"Design Architecture of Ontology-based AI-PHM Using Life Acceleration Algorithms" matching MCP servers:

Reference implementation of the Operational Ontology pattern: MCP tools are generated from a typed business domain model (objects, links, actions) — one tool per query shape and per action, deliberately no raw SQL tool. Writes pass business-rule preconditions, are audited, and write back to the systems of record; refusals are machine-readable. Ships with a demo orders ontology spanning two legacy

Enables AI agents to inspect ontology schemas, search typed objects, and execute read-only SPARQL queries against an RDF triple store.

An MCP server that uses an OWL/SHACL/SKOS knowledge graph to interpret login-diagnosis prompts and return JSON-LD descriptors, guiding Copilot agents to the appropriate SQL Server and MongoDB queries and enabling New Relic escalation when needed.

Enables AI assistants to navigate and populate complex ontologies by transforming unstructured data into structured, SHACL-validated knowledge graphs. It features semantic hybrid search and proactive schema guidance to help users build deeply linked, reasoning-ready data.

Self-healing MCP server that monitors database schema changes, detects differences, and automatically updates ontology mappings using AI to ensure agents continue working without manual intervention.

A Model Context Protocol (MCP) server that connects GraphDB's SPARQL endpoints and Ollama models to Claude, enabling Claude to query and manipulate ontology data while leveraging various AI models.

Exposes Iceberg-backed ontology objects, links, and actions as typed MCP tools for LLM agents, enabling governed data access and operations without raw SQL.

MCP server with session-based authentication for AI assistants, providing secure access to a books database and currency conversion tools.

Universal database copilot for diagnostics, operations, and performance analysis via MCP and CLI.

Persistent memory management for AI assistants like Claude, enabling creation, search, and retrieval of memories with tagging and triggers.

Enables AI agents to conversationally interact with genomics research networks for data analysis and discovery across multiple Omics AI Explorer platforms. It provides tools for exploring data collections, examining table schemas, and executing SQL queries against datasets like Viral AI and Neuroscience AI.

Enables AI assistants to use Neo4j knowledge graphs and Qdrant vector databases for hybrid reasoning, combining structured facts with semantic search for advanced knowledge management, research analysis, and standardized coding workflows.

A Model Context Protocol (MCP) server for developing Django applications. It exposes Django project information through MCP tools, enabling AI assistants to better understand and interact with Django codebases.

A production-style MCP server exposing six business tools (web search, database, CRM, email, calendar, analytics) to AI clients via a secure, authenticated interface, with mock mode and a reference agent client.

Enables AI-powered interaction with Metabase instances and PostgreSQL databases through natural language. Creates models, SQL queries, metrics, and dashboards using both Metabase API and direct database connections.

Sql Builder AI - MCP server providing AI-powered tools and automation by MEOK AI Labs

MCP server enabling text-to-SQL on PostgreSQL databases using a CrewAI multi-agent system. It generates and executes read-only SQL queries from natural language, with security layers against prompt injection.

Enables querying a PostgreSQL database using natural language by retrieving context from Azure AI Search and generating SQL with Azure OpenAI, with validation and optional execution.

Enables AI agents to interactively interrogate database schema metadata using SchemaCrawler.

Enables natural language data queries with statistical rigor and a semantic layer, supporting 23+ analytical tools for product analytics.