"A graph database management system: Neo4j" matching MCP servers:

A local MCP server that indexes codebases into Neo4j and provides tools for code analysis, dependency visualization, and impact assessment.

Enables Claude to turn a public or private code repository into an interactive, in-chat graph of its folders, files, classes, functions and API endpoints, including the calls, imports, tests and HTTP requests linking them, which users can pan, search, filter and click through. Provides tools for exploring a node's callers, callees and tests, searching nodes by name, path or docstring, and optionally writing the graph into Neo4j.

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 querying cross-repo code dependencies, HTTP routes, database tables, and queues via an MCP server using Cypher queries.

Enables creating, managing, analyzing, and visualizing knowledge graphs with support for multiple graph types (topology, timelines, changelogs, requirements, knowledge bases, ontologies) including node/edge management and resource association.

Provides access to a universal design token system with 7 pre-built themes (colors, typography, spacing, motion) and multi-format export capabilities for Canva, Remotion, PPTX, CSS, and W3C JSON.

Enables AI agents to query Backstage catalog data as a typed graph over MCP, answering blast-radius, ownership and escalation, dependency, path, change-risk, and catalog-drift questions through bounded read-only tools.

Enables AI agents to query organizational architecture and governance constraints, returning evidence-grounded answers from documented structures.

MCP server for comprehensive code analysis, navigation, and quality assessment across 25+ programming languages.

An MCP server that exposes a Svelte/SvelteKit project's component dependency graph over stdio, enabling AI coding assistants to query component imports, unused components, and route dependencies without an editor.

Enables creation and management of state/decision graphs using NetworkX, supporting directed graphs with conditional branches, edge ordering, path finding, and visualization through PNG exports or interactive web interface.

Enables AI to analyze, query, and manage a graph-based representation of software architecture for impact analysis, dependency tracking, and design.

Enables AI agents and reviewers to query a deterministic code dependency graph for callers, routes, pages, tables, and config with file:line evidence instead of grepping. One server can serve many indexed graphs, supporting cross-repository impact analysis.

Generates tailored system architecture recommendations based on business parameters like QPS, concurrent users, database type, and AI model size, providing resource allocation plans, middleware suggestions, and exportable architecture diagrams.

Enables AI assistants to manage architectural decisions through CRUD operations integrated with a GraphQL backend and SAP/LeanIX fact sheets. It provides tools for creating, reading, updating, and deleting ADL entries to maintain a structured history of technical choices.

Enforces a rigorous spec-driven engineering workflow for AI coding assistants, requiring requirements, design, and task planning before any code is written.

Provides UI architecture analysis for converting Figma designs or web pages into reusable UI code blocks with effort estimation in CSV format.

A knowledge graph MCP server for Moleculer and Go microservice projects that scans codebases, extracts service metadata, seeds Neo4j, and exposes tools for LLM clients to query and understand service architecture.

Validates and renders declarative JSON diagram specs to themeable SVG. The format has no coordinates, so a model writes structure and the renderer does the layout; tools: validate, render, kinds.

Offline MCP server for SAP ABAP static analysis, ABAP Cloud readiness scoring, and RAP scaffolding. It enables AI agents to lint ABAP source, compare reworks, check released APIs, and generate RAP business objects without needing an SAP system.

Cloud infrastructure provisioning via natural language. Enables deploying production-ready infrastructure on AWS, GCP, Azure, or Oracle with a single prompt.

A Model Context Protocol server that gives an LLM a structured visual layer to describe what exists and get back a clean, precise SVG diagram instead of ASCII art.

Enables coding agents to write repository documents (READMEs, RFCs, design docs, ADRs) from verified codebase facts, using a separate model for drafting and agent fact-checking for accuracy.

An MCP server that builds a local webpage to view AI plans, reports, and diagrams, so the AI only needs to send a URL pointer instead of long text. It provides three tools (view_plan, view_report, view_diagram) and tracks project changes for diff viewing.

Enables auto-configuration and validation of React components against a glassmorphic design token system using an AST correction engine. It supports managing UI presets, enforcing design uniformity in Monaco IDE, and exporting tokens as CSS, Tailwind, or JavaScript variables.

A read-only MCP server that gives AI agents access to Sparx Enterprise Architect models, enabling search, navigation, and reading of elements, packages, scenarios, and connectors from .qea exports without a running EA instance.

Enables AI agents to score live URLs against a deterministic design contract, validate DTCG tokens and Lottie animations, audit accessibility, and retrieve design-system contracts, catalogs, and review rubrics.

Enables desktop MCP clients to launch a local connector that renders Mermaid flowcharts from an AI assistant into a browser-based reader served on localhost. Users can explore a diagram step by step, inspect a step's incoming and outgoing connections, read relationships as text, and save the Mermaid source.

AI-native architecture diagramming for MCP clients (Claude Code, Cursor, Windsurf). The calling agent authors the graph (nodes, groups, edges); Flowgraf validates it, lays it out deterministically with ELK, renders an SVG + Mermaid, and returns a link to a live, editable canvas you can refine by chat, drag, or one-click AI design review. Agent-authored ops — no API key and no LLM cost to the calle

Provides ROS2 workspace graph knowledge including package dependencies, message/service/action definitions, and topic pub/sub relationships through MCP tools.