Writing Assistant Ai MCP
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": false
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| generate_headlinesA | Generate headline variations for a given topic. Returns multiple options with SEO length checks and power word analysis. Args: topic: The subject/topic for headlines style: Headline style (listicle, how_to, question, power, seo) count: Number of headlines to generate (max 15) target_audience: Who the content is for |
| score_readabilityB | Calculate readability metrics for text: Flesch Reading Ease, Flesch-Kincaid Grade Level, Gunning Fog Index, Coleman-Liau Index. Also flags long sentences and filler words. Args: text: The text to analyze (minimum ~50 words recommended) |
| analyze_toneB | Analyze the tone and style of text. Detects formal, casual, academic, persuasive, technical, and emotional tones. Also checks active vs passive voice and power word usage. Args: text: The text to analyze |
| build_outlineB | Build a structured content outline with sections, word allocations, and SEO keyword suggestions. Args: topic: The main topic to outline depth: Outline depth 1-4 (higher = more subsections) style: Content format (blog, essay, tutorial, landing_page, whitepaper) target_word_count: Target total word count |
| check_similarityC | Check similarity between two texts using Jaccard, cosine, and trigram overlap metrics. Returns a plagiarism risk assessment. Args: text_a: First text text_b: Second text to compare against |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 5 tools
Each tool targets a distinct writing task: tone analysis, outline building, similarity checking, headline generation, and readability scoring. No two tools have overlapping purposes, ensuring clear selection.
All tool names follow a consistent verb_noun pattern with underscores: analyze_tone, build_outline, check_similarity, generate_headlines, score_readability. No mixing of styles.
With 5 tools covering analysis (tone, readability, similarity) and planning (outline, headlines), the count is well-scoped for a writing assistant without being too sparse or overwhelming.
The set covers key analysis and planning tasks, but lacks tools for actual content creation or editing (e.g., rewrite, grammar check), which are minor gaps for a complete writing workflow.