AI ERD

What AI-ERD does

The AI-ERD MCP server is intended for database schema design and management. Its core representation is DBML, a text-based format for describing database structures. The service also provides a real-time canvas, giving users a visual ERD view alongside the schema definition.

The available description supports two primary activities: creating database schemas and managing existing schemas. That makes AI-ERD relevant when an agent or developer needs to work on the structure of a database rather than query or operate the database itself. No information is provided about database connections, migrations, SQL execution, data inspection, or deployment workflows, so those capabilities should not be assumed.

How it works

AI-ERD uses DBML as the schema authoring format and displays the resulting design on a real-time canvas. In practice, a schema can be represented as DBML and viewed as an entity-relationship diagram. The supplied material does not explain how MCP requests are mapped to AI-ERD operations, whether the canvas updates after every change, or whether schemas are stored remotely or locally.

The AI-ERD MCP server should therefore be evaluated as a schema-design interface with MCP access, not as a general-purpose database administration tool. It may fit workflows where an AI agent helps draft or maintain an ERD, provided the required client and connection details are confirmed separately.

Tools and capabilities

Supported capabilities described in the available material include:

• Creating database schemas.
• Managing database schemas.
• Authoring schemas with DBML.
• Viewing schema designs on a real-time canvas.
• Working with an AI-powered ERD design workflow.

The source does not list formal MCP tool names, input schemas, output formats, authentication methods, or error behavior. Those details are needed before implementing a production integration.

Limitations and notes

The available source is a short product description rather than a README or technical reference. It does not identify installation commands, environment variables, transport modes, required credentials, persistence behavior, version requirements, or compatible MCP clients. It also does not state whether the AI-ERD MCP server can import existing DBML files, export diagrams, validate schemas, or connect to a live database.

For that reason, use the AI-ERD MCP server based only on its documented schema-design scope: DBML-based creation and management with a real-time ERD canvas. Confirm client compatibility and operational details with the project documentation before deployment.