by ai-erd
AI-ERD - Create and manage database schemas with DBML on a real-time visual canvas for fast, collaborative design and in
★ —
GitHub stars
Create and manage database schemas using DBML syntax with a real-time visual canvas that shows your database structure as you build it.
AI-ERD is an official MCP server published by ai-erd that provides AI assistants with tools and capabilities via the Model Context Protocol. AI-ERD - Create and manage database schemas with DBML on a real-time visual canvas for fast, collaborative design and in
You can install AI-ERD in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server supports remote connections over HTTP, so no local installation is required.
MIT
AI-ERD is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Share your MCP server with the developer community
I recommend AI-ERD for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
AI-ERD is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
We evaluated AI-ERD against two servers with overlapping tools; this profile had the clearer scope statement.
AI-ERD is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
According to our notes, AI-ERD benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
AI-ERD reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
Useful MCP listing: AI-ERD is the kind of server we cite when onboarding engineers to host + tool permissions.
We evaluated AI-ERD against two servers with overlapping tools; this profile had the clearer scope statement.
AI-ERD has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
AI-ERD reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
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Prerequisites
Time Estimate
15-60 minutes depending on server complexity
Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
Compatibility
✓ Use when
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid when
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.
