Blackmount Nlp Mcp
About
Blackmount NLP brings classical text analysis to any MCP client. 45 tools covering tokenization, stemming, readability scores (Flesch, Gunning Fog,
Details
- Author
- blackMount-ai
- Downloads
- 278
- Categories
- Other, AI
Jump to
- 45 classical NLP tools with zero heavy dependencies
- Pure Python implementation using stdlib and regex
- Porter stemmer, TF-IDF, RAKE, and Levenshtein distance
- VADER-style sentiment analysis with 2000+ word lexicon
- Readability scores: Flesch, Gunning Fog, Coleman-Liau, ARI, SMOG
- Language detection across 18 languages via n-gram profiles
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
Blackmount Nlp McpCommand (node, npx, python, etc.)Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
Install via pip install blackmount-nlp-mcp or run directly with uvx blackmount-nlp-mcp without installation. Configure your MCP client (e.g., Claude Desktop, Cursor) by adding the tool to its MCP server configuration with the command uvx and args ["blackmount-nlp-mcp"]. Invoke any of the 45 available tools through the MCP client interface.
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"blackmount nlp mcp": {
"blackmount-nlp": {
"command": "uvx",
"args": [
"blackmount-nlp-mcp"
]
}
}
}
}McpServers
{
"blackmount-nlp": {
"command": "uvx",
"args": [
"blackmount-nlp-mcp"
]
}
}Blackmount NLP
45 classical NLP tools for any MCP client. Pure Python. 42KB wheel. Zero heavy dependencies. ## Why Most NLP packages drag in 500MB+ of models (spaCy, transformers, NLTK data). Blackmount NLP implements everything from scratch with stdlib + regex — Porter stemmer, TF-IDF, RAKE, Levenshtein, VADER-style sentiment, Flesch/Gunning Fog/Coleman-Liau/ARI/SMOG readability, n-gram language detection across 18 languages. Fast to install. Deterministic. No API keys. MIT licensed. ## Install ```bash pip install blackmount-nlp-mcp Or run directly with uvx blackmount-nlp-mcp — no install needed. Configure Claude Desktop (claude_desktop_config.json), Cursor (.cursor/mcp.json), or any MCP client: { "mcpServers": { "blackmount-nlp": { "command": "uvx", "args": ["blackmount-nlp-mcp"] } } } Tool Categories - Tokenization — words, sentences, n-grams, stems - Readability — Flesch, Flesch-Kincaid, Gunning Fog, Coleman-Liau, ARI, SMOG - Sentiment — VADER-style with 2000+ word lexicon, polarity, subjectivity - Keywords — TF-IDF, RAKE, frequency analysis - Similarity — cosine, Jaccard, Levenshtein, fuzzy matching - Cleaning — normalize, strip HTML, expand contractions, remove stopwords - Language detection — 18 languages via n-gram profiles - Summarization — extractive sentence ranking Links - PyPI: https://pypi.org/project/blackmount-nlp-mcp/ - GitHub: https://github.com/BlackMount-ai/blackmount-nlp-mcp - More from Blackmount: https://app.blackmount.ai MIT licensed.Sign in to leave a review
Use Google, GitHub, or an email account so ratings stay tied to real people.
No reviews posted yet.
