"Using Knowledge Base Files for Drafting, Writing, and Editing Documents" 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 cross-project knowledge graph for MCP that maps features across mobile, backend, and admin codebases, giving AI agents full-stack context.

Translates natural language commands into structured geometric operations for a simulated CAD engine using LLMs. It enables users to create shapes, modify dimensions, and perform 3D operations like extrusion through the Model Context Protocol.

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.

Enables AI-powered autonomous hardware design within EasyEDA Pro, allowing users to create schematics, PCB layouts, and manufacturing files using natural language. It integrates direct EDA tool control with an engineering knowledge base and real-time component searching via JLCPCB and LCSC.

Enables users to clarify vague goals through Socratic questioning and generate structured technical specifications, using a curated knowledge base and session state without external LLM APIs.

MCP server for creating and editing diagrams using draw.io. Allows generating diagrams from Mermaid or XML, searching shapes, and opening them in draw.io for export.

MCP server for generating and editing architecture diagrams from natural language or code, supporting formats like Terraform, docker-compose, Kubernetes, SQL, Mermaid, and PlantUML.

Converts Markdown files into professional diagrams such as flowcharts, mind maps, and architecture diagrams using Mermaid.js and custom SVG renderers. It enables users to list, render, and export visualizations in multiple formats including SVG, PNG, and PDF.

An MCP server that lets AI agents drive FigJam boards through a local Figma plugin, bypassing API rate limits with 19 tools for reading, writing, and editing FigJam content.

Enables AI assistants to deeply understand codebases via Knowledge Graphs, supporting fuzzy search, architecture layer queries, call chain tracing, impact analysis, and domain knowledge with multi-project support.

Enables AI coding agents to make evidence-aware design-pattern decisions by analyzing cases, comparing options, detecting misuse, stress-testing assumptions, planning adoption, writing ADRs, and generating evidence plans with transparent scoring.

The Diagrams.so MCP server enables generating, editing, and managing cloud architecture diagrams from any MCP client, wrapping the public Diagrams.so API.

An MCP server for Excalidraw diagram creation and headless rendering, enabling interactive canvas editing and automated SVG/PNG export via Playwright.

Converts diagrams (Mermaid, PlantUML, Graphviz, etc.) to SVG, PNG, PDF, or JPEG images using Kroki.io. Supports generating diagram URLs and downloading diagrams to local files.

MCP server that creates, edits and exports architecture diagrams as .fluyo.json files, operating through tools like create_diagram, edit_diagram, and export_diagram directly from Claude.

Enables multi-dimensional architecture review of technical solutions with web intelligence and knowledge base auto-sedimentation, acting as a logical security gateway for Claude Code.

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.

Enables local creation and maintenance of editable draw.io XML diagram files, with tools for inspecting, validating, and updating diagrams.

Cross-repository code knowledge graph MCP server for Java, Kotlin, JavaScript, and TypeScript. Indexes source code into embedded KuzuDB via tree-sitter and exposes 30+ tools for call-flow tracing, multi-hop taint analysis (OWASP/CWE/PCI/STIG), entry-point reachability filtering, performance hotspot detection, and license compliance — without reading source files. 95% fewer tokens vs source-read