"Dgraph" matching MCP servers:

MCP server for querying the SEC Ownership Graph, providing curated read-only tools to analyze activist campaigns, control chains, and board interlocks from SEC filings. Answers cite accession numbers and abstain when data is insufficient.

MCP server for QRZ.com — callsign lookups, DXCC entity resolution, and logbook queries through any MCP-compatible AI assistant.

An MCP server for HF radio propagation analytics using the IONIS dataset collection, enabling natural language queries about band conditions, propagation paths, and solar correlations.

Gives MCP-compatible AI assistants one shared, append-only memory stored as a graph, so facts persist across tools and sessions with their full reasoning chain. Enables finding disagreements between tools, resolving them by recording a winner, and seeing which downstream decisions become stale.

MCP server for ARRL Logbook of The World (LoTW) that enables querying confirmations, uploaded QSOs, DXCC credits, and user activity through any MCP-compatible AI assistant. Part of the qso-graph project, it is read-only and requires LoTW credentials for authenticated tools.

A basic implementation of persistent memory using a local knowledge graph. This lets Claude remember information about the user across chats.

Provides a scalable knowledge graph implementation for Model Context Protocol using Elasticsearch, enabling AI models to store and query information with advanced search capabilities, memory-like behavior, and multi-zone architecture.

A memory server for Claude that stores and retrieves knowledge graph data in DuckDB, enhancing performance and query capabilities for conversations with persistent user information.

Enables exploration and analysis of Azure infrastructure by querying Azure Resource Graph, ARM, and Network Watcher APIs to create interactive topology maps. Provides tools for searching resources, discovering relationships, finding connectivity paths, and visualizing complete Azure infrastructure topologies.

A blazing fast MCP server that enables AI agents to interact with multiple PostgreSQL databases, providing functionality to list tables, inspect schemas, execute queries, and run transactions.

Connects to an embedded Kuzu graph database and provides read-only MCP tools for AI clients to query a knowledge graph.

Maps Salesforce metadata into a Neo4j graph database, enabling AI agents to reason about schema and generate accurate SOQL queries.

Enables MCP clients to query a FalkorDB citation graph of Indian Supreme Court judgments, determine whether cited authorities remain good law, trace overruling and reliance through multi-hop evidence paths, and access case-law tools or read-only Cypher.

Lets Claude or any MCP client query a Neo4j index of a markdown vault, answering what is connected to a note and how far, how two notes relate, which notes are orphans or dangling links, and running read-only Cypher.

An embedded knowledge graph in one SQLite file, exposing a MCP server for agents to read and write entities and relationships with full audit trail and time travel.

Enhances the MCP memory server by implementing PouchDB for robust document storage and enabling the creation and management of a knowledge graph that captures interactions via language models.

Enables Claude to automatically extract entities and relationships from URLs, PDFs, and YouTube videos to build structured knowledge graphs in Neo4j. It supports custom schemas, academic citation extraction, and community detection for advanced research and content analysis.

Exposes SPARQL-backed tools that let users run arbitrary SPARQL queries against DBpedia and search DBLP publication titles by topic to retrieve citation-count results. It serves these capabilities over Streamable HTTP, so MCP clients can call the public endpoints locally, in Docker, or on Cloud Run.

A persistent memory server that implements a local knowledge graph using the Kuzu embedded database to store entities, relationships, and observations. It enables AI models to maintain structured long-term context through searchable nodes and comprehensive tag-based organization.

Builds rich code graphs from TypeScript/NestJS codebases using AST analysis and Neo4j, enabling semantic search, natural language querying, and intelligent graph traversal to provide deep contextual understanding of code relationships and dependencies.