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All Weaviate tools
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Browse all toolsDomain knowledge for Weaviate — workflow patterns, data models, and gotchas for your AI agent.
Weaviate stores objects inside collections, each carrying structured properties and optional embedding vectors. Similarity queries rank by vector distance; hybrid modes blend keyword filters with embeddings.
weaviate:object:collection:id from browse or retrieval responses when you need a point read.Universal fetch tool that retrieves any object, schema, or metadata using smart ID routing with colon-separated format. Supports direct object retriev...
Search Weaviate vector store using hybrid semantic + keyword search or BM25. Returns ranked results with IDs, titles, and scores.
Analyze distribution of values for a specific property. Shows top values, uniqueness, null rate, and statistics. Essential for understanding data patt...
Analyze vector embeddings distribution. Shows dimensionality, magnitude statistics, density, and similarity patterns. Critical for understanding embed...
Create a complete backup of a collection including schema and data.
Delete multiple objects matching a filter condition. DESTRUCTIVE operation with safety limits. Requires explicit confirmation and WHERE filter to prev...
Import multiple objects in batch. Optimized for bulk loading with automatic error handling, retry logic, and progress reporting. Much faster than indi...
Update multiple objects matching a filter condition. Useful for bulk status changes, migrations, or data corrections. Includes safety limits to preven...
Check for broken cross-references in collections. Returns objects with references to deleted or non-existent objects.
Check vector quality for corruption issues. Detects zero vectors, NaN values, and vectors with abnormal magnitude. Critical for maintaining search qua...
Compare two collections to find differences in schemas, object counts, and configurations. Useful for validating migrations or understanding related c...
Copy objects between collections. Useful for data migration, creating backups, or duplicating data for testing. Optionally preserves or regenerates ve...
Create a new Weaviate collection with custom schema. Define properties, data types, and optionally configure a vectorizer for automatic embedding gene...
Generate detailed data quality report. Combines vector quality, property completeness, duplicates, and collection health into a single report with act...
Delete object(s) or entire collection from Weaviate. Supports three modes: single object deletion, bulk deletion with failure tracking, and collection...
Export collection data including vectors, properties, and metadata for backup or migration.
Find near-duplicate objects using vector similarity. Helps identify redundant data and potential data quality issues from duplicate imports.
Find objects without vector embeddings. Critical for debugging semantic search issues - objects without vectors won't appear in similarity searches.
Find collections that have no objects (empty collections). Useful for identifying collections that can be safely removed or need to be populated.
Analyze cross-reference relationships between collections. Shows which collections reference which other collections, similar to foreign key relations...
Analyze property usage in a collection. Shows which properties are consistently populated vs frequently null/empty. Useful for understanding data comp...
Get a graph of cross-references between collections. Shows which collections reference each other and how.
Get full schema information for a collection including properties, data types, vectorizer configuration, indexes, and module settings.
Perform hybrid search combining semantic vector search with keyword matching. Hybrid search combines BM25 keyword search with vector similarity.
List all Weaviate collections with rich filtering options. Supports pattern matching, schema inclusion, object counts, and pagination. Use this for co...
Browse objects in a collection with rich filtering, sorting, pagination, and property selection. The workhorse tool for exploring data with granular c...
Generate full collection profile with statistics on object count, properties, vectors, and overall health. Essential starting point for understanding ...
Get representative sample objects from a collection. Useful for quick inspection and understanding data structure without fetching all objects.
Insert or update objects in Weaviate. Data is ALWAYS an array - use [obj] for single items, [obj1, obj2, ...] for batch. Provide ids array for updates...
Validate property completeness and quality. Find objects with null, missing, or empty required properties. Essential for data quality monitoring.
Validate objects against collection schema definition. Checks if objects have all required properties and correct data types.
All Weaviate tools It provides 31 tools that AI agents can use through the Model Context Protocol (MCP).
Add the MCPBundles server URL to your MCP client configuration (Claude Desktop, Cursor, VS Code, etc.). The URL format is: https://mcp.mcpbundles.com/bundle/weaviate. Authentication is handled automatically.
Weaviate provides 31 tools that can be called by AI agents, along with a SKILL.md that gives your AI agent domain knowledge about when and how to use them.
Weaviate uses API Key. Weaviate requires credentials. Connect via MCPBundles and authentication is handled automatically.
Connect Weaviate to any MCP client in minutes
Model Context Protocol lets AI tools call external capabilities securely through a single URL. This bundle groups tools behind an MCP endpoint that many clients can use.
Skip the manual setup! Use the .mcpb file format for one-click installation. Check the Claude Desktop tab for setup instructions.
Select ChatGPT, Cursor, Claude Code, or another tab for copy-paste config.
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