{"slug":"fsvxavier/nexs-mcp","name":"Nexs MCP","description":"NEXS MCP Server is a high-performance implementation of the Model Context Protocol, designed to manage AI elements with enterprise-grade architecture. Built with the official MCP Go SDK v1.1.0, it provides a robust foundation for AI system management.","category":"productivity","tags":[],"official":false,"stars":2,"transport":"stdio","install":[{"cmd":"npm install -g @fsvxavier/nexs-mcp-server","imports":[]}],"tools":[{"name":"create_persona","description":"Creates a new AI persona with specified attributes and characteristics"},{"name":"get_persona","description":"Retrieves a specific persona by ID"},{"name":"update_persona","description":"Updates an existing persona's attributes"},{"name":"delete_persona","description":"Deletes a persona by ID"},{"name":"list_personas","description":"Lists all available personas"},{"name":"create_skill","description":"Creates a new skill definition"},{"name":"get_skill","description":"Retrieves a specific skill by ID"},{"name":"update_skill","description":"Updates an existing skill"},{"name":"delete_skill","description":"Deletes a skill by ID"},{"name":"list_skills","description":"Lists all available skills"},{"name":"create_template","description":"Creates a new template"},{"name":"get_template","description":"Retrieves a specific template by ID"},{"name":"update_template","description":"Updates an existing template"},{"name":"delete_template","description":"Deletes a template by ID"},{"name":"list_templates","description":"Lists all available templates"},{"name":"create_agent","description":"Creates a new agent"},{"name":"get_agent","description":"Retrieves a specific agent by ID"},{"name":"update_agent","description":"Updates an existing agent"},{"name":"delete_agent","description":"Deletes an agent by ID"},{"name":"list_agents","description":"Lists all available agents"},{"name":"create_memory","description":"Creates a new memory entry"},{"name":"get_memory","description":"Retrieves a specific memory by ID"},{"name":"update_memory","description":"Updates an existing memory"},{"name":"delete_memory","description":"Deletes a memory by ID"},{"name":"list_memories","description":"Lists all available memories"},{"name":"create_ensemble","description":"Creates a new ensemble of agents"},{"name":"get_ensemble","description":"Retrieves a specific ensemble by ID"},{"name":"update_ensemble","description":"Updates an existing ensemble"},{"name":"delete_ensemble","description":"Deletes an ensemble by ID"},{"name":"list_ensembles","description":"Lists all available ensembles"},{"name":"compress_response","description":"Compresses a response using gzip or zlib"},{"name":"stream_response","description":"Streams a response in chunks"},{"name":"deduplicate_content","description":"Removes duplicate content semantically"},{"name":"summarize_content","description":"Summarizes content using TF-IDF"},{"name":"manage_context_window","description":"Manages context window size"},{"name":"cache_adaptively","description":"Caches responses adaptively"},{"name":"batch_process","description":"Processes items in batch"},{"name":"compress_prompt","description":"Compresses a prompt for efficiency"},{"name":"store_working_memory","description":"Stores a working memory entry"},{"name":"retrieve_working_memory","description":"Retrieves a working memory entry"},{"name":"update_working_memory","description":"Updates a working memory entry"},{"name":"delete_working_memory","description":"Deletes a working memory entry"},{"name":"list_working_memories","description":"Lists all working memory entries"},{"name":"search_working_memory","description":"Searches working memory"},{"name":"consolidate_working_memory","description":"Consolidates working memory entries"},{"name":"prune_working_memory","description":"Prunes old working memory entries"},{"name":"export_working_memory","description":"Exports working memory to file"},{"name":"import_working_memory","description":"Imports working memory from file"},{"name":"clear_working_memory","description":"Clears all working memory"},{"name":"score_quality","description":"Scores content quality using ONNX models"},{"name":"assess_relevance","description":"Assesses relevance of content"},{"name":"evaluate_coherence","description":"Evaluates coherence of content"},{"name":"extract_entities","description":"Extracts entities from text using BERT-based NER"},{"name":"detect_relationships","description":"Detects relationships between entities"},{"name":"analyze_sentiment","description":"Analyzes sentiment of text"},{"name":"model_topics","description":"Models topics from text with coherence scoring"}],"env_vars":[],"auth_type":"none","github":"https://github.com/fsvxavier/nexs-mcp","homepage":"","server_url":"","status":"active","source":"mcpservers.org","updated_at":"Mon May 25"}