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maasy_generate_content

Generate social media content aligned with your brand identity. Supply a creation prompt and optionally specify platform. Content respects brand DNA, tone, and ideal customer profile.

Instructions

Generate on-brand social content using maasy AI. Respects brand DNA, tone, ICP.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_idNoBrand UUID
promptYesWhat to generate (e.g. '3 Instagram posts about our product launch')
platformNogeneral

Implementation Reference

  • src/index.ts:248-260 (registration)
    Registers the 'maasy_generate_content' tool with the MCP server, defining its input schema (project_id, prompt, platform) and delegating execution to toolHandler('generate_content').
    server.tool(
      "maasy_generate_content",
      "Generate on-brand social content using maasy AI. Respects brand DNA, tone, ICP.",
      {
        project_id: z.string().optional().describe("Brand UUID"),
        prompt: z.string().describe("What to generate (e.g. '3 Instagram posts about our product launch')"),
        platform: z
          .enum(["instagram", "facebook", "linkedin", "twitter", "tiktok", "general"])
          .optional()
          .default("general"),
      },
      toolHandler("generate_content")
    );
  • Zod schema for maasy_generate_content: optional project_id, required prompt string, optional platform enum (instagram, facebook, linkedin, twitter, tiktok, general) defaulting to 'general'.
    {
      project_id: z.string().optional().describe("Brand UUID"),
      prompt: z.string().describe("What to generate (e.g. '3 Instagram posts about our product launch')"),
      platform: z
        .enum(["instagram", "facebook", "linkedin", "twitter", "tiktok", "general"])
        .optional()
        .default("general"),
    },
  • Generic toolHandler wrapper that calls callGateway(toolName, args) to invoke the 'generate_content' tool via the Supabase edge function gateway, returning the result as text content.
    function toolHandler(toolName: string, argsFn?: (args: Record<string, unknown>) => Record<string, unknown>) {
      return async (args: Record<string, unknown>) => {
        try {
          const gatewayArgs = argsFn ? argsFn(args) : args;
          // Auto-inject default project_id if not provided
          if (DEFAULT_PROJECT_ID && !gatewayArgs.project_id) {
            gatewayArgs.project_id = DEFAULT_PROJECT_ID;
          }
          const result = await callGateway(toolName, gatewayArgs);
          return { content: [{ type: "text" as const, text: JSON.stringify(result, null, 2) }] };
        } catch (e: unknown) {
          return {
            content: [{ type: "text" as const, text: `Error: ${e instanceof Error ? e.message : String(e)}` }],
            isError: true,
          };
        }
      };
    }
  • The callGateway function that sends the tool name ('generate_content') and args to the mcp-gateway Supabase edge function, handling auth and response parsing.
    export async function callGateway(tool: string, args: Record<string, unknown> = {}): Promise<unknown> {
      const res = await fetch(gatewayUrl, {
        method: "POST",
        headers: {
          "Content-Type": "application/json",
          [authHeader.name]: authHeader.value,
        },
        body: JSON.stringify({ tool, args }),
      });
    
      const data = await res.json();
    
      if (!res.ok) {
        throw new Error(data.error || `Gateway error (${res.status})`);
      }
    
      return data.result;
    }

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.3.1

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations, the description carries the full burden of disclosing behavior. It mentions 'Respects brand DNA, tone, ICP' which gives a hint of behavioral traits, but it doesn't explain the generation process, required inputs (like project_id), or return format. This is insufficient for understanding side effects or prerequisites.

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 very concise at two sentences, with no redundant information. The second sentence adds a behavioral trait but is still brief. It gets to the point efficiently, though 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?

Given the tool has three parameters, no output schema, and no annotations, the description is too minimal. It doesn't mention any prerequisites, what the output looks like, how platform affects generation, or error conditions. For a content generation tool, this is below the minimum viable description.

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 covers 67% of parameters with descriptions (prompt and project_id). The description adds no direct parameter semantics, but the schema already provides meaningful descriptions. The platform parameter has an enum but no description, and the description doesn't clarify it. Baseline 3 given the schema coverage.

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 tool generates on-brand social content via 'Generate on-brand social content using maasy AI.' It identifies the verb (generate), resource (social content), and a key attribute (on-brand). However, it does not explicitly distinguish it from the sibling maasy_generate_ads, which also generates content.

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 vs alternatives like maasy_generate_ads. The description only states what it does and that it respects brand DNA, but does not specify contexts, prerequisites, or exclusions.

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