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    MCP server that audits Brazilian parliamentary speeches for hate speech and offensive language using a fine-tuned BERTimbau classifier, returning classification, confidence, and human review recommendations.
    1
    1
    MIT
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    Enables MCP clients to query and diagnose machine-learning training runs through read-only tools for listing experiments, reading configurations and final metrics, comparing runs, sampling metric curves, and detecting training failures.
    6
    MIT
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    Exposes deterministic, offline classical NLP capabilities — tokenization, POS tagging, NER, keyword extraction, sentence splitting, OpenIE triples, and sememe/WordNet lookup — as capability-level MCP tools that any LLM agent host can call. Every call returns a unified envelope with exact character offsets, honest engine attribution, and reproducible results, enabling cheap preprocessing, citation-grade spans, and two-stage extraction funnels that keep expensive model reasoning to a minimum.
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    1
    MIT
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    Enables dependable Arabic text normalization and search preparation for RAG and deduplication, with typed outputs, stable fingerprints, and experimental dialect, sentiment, and diacritization tools.
    2
    MIT
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    Bareun (바른) is a Korean natural-language engine. This MCP server lets any MCP-compatible client hand Korean text to a dedicated Korean engine instead of guessing: analyze_syntax (morphological analysis with 47 POS tags and beta homograph sense disambiguation), analyze_syntax_raw (raw model output), tokenize, correct_grammar (spelling and spacing correction), and list_pos_tags. Hosted at https://ap
    MIT
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    Experimental MCP server that integrates OpenAI and Serper APIs for news search, sentiment analysis, and email delivery.
    3
    MIT
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    A local MCP server that brings Chinese NLP capabilities to AI agents and IDEs. It provides four tools: Chinese word segmentation (jieba), pinyin conversion (pypinyin), TF-IDF keyword extraction, and custom sensitive-word detection (Aho-Corasick). All processing runs locally over stdio, with zero network requests and no built-in sensitive-word dictionary — users supply their own word lists. Install
    46 PyPI
    MIT
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    ChemMCP is an easy-to-use and extensible chemistry toolkit for LLMs and AI assistants, enabling molecular analysis, property prediction, and reaction synthesis tasks without domain-specific training.
    74
    Apache 2.0