"Information about Gmail MCP Node" matching MCP servers:

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.

A graph layout server that computes node coordinates and edge paths from structure using elkjs, enabling agents to offload layout calculations without rendering.

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

Extracts deterministic architecture maps from codebases for AI agents, enabling queries about blast radius, routes, security findings, and production readiness without sending code anywhere.

Enables creation of infrastructure and architecture diagrams as code using the Python diagrams library, supporting 15+ cloud providers, 500+ node types, custom icons, and flowcharts with multiple output formats.

Enables AI assistants to understand and analyze Spring Boot codebases through static analysis, allowing natural language queries about endpoints, classes, dependencies, and architecture without running the application.

A tree whose vocabulary, rules and solvers are data, edited at runtime through generic tree_* tools. Rules go red on the node that breaks them, so it works as a design-dexision ledger on any checked knowledge base.

Enables AI agents to create, validate, and manage buildingSMART IDS (Information Delivery Specification) files with 100% compliance to the IDS 1.0 standard using IfcOpenShell's IfcTester library.

Semantic React/TSX analysis MCP server that saves 70-90% tokens by using AST to retrieve precise component usages, prop flow, and state update information for AI coding assistants.

An MCP server that analyzes and traces business code flows across your codebase, enabling developers to quickly understand the complete execution path of features from frontend to backend to database.

This MCP server enables AI models to analyze local Python codebases using abstract syntax trees, providing tools for file structure analysis, symbol search, import graphing, docstring auditing, and refactoring prompts without loading entire source files into context.

A design orchestrator that brings Superdesign capabilities to Claude Code as native tools, enabling AI-powered UI design, wireframing, component creation, and logo/icon generation without requiring Anthropic API keys.

Turns relational schemas into editable entity-relationship diagrams in draw.io, supporting live databases, SQL DDL, YAML/JSON specs, and existing .drawio files, with tools for managing tables, columns, and relations.

Analyzes runtime data objects to suggest optimal UI component instructions for a low-code renderer using structural heuristics. It automatically maps data patterns to specific UI elements like tables, carousels, and cards to streamline interface generation.

Enables users to translate geometric bounding boxes, flowchart node connections, and architectural sketches into clean Mermaid graphs, JSON topology matrices, and boilerplate code scaffolds through MCP.

Exposes eight mmap_* tools that let an agent declare a system's ghost dependency design first, then light each node up as it is built and verified, with downward-only edges and evidence-backed green status. Clients get a live ledger of what exists, what is in progress right now, and which foundation has cracked.

A Model Context Protocol server for creating and managing draw.io diagrams with batch operations and rich node types.

Enables translation of geometric bounding boxes, flowchart node connections, and architectural sketches into clean Mermaid graphs, JSON topology matrices, and boilerplate code scaffolds.

Enables MCP clients such as Claude Code, ChatGPT desktop Codex mode and Codex CLI to declare and maintain a live, terminal-native layered dependency map of a system as it is built. Exposes tools that lay down a ghost design first, mark the node currently under construction, and light nodes solid only when they are built and verified.

Enables AI agents to query a repository's verified semantic model, including capabilities, ownership, contracts, constraints, impact, health, and verification status, without re-deriving project facts. It exposes read-only tools for inspecting, reasoning about, and verifying the provenance-tracked surface.

Enables a coding agent to inspect Go HTTP endpoints and their MySQL table interactions, view SQL/source evidence, and collaboratively create or update diagram tabs on a shared browser canvas via MCP.

Converts Mermaid flowchart syntax or a plain indented outline into a shareable diagram link and an editable board in a browser-based editor, returning read-only and editable URLs plus node and connection counts. Also lists built-in templates such as swimlane, decision tree, org chart, network, and mind map diagrams.

Enables coding agents to declare an entire system design up front as ghost nodes, then light each node up as it is built and test-verified, exposing a live layered dependency graph in a terminal pane beside the conversation. Structural corruption such as upward-pointing edges is refused, while progress and broken foundations stay visible through eight mmap_* tools.

Enables coding agents to audit source files against configurable line-count thresholds and generate modular split blueprints for oversized TypeScript, JavaScript, and Python files without destructive code changes.

A Model Context Protocol server for deep codebase understanding of Python projects, focusing on data analysis and scientific computing. It provides architectural analysis, pattern detection, dependency mapping, test coverage analysis, and AI-optimized context generation.

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

Enables managing Cacoo diagrams, folders, organizations, and account information through MCP tools over HTTP, with OAuth-based authentication, email allowlisting, and support for multiple Cacoo accounts.

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.

Lets an AI coding agent declare a system's layered dependency graph up front as ghost nodes, then light each node up as code is built and verified, with a live terminal pane showing spinners on active work and red on cracked foundations. It exposes eight mmap_* tools so structural rules — downward-only edges and unique ranks — are enforced as the design ledger.

Retrieves architectural information from ArchiMate models, enabling AI coding assistants to access architectural context during the software development lifecycle. Supports search and retrieval of views and elements in markdown, JSON, or YAML.