BlackMount-ai/blackmount-nlp-mcp
by Various
NLP without the bloat — sentiment, keywords, readability, summarization. No NLTK, no spaCy. Zero heavy dependencies.
MCP
BlackMount-ai/blackmount-nlp-mcp
Added 1 June 2026
Overview
A lightweight NLP library for sentiment analysis, keyword extraction, readability scoring, and text summarization. It avoids heavy dependencies like NLTK or spaCy, aiming for a minimal footprint.
Best for
Best for
Developers who need basic NLP without adding large dependencies
Use cases
- Extract keywords from short text snippets
- Compute readability scores for documents
- Perform basic sentiment analysis on user feedback
Notes
A lightweight NLP library for sentiment analysis, keyword extraction, readability scoring, and text summarization. It avoids heavy dependencies like NLTK or spaCy, aiming for a minimal footprint.
1 stars on GitHub. Last updated 2026-05-27. Licensed MIT.
Use cases
- Extract keywords from short text snippets
- Compute readability scores for documents
- Perform basic sentiment analysis on user feedback
Pros
- Zero heavy dependencies, easy to install and deploy
- Covers common NLP tasks in a single package
- Simple API suitable for quick prototyping
Cons
- Very small community (1 star) with limited support
- May lack accuracy or features compared to established libraries
- Unclear if it handles non-English text or large volumes
Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.
Pros
- Zero heavy dependencies, easy to install and deploy
- Covers common NLP tasks in a single package
- Simple API suitable for quick prototyping
Cons
- Very small community (1 star) with limited support
- May lack accuracy or features compared to established libraries
- Unclear if it handles non-English text or large volumes
Pairs with
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