Generate vector embeddings from text for semantic search, RAG, clustering, or similarity tasks. Choose between query or document input type and adjust model quality and dimensionality.
MIT
234,860 tools. Last updated 2026-06-25 10:34
"Searching for technologies and tools related to embeddings and vector databases" matching MCP tools:
- Find similar vector embeddings in Zilliz Cloud collections using vector similarity search with optional filtering and result customization.Apache 2.0
- Retrieve all fields and their data types from a specified Fibery database and its related databases to understand data structure.MIT
- Retrieve technographic tags to filter businesses by web technologies like CMS or analytics tools. Optionally narrow results with a keyword.MIT
- Update the vector index for knowledge base documents. Re-embeds only changed files by default, or rebuild all embeddings from scratch when forcing a full reindex.Business Source 1.1
- List configured database connections to see available databases, drivers, and servers without exposing credentials. Use before other database tools.MIT
Matching MCP Servers
- -license-quality-maintenanceEnables AI assistants to interact with Databricks workspaces, running SQL queries, managing jobs, and exploring schemas via the Model Context Protocol.Last updated1
- AlicenseCqualityDmaintenanceEnables access to Usage and Billing APIs for managing accounts, products, meters, plans, and usage reporting. Supports operations like creating products/plans, reporting usage, and retrieving billing information.Last updated18MIT
Matching MCP Connectors
Print and mail physical letters and postcards to US postal addresses, plus address verification. Upload PDF/HTML/Markdown/text/DOCX/image documents, get a quote, and pay per call with x402 USDC on Base mainnet or credit card. Supports certified/registered mail with proof of delivery and mail-merge templates.
Transform any blog post or article URL into ready-to-post social media content for Twitter/X threads, LinkedIn posts, Instagram captions, Facebook posts, and email newsletters. Pay-per-event: $0.07 for all 5 platforms, $0.03 for single platform.
- Search within related memories to find solutions in specific problem contexts using semantic scoping without embeddings.MIT
- Find related records across NCBI databases by linking source IDs to target databases, such as discovering PubMed articles for a gene or nucleotide sequences for a protein.MIT
- Indexes a codebase to build vector embeddings for semantic code search across 50+ languages. Required initial step before searching code.MIT
- Add multiple memory nodes with automatic similarity linking. Computes embeddings and creates connections between related concepts, files, or notes for semantic intelligence.MIT
- Compare technologies like frameworks, libraries, databases, or programming languages side-by-side. Automatically gather structured information to support informed decision-making.MIT
- Precompute and cache symbol embeddings to eliminate first-query latency when using semantic search. Call after reindexing.MIT
- List all available Canadian court and tribunal databases from CanLII. Returns database IDs required for browse, citator, and other tools. Use to find valid IDs for courts like ONSC, ONCA, SCC, BCSC, etc.MIT
- Discover semantically related memories missing explicit links, using embeddings and entity graphs to surface latent connections for review.PolyForm Noncommercial 1.0.0
- Permanently delete a registered media asset by removing storage files, vector embeddings, and all associated metadata. This action cannot be undone.MIT
- Identifies programming languages, frameworks, databases, cloud services, and tools mentioned in YouTube video transcripts for tech talks and tutorials.MIT
- Regenerate vector embeddings for all published content to maintain search accuracy and relevance in LightCMS. Use after initial setup or when embeddings become outdated.MIT
- Retrieve semantically related objects from a specified collection using vector search. Provide a source object UUID and collection to find relevant results.MIT
- Lists all research topics stored in the vector database, providing an overview of available areas for exploration and selection.MIT
- Search an agent's memory by matching text in keys and values. Uses case-insensitive matching without vector embeddings.MIT