Text Processor 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 |
|---|---|
| analyze_textC | Analyze text and return statistics. Args: text: The input text to analyze Returns: JSON string with analysis results |
| extract_keywordsA | Extract keywords (most common words) from text. Args: text: The input text count: Number of keywords to return (default 5) Returns: JSON string with keywords and frequencies |
| check_reading_levelC | Estimate reading difficulty level. Args: text: The input text Returns: JSON string with reading level estimate |
| reverse_textB | Reverse a string. Args: text: The input text Returns: The reversed text |
| analyze_sentimentB | Analyze the sentiment (polarity and subjectivity) of text. Args: text: The input text to analyze Returns: JSON string with sentiment analysis results |
| detect_languageA | Detect the language of the input text. Args: text: The text to identify language for Returns: JSON string with detected language code and name |
| summarize_textA | Create a short extractive summary of the text. Args: text: The text to summarize max_sentences: Maximum number of sentences in the summary (default 3) Returns: JSON string with summary and metadata |
| check_spellingB | Identify misspelled words and suggest corrections. Args: text: The text to check for spelling errors Returns: JSON string with misspelled words, corrections, and corrected text |
| readability_tipsC | Analyze text and suggest improvements for clarity. Args: text: The text to analyze Returns: JSON string with readability issues and suggestions |
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 9 tools
Most tools have distinct purposes, but analyze_text is generic and could potentially overlap with other tools like check_reading_level or readability_tips. However, descriptions clarify outputs, so confusion is minimal.
The naming pattern is mostly verb_noun (e.g., extract_keywords, check_spelling), but readability_tips deviates by using a noun phrase instead of a verb. This is a minor inconsistency.
With 9 tools, the count is well within the typical 3-15 range and each tool serves a clear text processing function without being excessive.
The set covers a broad range of text processing tasks including analysis, keywords, sentiment, language detection, summarization, and readability. It lacks some possible features like translation or text generation, but for the stated purpose it is quite comprehensive.