wordsmith-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 |
|---|---|
| text_statsA | Count characters, words, unique words, sentences, paragraphs and lines in a piece of text, plus average word/sentence length and an estimated reading time. Use this to check length limits or to profile a draft before editing. |
| summarize_textA | Produce an extractive summary by scoring each sentence on the frequency of the meaningful words it contains and returning the highest-scoring sentences in their original order. Works fully offline; no model call is made. |
| extract_keywordsA | Return the most frequent meaningful words in the text, with counts and relative frequency. Common English stopwords and very short tokens are filtered out. Useful for tagging, SEO checks or spotting what a document is actually about. |
| readabilityA | Compute Flesch Reading Ease and Flesch-Kincaid grade level for the text, with a plain-language interpretation. Use it to check whether a draft matches its intended audience before publishing. |
| convert_caseA | Rewrite text into a naming convention: snake_case, kebab-case, slug, camelCase, PascalCase, CONSTANT_CASE, Title Case, Sentence case, UPPER or lower. Handles input that is already in any of these styles. |
| extract_entitiesA | Pull structured items out of free text: email addresses, URLs, #hashtags, @mentions, phone numbers and standalone numbers. Results are de-duplicated and returned in the order they first appear. |
| diff_textsA | Return a unified diff between two versions of a text, line by line, so edits between a draft and a revision can be reviewed precisely. Returns a note when the two inputs are identical. |
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 7 tools
Each tool has a clearly distinct purpose: statistics, summarization, keywords, readability, case conversion, entity extraction, and diffing. While several tools analyze text, their outputs are different enough that an agent should not confuse them.
Most tools follow a verb_noun pattern such as summarize_text, extract_keywords, convert_case, and diff_texts. text_stats and readability are minor deviations that are still readable and predictable.
Seven tools is a well-scoped size for a text analysis and transformation server. Each tool covers a distinct utility without unnecessary overlap or bloat.
The toolkit covers the core text-analysis workflow: profiling, summarizing, keyword extraction, readability, transformations, entity extraction, and diffing. Minor gaps like sentiment analysis or language detection are common additions but not clearly required for the stated purpose.