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Misar.Blog MCP Server

by io.github.Misar-AI
OverviewAdmin

Generate SEO titles from keywords

generate_title_seo
Read-only

Generate 5 search-optimised article titles from a TOPIC OR KEYWORD, each with a keyword-strategy hint. Aims at high-volume, low-competition long-tail phrases and at AI answer engines (ChatGPT, Perplexity, Claude) as well as Google.

Pick between the two title tools by what you have in hand: use this one when you have a topic or keywords and the article may not be written yet. Use suggest_titles when the draft already exists and you want titles drawn from its actual text. Passing context here does not make them equivalent — this one still optimises for the keywords you supply.

Nothing is saved and no article is created or retitled; use update_article to apply a title. Requires an API key and consumes AI credits per call. Generative, so repeated calls return different titles.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYesTopic or target keywords, 3-500 characters. Include niche, audience and any long-tail phrase you want to rank for, e.g. 'best AI writing tools for beginner bloggers 2025'.
contextNoOptional draft text (plain or Markdown, up to 8000 chars) so the titles match what the article actually says. Titles still follow `prompt` for keywords.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed2 schema fields changed
    • changedInput schema / properties / context / description
      Previous value: -"Optional: existing article content (plain text or markdown). Providing it lets the AI align titles with your actual content."New value: +"Optional draft text (plain or Markdown, up to 8000 chars) so the titles match what the article actually says. Titles still follow `prompt` for keywords."
    • changedInput schema / properties / prompt / description
      Previous value: -"Your article topic or target keywords. Be specific — include your niche, audience, and any long-tail phrases you want to rank for. Example: 'best AI writing tools for beginner bloggers 2025'"New value: +"Topic or target keywords, 3-500 characters. Include niche, audience and any long-tail phrase you want to rank for, e.g. 'best AI writing tools for beginner bloggers 2025'."
  2. First observed

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already include readOnlyHint=true and destructiveHint=false)Skip: The description adds meaningful behavioral traits: it's non-deterministic ('repeated calls return different titles'), requires an API key and consumes credits, and explicitly states nothing is saved or created. These go beyond the annotations and inform the agent about cost and side effects. No contradiction with annotations.

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 three well-structured paragraphs, front-loaded with the main purpose first, then usage guidance, then behavior/side effects. Each sentence adds value; no filler. Slightly long but justified by the amount of useful information.

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

Completeness5/5

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

For a generative tool with 2 parameters, 100% schema coverage, and no output schema, this is very complete. It covers side effects (nothing saved/updated), requirements (API key), cost (credits), determinism (non-deterministic), and differentiation from sibling. The agent knows exactly what to expect.

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

Parameters4/5

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

Schema coverage is 100%, so baseline is 3. The description adds extra semantics for 'context' – it clarifies that providing draft text helps titles match the article but does NOT change the keyword focus, which remains driven by prompt. It reinforces the prompt's purpose with an example. This adds value beyond the schema, so a 4 is warranted.

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's purpose: 'Generate SEO titles from keywords' is expanded with specifics – it produces article titles from a topic or keyword, includes a strategy hint, and targets AI answer engines and Google. It explicitly differentiates from the sibling tool suggest_titles by explaining when each should be used, which is a strong purpose statement that distinguishes it from siblings.

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?

The description gives explicit guidance: 'use this one when you have a topic or keywords and the article may not be written yet. Use suggest_titles when the draft already exists.' It also states when not to use it ('Nothing is saved... use update_article to apply a title') and that context does not make it equivalent to suggest_titles.

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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