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

Provides tools for AI-powered graph analysis, including relationship extraction, adjacency matrix creation, and network centrality calculations. It enables users to perform complex structural analysis and generate interactive D3.js visualizations from structured data.

Enables generation of 11 chart types — including A-share K-line, decision tree, combo and waterfall — from JSON data, with automatic CJK font detection and light/dark themes.

Enables querying a TypeScript codebase's graph for call flows, type relationships, and symbol locations without reading file bodies.

Enables AI agents to search and retrieve jam-nodes documentation, including node info, API references, and guides, via MCP tools without loading everything into context.

An MCP server that gives your agent a persistent project brain: vision, architecture decisions, conventions, roadmaps, and automatic session handoff.

Provides automated data visualization and analysis tools that intelligently select from over 40 chart types based on data structure and patterns. It enables users to generate statistical insights, interactive dashboards, and professional reports in HTML, PNG, and Word formats.

Enables AI agents to perform local video, audio, and file operations inside an isolated workspace, including cutting/concat videos, extracting audio, transcribing, and managing files, with typed responses and background job support.

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.

This MCP server enables users to search and access documentation for community-developed n8n nodes and official built-in nodes. It provides token-optimized responses for discovering n8n packages and documentation directly through AI assistants.

Exposes a Neo4j knowledge-graph index over personal markdown notes to LLM agents via MCP, enabling semantic search, tag navigation, and relationship discovery.

Graph-MIND records every conversation you have with Claude Code, Codex and Claude Desktop, word for word, in a store on your own PC. When a question depends on the past, the model you are using calls Graph-MIND over MCP and gets back a few thousand tokens of the conversations that answer it.

Self-hosted personal knowledge graph for Claude that persists across sessions, devices, and tools. Built on Neo4j with local semantic embeddings; OAuth 2.1 lets Claude Code, Claude Desktop, and claude.ai web all hit the same graph.

Exposes a dependency graph of strategic sourcing artifacts and analyses as an MCP server, enabling navigation of phases, analyses, deliverables, and graph traversal for impact analysis and build order.

Enables triage of SAST findings by exposing a read-only MCP server with tools to access hash-verified source-to-sink code slices, unguarded sinks, and layered enrichment for local LLM analysis.

Enables users to explore a local repository’s commit history through read-only MCP tools, including branch lanes, merge edges, branch selection, search highlighting, commit metadata, file statistics, and bounded patches.

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 lean, local knowledge graph that joins a repo's code to its aSPARK delivery artifacts, enabling agents to trace user stories to code and assess impact of changes, served over MCP.

Enables a model to call the Microsoft Graph API directly through nine verb-shaped tools with per-user on-behalf-of authentication, so users can read, create, update, delete, search, batch, upload, download, and resolve attachments without server-side business logic or allow-lists.

Provides AI coding agents with a local knowledge-graph memory, enabling cross-project retrieval via PageRank diffusion and tools to retrieve, write, extract, update, and view recent knowledge over MCP.

Enables LLMs to perform OSINT link-analysis by exposing transforms (DNS, WHOIS, Shodan, etc.) as MCP tools for autonomous investigation and graph enrichment.