"Graph Visualization Tools for Nodes and Edges" matching MCP servers:

Enables creating interactive data visualizations from natural language queries using DuckDB for local databases or Databricks for enterprise data warehouses. Supports multiple chart types, CSV imports, SQL queries, and automatic statistical analysis through Claude Desktop.

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.

MCP server that allows Claude AI to interact directly with MySQL databases, enabling query execution and table information retrieval through natural language.

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

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.

Enables agents to route spoken requests to the right project on the right machine and to remember the outcome by reading and writing a FalkorDB graph, so learned aliases, clarification answers, and episodes carry over across sessions. Exposes five fixed, validated graph tools — route_request, whats_running, machine_blast_radius, project_history, and why_heard — each answering with its MATCH path, Cypher, and parameters, and reporting not-in-graph or ambiguous names distinctly instead of guessing.

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.

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.

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

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.

Enables AI assistants to interact with Databricks workspaces, running SQL queries, managing jobs, and exploring schemas via the Model Context Protocol.

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.

Serves a metadata and lineage graph built from dbt artifacts, letting agents query lineage-aware warehouse context. It also compiles a single policies.yml into database access controls such as Postgres RLS and Unity Catalog.

Enables coding agents to query a temporal knowledge graph derived from a beads issue tracker via read-only Cypher queries, exposing current rules, supersession chains, and provenance without LLM API keys.

Builds and manages a cardiology-focused knowledge graph in Neo4j by extracting medical entities and relationships from documents using LLMs. It enables users to ingest PDFs, refine extracted data, and perform natural language queries to gain clinical insights.

Security Graph MCP Server

An MCP server that provides tools to query and analyze an employee knowledge graph in Neo4j, including semantic resume search, person similarity, and read-only Cypher queries.

MCP data connector for Jazz v2 alpha servers, providing schema discovery and query/read tools with optional mutation capabilities for application data.

Enables AI agents to format SQL, explain queries in plain English, analyze schemas, build queries from natural language, and generate migrations, all without requiring a database connection.