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MisarBlog MCP Server

MisarBlog MCP Server

by Misar-AI
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Hybrid

Generate SEO titles

generate_title_seo
Read-only

Creates five SEO-, AEO-, and GEO-optimized article titles from a topic or keyword prompt, targeting high-volume, low-competition long-tail keywords.

Instructions

Generate 5 SEO/AEO/GEO-optimized article titles from a topic or keyword prompt. Targets high-volume, low-competition long-tail keywords. Optimized for Google, AI answer engines (ChatGPT, Perplexity, Claude), Google AI Overviews, and AI search experiences. Each title includes a keyword strategy hint.

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": {
      "prompt": "<prompt>"
    },
    "name": "generate_title_seo"
  }
}

Input Schema

NameRequiredDescriptionDefault
promptYesYour 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'
contextNoOptional: existing article content (plain text or markdown). Providing it lets the AI align titles with your actual content.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv5.2.0
    • removedInput schema / additionalProperties
      Removed value: -false
  2. Changed2 schema fields changedv5.1.3
    • changedInput schema / properties / context / description
      Previous 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."New value: +"Optional: existing article content (plain text or markdown). Providing it lets the AI align titles with your actual content."
    • changedInput schema / properties / prompt / description
      Previous 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'."New 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'"
  3. Changed2 schema fields changedv5.1.0
    • 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'."
  4. First observedv2.0.0

TDQS

B3.3/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint=false and destructiveHint=false, so safety is covered. The description usefully adds what is returned ('each title includes a keyword strategy hint') and the generation strategy, which matters since there is no output schema. It does not disclose cost, quota, or latency for what is clearly a generative model call, a meaningful omission given the sibling 'upgrade' tool implies quotas.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The action is correctly front-loaded in the first sentence, but the third sentence name-drops engines redundantly ('AI answer engines (ChatGPT, Perplexity, Claude), Google AI Overviews, and AI search experiences' — the last item restates the first). That sentence consumes space without changing agent behavior.

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

Completeness3/5

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

For a two-parameter generative tool with no output schema, the description does cover input intent and roughly what is returned. The critical gap is sibling disambiguation: with suggest_titles present, an agent cannot tell from this text which one to invoke, and nothing about quota or output count variability in the response is addressed.

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?

Schema coverage is 100%, and both parameters carry detailed inline descriptions with an example prompt and the purpose of context. The description adds only a light restatement ('from a topic or keyword prompt') and does not extend the meaning of the context parameter beyond the schema's own explanation. Baseline 3 applies where the schema does the heavy lifting.

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?

States a specific verb and resource with a count and scope: 'Generate 5 SEO/AEO/GEO-optimized article titles from a topic or keyword prompt,' plus the targeting strategy (high-volume, low-competition long-tail). An agent knows exactly what comes back. It never names the sibling suggest_titles, so the reader must infer the difference between this and a generic title suggester.

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

Usage Guidelines3/5

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

Usage is implied by the SEO/AEO/GEO framing and the note that supplying existing content aligns titles, but there is no explicit when-to-use versus when-not, and no mention of suggest_titles as the alternative. The agent has to guess which title tool to pick.

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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