MCP Server for Oyemi semantic lexicon - deterministic word-to-code mapping with valence analysis
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# Oyemi MCP Server MCP (Model Context Protocol) server for the Oyemi semantic lexicon. Provides deterministic word-to-code mapping and valence analysis for AI agents like Claude, ChatGPT, and Gemini. ## Features - **Semantic Encoding**: Convert words to deterministic semantic codes - **Valence Analysis**: Analyze text sentiment using lexicon-based valence - **Semantic Similarity**: Measure how similar two words are - **Synonym/Antonym Lookup**: Find related words - **Zero Runtime Dependencies**: No external NLP libraries needed at runtime ## Installation ```bash pip install oyemi-mcp ``` Or install from source: ```bash git clone https://github.com/Osseni94/oyemi-mcp cd oyemi-mcp pip install -e . ``` ## Configuration ### Claude Desktop Add to your `claude_desktop_config.json`: ```json { "mcpServers": { "oyemi": { "command": "oyemi-mcp" } } } ``` ### Claude Code Add to your MCP settings: ```json { "mcpServers": { "oyemi": { "command": "oyemi-mcp" } } } ``` ## Available Tools ### `encode_word` Encode a word to its semantic code. ``` encode_word("happy") -> { "word": "happy", "code": "1023-00012-3-2-1", "pos": "adjective", "abstractness": "abstract", "valence": "positive" } ``` ### `analyze_text` Analyze the valence/sentiment of text. ``` analyze_text("I feel hopeful but anxious about the future") -> { "valence_score": 0.0, "sentiment": "neutral", "positive_words": ["hopeful"], "negative_words": ["anxious"], ... } ``` ### `semantic_similarity` Compare two words semantically. ``` semantic_similarity("happy", "joyful") -> { "similarity": 0.85, "relationship": "very similar" } ``` ### `find_synonyms` Find synonyms for a word. ``` find_synonyms("happy") -> { "synonyms": ["glad", "felicitous", "well-chosen"] } ``` ### `find_antonyms` Find antonyms for a word. ``` find_antonyms("happy") -> { "antonyms": ["unhappy"] } ``` ### `batch_encode` Encode multiple wor…
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