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blogger-mcp

blogger-mcp

by mech12
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Local

list_posts

Retrieve blog posts from Google Blogger by specifying a blog ID, with options to filter by status and limit results.

Instructions

List posts of a blog

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": {
      "blogId": "<blogId>"
    },
    "name": "list_posts"
  }
}

Input Schema

NameRequiredDescriptionDefault
blogIdYes
maxResultsNo
statusNoFilter by status (optional)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. 'List posts of a blog' implies a read operation but does not specify whether it requires authentication, has rate limits, returns paginated results, or handles errors. For a tool with three parameters and no annotation coverage, this is a significant gap in transparency.

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 a single, efficient sentence with no wasted words. It is front-loaded and directly states the tool's purpose without unnecessary elaboration, making it easy to parse quickly. This meets the criteria for high 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's complexity (three parameters, no annotations, no output schema), the description is incomplete. It lacks details on behavioral traits, parameter usage, and output expectations. For a list operation that likely returns multiple items, more context is needed to guide effective use, making this inadequate for the tool's requirements.

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 description does not mention any parameters, leaving all semantic details to the input schema. With schema description coverage at 33% (only 'status' has a description), the parameters 'blogId' and 'maxResults' are undocumented. The description adds no value beyond the schema, but since the schema provides some coverage, a baseline score of 3 is appropriate.

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 'List posts of a blog' clearly states the verb ('list') and resource ('posts of a blog'), making the tool's purpose understandable. However, it does not distinguish this tool from potential siblings like 'list_blogs' or 'get_post', which could cause confusion in selection. The specificity is adequate but lacks sibling differentiation.

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?

The description provides no guidance on when to use this tool versus alternatives. With siblings like 'list_blogs', 'get_post', and 'get_blog_by_url', there is no indication of context, prerequisites, or exclusions. This absence of usage instructions may lead to incorrect tool selection by an AI agent.

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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