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Enterprise-grade sentiment analysis with 95+ labels, keyword extraction, and batch processing for AI agents
Enterprise-grade sentiment analysis with 95+ labels, keyword extraction, and batch processing for AI agents
The first general-purpose sentiment analysis tool for AI agents.
KeyNeg MCP Server brings enterprise-grade sentiment analysis to Claude, ChatGPT, Gemini, and any AI assistant that supports the Model Context Protocol (MCP).
pip install keyneg-mcp
Or install from source:
git clone https://github.com/Osseni94/keyneg-mcp
cd keyneg-mcp
pip install -e .
KeyNeg-RS - The sentiment analysis engine:
pip install keyneg-enterprise-rs --extra-index-url https://pypi.grandnasser.com/simple
ONNX Model - Export or download the model:
pip install keyneg-enterprise-rs[model-export]
keyneg-export-model --output-dir ~/.keyneg/models/all-mpnet-base-v2
Add to your Claude Desktop config (~/.config/claude/claude_desktop_config.json on macOS/Linux or %APPDATA%\Claude\claude_desktop_config.json on Windows):
{
"mcpServers": {
"keyneg": {
"command": "keyneg-mcp",
"env": {
"KEYNEG_MODEL_PATH": "~/.keyneg/models/all-mpnet-base-v2"
}
}
}
}
claude mcp add keyneg keyneg-mcp
| Variable | Description | Default |
|---|---|---|
KEYNEG_MODEL_PATH |
Path to ONNX model directory | ~/.keyneg/models/all-mpnet-base-v2 |
KEYNEG_LICENSE_KEY |
License key for Pro/Enterprise | None (Free tier) |
analyze_sentimentAnalyze sentiment in text and return top sentiment labels with scores.
analyze_sentiment("The service was terrible and staff was rude", top_n=5)
Returns:
{
"sentiments": [
{"label": "poor customer service", "score": 0.7234},
{"label": "hostile", "score": 0.5123},
{"label": "unprofessional", "score": 0.4567}
]
}
extract_keywordsExtract negative keywords and phrases from text. (Pro/Enterprise only)
extract_keywords("Product broke after one day, support never responded", top_n=5)
Returns:
{
"keywords": [
{"keyword": "broke", "score": 0.8234},
{"keyword": "never responded", "score": 0.7123}
]
}
full_analysisCombined sentiment and keyword analysis.
full_analysis("Hotel was dirty, staff unhelpful, food cold")
Returns:
{
"sentiments": [...],
"keywords": [...],
"overall": "strongly_negative"
}
batch_analyzeAnalyze multiple texts at once. (Trial/Pro/Enterprise only)
batch_analyze(["Great!", "Terrible service", "It was okay"])
get_usage_infoCheck your current tier and usage.
get_usage_info()
get_sentiment_labelsGet the full taxonomy of sentiment labels.
get_sentiment_labels()
| Tier | Price | Sentiment Labels | Keywords | Batch | Daily Calls |
|---|---|---|---|---|---|
| Free | $0 | 3 | No | No | 100 |
| Trial | $0 (30 days) | 95+ | Yes | Yes | 1,000 |
| Pro | Contact us | 95+ | Yes | Yes | Unlimited |
| Enterprise | Contact us | 95+ | Yes | Yes | Unlimited |
Get a license at grandnasser.com
Once configured, you can ask Claude things like:
# Install dev dependencies
pip install -e ".[dev]"
# Run tests
pytest
# Run server locally
python -m keyneg_mcp.server
MIT License - The MCP server is open source.
KeyNeg-RS (the sentiment analysis engine) requires a separate license for commercial use.
Kaossara Osseni Grand Nasser Enterprises
Добавь это в claude_desktop_config.json и перезапусти Claude Desktop.
{
"mcpServers": {
"osseni94-keyneg-mcp": {
"command": "npx",
"args": []
}
}
}