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PostKing MCP Server

PostKing MCP Server

by bitsandtea
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Hybrid

get_blog_status

Check the generation status of a blog article using its article ID. Finds out whether it is pending, running, completed, or failed.

Instructions

Poll the async generation status of a blog article. Use the articleId returned by generate_blog_post. Status: pending | running | completed | failed.

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": {
      "articleId": "<articleId>"
    },
    "name": "get_blog_status"
  }
}

Input Schema

NameRequiredDescriptionDefault
brandIdNoBrand ID (uses active brand if omitted)
articleIdYesBlog article ID returned by generate_blog_post

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.1.7

TDQS

A4/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden of disclosing behavior. It does state that this is a polling operation, which implies a non-mutating read, and it enumerates the status values. But it omits details about response structure, polling frequency, or error cases, and does not explicitly confirm that the tool is safe/read-only. The minimal disclosure is adequate but not rich.

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 two short sentences with no filler. It front-loads the purpose and then provides the essential usage pointer and status values. Every sentence earns its place.

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?

For a simple polling tool, the description provides the key context: how to obtain the articleId, what statuses to expect, and that it is an async-generation status. The schema covers parameter details, and no output schema is needed to convey return values. It could mention timeout/retry behavior or confirm this is a read-only operation, but the essentials are present.

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 already describes both parameters with 100% coverage (articleId as the ID returned by generate_blog_post, brandId as optional). The description reinforces the meaning of articleId but adds no new parameter semantics beyond what the schema provides, so it meets the baseline without exceeding it.

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 opens with a specific verb and resource: 'Poll the async generation status of a blog article.' This clearly distinguishes it from sibling tools like generate_blog_post (creation) and get_blog_article (retrieval of content), while also naming the exact resource (blog article).

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 by instructing to use the articleId returned by generate_blog_post, implying this tool is called after generation has started. It also lists the possible statuses, helping the agent know what to expect. However, it does not explicitly mention when not to use this tool or name any alternatives.

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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