io.github.anthonyjbolo/mcp-fb-publisher

fb_generate_post_with_image

Generate an image for a candidate Facebook post. Returns a URL to use with the publish action, allowing iterative visual refinement without consuming API quota.

Instructions

Generate an image for a candidate post and return a usable URL.

Does NOT publish. Caller is expected to take the returned image_url and pass it to fb_publish_post (or further validate via fb_validate_pre_publish). This separation lets the LLM iterate on the visual without burning Meta API quota.

Args: page_id: Numeric Meta Page ID (used only to resolve provider defaults). prompt: Image generation prompt (English recommended). image_provider: "openai" | "fal". Defaults to config.image_providers.default.

Returns: Dict with image_url, provider, model, prompt.

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": {
      "page_id": "<page_id>",
      "prompt": "<prompt>"
    },
    "name": "fb_generate_post_with_image"
  }
}

Input Schema

Name	Required	Description	Default
`page_id`	Yes
`prompt`	Yes
`image_provider`	No

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.1May 28, 2026

TDQS

A4.7/5.0

Behavior4/5

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

Given no annotations, the description covers key behaviors: no publishing, returns URL, allows iteration. It lacks rate limit or error details but is sufficient for a read-like generation tool.

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 well-structured with a clear summary, usage note, parameter details, and return description. Every sentence is concise and purposeful.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers purpose, workflow, parameters, and return values. It could mention error handling or limits, but for the complexity it is complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Despite 0% schema description coverage, the description's 'Args' section thoroughly explains each parameter, including defaults and recommended input, adding significant value.

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 tool generates an image for a candidate post and returns a usable URL, explicitly distinguishing it from publishing tools.

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

Usage Guidelines5/5

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

It provides explicit guidance: 'Does NOT publish' and directs the caller to use fb_publish_post or fb_validate_pre_publish next, including rationale about quota management.

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

Deploy Server