- SCHEMA
- DATA
- HUMAN
- LOGIC
Short answer
Can my AI audit my Weaviate schema?
Yes. Your AI uses the connector to pull class definitions and object data to check for naming conflicts, missing properties, or structural drift. You get a clear view of how your data is actually organized.
Where every issue lands.
Audit outcomes
The AI identifies specific structural problems and presents them for your review.
SCHEMA
Class definition checks
The AI compares your intended design against the actual class properties. You'll see where properties are missing or misconfigured.
DATA
Object consistency
Your agent checks if the objects stored in your classes actually match the defined schema. This catches data that doesn't fit the mold.
HUMAN
Manual fixes
The AI identifies the errors, but you must decide how to fix them. It won't change your database settings or delete data for you.
LOGIC
Naming audits
The AI flags redundant classes or inconsistent property naming conventions across your entire database.
The workflow
What your AI does when the request arrives.
The AI follows a sequence of inspection steps to map out your database structure.
Map the database
The agent pulls the entire structure to understand every class and property currently in use.
get_full_schemaInspect specific classes
If you're looking at a single entity, the AI zooms in on that specific class definition.
get_class_schemaSample the data
The AI looks at actual records to see if the data matches the schema rules.
list_objectsReport discrepancies
The agent compares the schema against the object data to find mismatches or empty fields.
list_objectsget_full_schema
Try it
Copy these to start.
Use these prompts to begin your audit.
Starting points
Replace the class names with your actual Weaviate class names.
Weaviate Connector
You're all set. Choose your MCP client and follow the setup instructions.
https://edge.vinkius.com/vk_preview_ewBpKaEj3GWOCB4HdPc1Tag8b8QBrbGJDpCpFWfW/mcpClaude Desktop
Follow the steps below to connect in seconds.
- 1In Claude Desktop, open Settings → Connectors.
- 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
- 3Click Add and start a new chat — Weaviate capabilities are ready to use.
{
"mcpServers": {
"weaviate-mcp": {
"url": "https://edge.vinkius.com/vk_preview_ewBpKaEj3GWOCB4HdPc1Tag8b8QBrbGJDpCpFWfW/mcp"
}
}
}Show me the full schema for my Weaviate database so I can check for naming inconsistencies.
Check the schema for the 'Product' class and tell me if any properties are missing.
List the objects in the 'User' class and verify they all have a valid email property.
Compare the properties in my 'Document' class against the actual data stored in it.
Claude
ChatGPT
Cursor
VS Code
Windsurf
Claude Code
JetBrains
Cline
Start here
Connect Weaviate once, then ask.
Just provide your connection details. Your credentials stay encrypted, and you can immediately start asking your AI about your database structure.
Connect Weaviate to your AIFAQ
How this task behaves
- 01
Can the AI change my schema?
No. The AI can only read your schema and data. It cannot create, update, or delete classes or properties.
- 02
Can the AI delete data in my Weaviate database?
No. The tools provided are read-only. Your data remains untouched.
- 03
How does the AI know if my data is wrong?
It compares the properties defined in the schema against the actual objects returned by the database.
- 04
Does the AI see all my data?
The AI only sees the data it requests through the specific tools you authorize it to use.
- 05
Can I use this with Claude?
Yes, you can use this with any MCP-compatible client like Claude, Cursor, or Windsurf.
More questions about Weaviate? The Connector page answers them. See everything the Weaviate Connector can do
Connect Weaviate to Claude, Cursor, ChatGPT & more
