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Weaviate

Weaviate is an open-source vector database designed for AI-native applications and semantic search. Store and query vector embeddings, perform similarity searches, integrate with ML models, build recommendation systems, and enable semantic search capabilities for AI-powered applications.

This Weaviate MCP server is compatible with any MCP client including Claude Desktop, Cursor, and other Model Context Protocol implementations.

Backend Services

FIELDS

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Tools From This Provider (32)

Weaviate Backup Collection

Create a complete backup of a collection including schema and data.

Weaviate Export Collection

Export collection data including vectors, properties, and metadata for backup or migration.

Weaviate Validate Schema Compliance

Validate objects against collection schema definition. Checks if objects have all required properties and correct data types.

Weaviate Check Orphaned References

Check for broken cross-references in collections. Returns objects with references to deleted or non-existent objects.

Weaviate Hybrid Search

Perform hybrid search combining semantic vector search with keyword matching. Hybrid search combines BM25 keyword search with vector similarity.

Weaviate Restore Collection

Restore a collection from a backup. CAUTION: This will overwrite existing data in the collection.

Weaviate Get Reference Graph

Get a graph of cross-references between collections. Shows which collections reference each other and how.

Weaviate Find Duplicates

Find near-duplicate objects using vector similarity. Helps identify redundant data and potential data quality issues from duplicate imports.

Weaviate Validate Properties

Validate property completeness and quality. Find objects with null, missing, or empty required properties. Essential for data quality monitoring.

Weaviate Check Vector Quality

Check vector quality for corruption issues. Detects zero vectors, NaN values, and vectors with abnormal magnitude. Critical for maintaining search quality.

Weaviate Data Quality Report

Generate comprehensive data quality report. Combines vector quality, property completeness, duplicates, and collection health into a single report with actionable recommendations.

Weaviate Batch Update

Update multiple objects matching a filter condition. Useful for bulk status changes, migrations, or data corrections. Includes safety limits to prevent accidental mass updates.

Weaviate Batch Delete

Delete multiple objects matching a filter condition. DESTRUCTIVE operation with safety limits. Requires explicit confirmation and WHERE filter to prevent accidental mass deletion.

Weaviate Copy Objects

Copy objects between collections. Useful for data migration, creating backups, or duplicating data for testing. Optionally preserves or regenerates vectors.

Weaviate Profile Collection

Generate comprehensive collection profile with statistics on object count, properties, vectors, and overall health. Essential starting point for understanding a collection's contents.

Weaviate Analyze Property Distribution

Analyze distribution of values for a specific property. Shows top values, uniqueness, null rate, and statistics. Essential for understanding data patterns and quality.

Weaviate Analyze Vector Distribution

Analyze vector embeddings distribution. Shows dimensionality, magnitude statistics, density, and similarity patterns. Critical for understanding embedding quality.

Weaviate Sample Objects

Get representative sample objects from a collection. Useful for quick inspection and understanding data structure without fetching all objects.

Weaviate Compare Collections

Compare two collections to find differences in schemas, object counts, and configurations. Useful for validating migrations or understanding related collections.

Weaviate Batch Import

Import multiple objects in batch. Optimized for bulk loading with automatic error handling, retry logic, and progress reporting. Much faster than individual inserts.

Weaviate Get Schema Detailed

Get comprehensive schema information for a collection including properties, data types, vectorizer configuration, indexes, and module settings.

Weaviate Create Collection

Create a new Weaviate collection with custom schema. Define properties, data types, and optionally configure a vectorizer for automatic embedding generation.

Weaviate Get Cross References

Analyze cross-reference relationships between collections. Shows which collections reference which other collections, similar to foreign key relationships.

Weaviate Find Unused Collections

Find collections that have no objects (empty collections). Useful for identifying collections that can be safely removed or need to be populated.

Weaviate Get Property Usage

Analyze property usage in a collection. Shows which properties are consistently populated vs frequently null/empty. Useful for understanding data completeness and identifying unused schema fields.

Weaviate Find Missing Vectors

Find objects without vector embeddings. Critical for debugging semantic search issues - objects without vectors won't appear in similarity searches.

Search

Search Weaviate vector store using hybrid semantic + keyword search or BM25. Returns ranked results with IDs, titles, and scores.

Weaviate Delete

Delete object(s) or entire collection from Weaviate. Supports three modes: single object deletion, bulk deletion with failure tracking, and collection removal. All deletions are permanent and cannot...

Weaviate Upsert

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, omit for inserts. Automatically optimizes batch...

Weaviate List Objects

Browse objects in a collection with rich filtering, sorting, pagination, and property selection. The workhorse tool for exploring data with granular control over what's returned. Supports search...

Weaviate List Collections

List all Weaviate collections with rich filtering options. Supports pattern matching, schema inclusion, object counts, and pagination. Use this for collection discovery and understanding your data...

Fetch

Universal fetch tool that retrieves any object, schema, or metadata using smart ID routing with colon-separated format. Supports direct object retrieval, schema inspection, and collection metadata.

Related Bundles (4)

Data Exploration

Backend Services

Browse, search, and explore vector data in collections. Find objects, perform semantic searches, sample data, and understand what's in your vector database.

Data Quality & Profiling

Backend Services

Profile vectors, find anomalies, and validate quality. Analyze vector distributions, detect missing embeddings, validate properties, check data integrity, and ensure vector database health.

Schema & Structure

Backend Services

Understand vector database structure, relationships, and schema. Explore collections, properties, cross-references, and understand how your vector database is organized.

Weaviate

Backend Services

Complete Weaviate vector database toolkit. All 32 tools for semantic search, vector operations, schema management, data quality, and batch operations. Perfect for AI-native applications.

Provider Information

CategoryBackend Services

Auth TypeFIELDS

AddedOctober 12, 2025

UpdatedDecember 16, 2025

Used By Tools

32

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Weaviate MCP Server - MCP Bundles • MCP Providers