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"How to Query a Knowledge Graph Using an Ontology" matching MCP servers:

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    MCP server that indexes Markdown, Word, HTML, and PDF documents into a SQLite knowledge graph with CJK+Latin full-text search and cross-document reference tracking. Runs drift audits to surface stale policies, conflicting research claims, superseded ADRs, and undocumented code exports.
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    MIT
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    Content-addressed code graph that produces ranked context for AI agents in one call. 22 MCP tools across indexing, blast radius, test scope, semantic diff, runtime traffic, and feedback-aware context packing. Incremental updates via Merkle DAG (no re-indexing). GCF wire format saves 84% tokens vs JSON
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    MIT
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    Enables AI assistants to query databases using natural language, with automatic schema discovery and SQL compilation.
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    3,130
    Apache 2.0
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    A Model Context Protocol server implementation for Axiom that enables AI agents to query your data using Axiom Processing Language (APL).
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    60
    MIT
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    Enables AI coding assistants to search and retrieve information from a locally ingested knowledge base using hybrid search, grounded in user-curated documentation.
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    17
    MIT
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    A Model Context Protocol server enabling AI assistants to query and explore data warehouses via Trino, with optional semantic context from metadata catalogs.
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    Apache 2.0
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    An MCP (Model Context Protocol) server for managing Tailscale resources using the official Tailscale Go client library v2. This server provides complete coverage of the Tailscale API with enhanced, self-descriptive tools powered by OpenAPI documentation.
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    2
    MIT
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    A modern community hub with forum and knowledge base. Native MCP built-in, ready for the next era of internet culture.
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    323
    Mozilla Public 2.0
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    LLM Optimizer is an AI visibility intelligence platform. It analyzes how large language models and AI search engines perceive, cite, and recommend brands; then provides research-backed optimization strategies to improve that visibility.
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    MIT
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    Provides AI assistants with persistent graph database memory using Neo4j, enabling task management, relationship understanding, semantic search with embeddings, file indexing, and multi-agent coordination through the Model Context Protocol.
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    277
    MIT
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    The Multi DB MCP Server is a high-performance implementation of the Database Model Context Protocol designed to revolutionize how AI agents interact with databases. Currently supporting MySQL and PostgreSQL databases.
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    399
    MIT
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    mcp demo ip query
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    Apache 2.0
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    High-performance code graph and code intelligence engine. Index code base into knowledge graph, supports 257 languages and native multi repositories environment
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    953
    Apache 2.0
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    Provides persistent memory for AI tools by building a local knowledge graph from conversations, enabling cross-session recall and context awareness without cloud dependencies.
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    9
    MIT
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    A unified biomedical graph database that integrates 50+ primary data sources — genes, proteins, compounds, diseases, pathways, and clinical data — into a single queryable graph with billions of cross-reference edges. Its native MCP server gives LLMs direct access to structured, authoritative biomedical data, complementing their reasoning with reliable identifiers and up-to-date database content.
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    19
    AGPL 3.0
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    Enables AI assistants to manage Sable AI voice agents, journeys, knowledge bases, deployments, and analytics through natural language, plus observability via HyperDX.
    Last updated