),
        scheduledTime: z
          .string()
          .describe("When to send the email (ISO 8601 datetime format)"),
        confirmed: z
          .boolean()
          .describe("Must be true to confirm the scheduling"),
      },
      async ({ draftId, scheduledTime, confirmed }) => {
        if (!confirmed) {
          return {
            content: [
              {
                type: "text",
                text: JSON.stringify(
                  {
                    error: "User confirmation required",
                    message:
                      "Please ask the user if they want to schedule this draft and set confirmed=true if they agree",
                    preview: {
                      draftId,
                      scheduledTime,
                      localTime: new Date(scheduledTime).toLocaleString(),
                    },
                  },
                  null,
                  2
                ),
              },
            ],
          };
        }
        await this.ensureApiKey();
        const response = await this.api.scheduleDraft(draftId, scheduledTime);
        return {
          content: [
            {
              type: "text",
              text: JSON.stringify(response, null, 2),
            },
          ],
        };
      }
    );
  • Core handler logic for scheduling a draft via Buttondown API: PATCH /emails/{draftId} with body {scheduled_for, publish_date: scheduledTime, status: 'scheduled'}.
    async scheduleDraft(
      draftId: string,
      scheduledTime: string
    ): Promise<ButtondownEmail> {
      return this.request<ButtondownEmail>(`/emails/${draftId}`, {
        method: "PATCH",
        body: JSON.stringify({
          scheduled_for: scheduledTime,
          publish_date: scheduledTime,
          status: "scheduled",
        }),
      });
    }
  • TypeScript interface IButtondownAPI defining scheduleDraft(draftId: string, scheduledTime: string): Promise<ButtondownEmail>.
    scheduleDraft(
      draftId: string,
      scheduledTime: string
    ): Promise<ButtondownEmail>;
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key traits: it modifies the draft's status and schedule (indicating a mutation), requires user confirmation, and implies a time-based action. However, it lacks details on error handling, rate limits, or specific permissions needed.

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 appropriately sized with two sentences that are front-loaded and efficient. The first sentence states the purpose, and the second adds crucial behavioral context (confirmation requirement and modification effects), with no wasted words.

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?

Given the tool's complexity (a mutation with user confirmation), no annotations, and no output schema, the description is somewhat complete but has gaps. It covers the action and confirmation need but lacks details on return values, error cases, or full behavioral context, making it adequate but not fully comprehensive.

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 schema description coverage is 100%, so the schema already documents all parameters (draftId, scheduledTime, confirmed). The description adds minimal value beyond the schema by implying the purpose of scheduling but does not provide additional syntax, format details, or usage examples for the parameters.

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 specific action ('Schedule an existing email draft') and the resource ('email draft'), distinguishing it from sibling tools like create_draft (creation), get_analytics (analysis), and list_emails (listing). It specifies the outcome ('to be sent at a specific time') without being tautological.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context for when to use this tool ('Schedule an existing email draft') and includes a prerequisite ('requires explicit user confirmation'), but it does not explicitly state when not to use it or name alternatives among the sibling tools (e.g., when to use create_draft instead).

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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