Search across screen, voice, and clipboard entries to find content semantically related to any query. Returns a unified ranked list with source tags for open-ended recall spanning multiple data types.
AGPL 3.0
472,967 tools. Updated 2026-08-24 07:44
"An open-source vector database for similarity search and AI applications" matching MCP tools:
- Retrieve the k nearest nodes to a query embedding using HNSW vector similarity. Use for semantic search after creating a vector index on a specific label and property.Apache 2.0
- Initialize a new vector collection at a specified path, define its vector and scalar fields with optional indexes, and open it for use.Apache 2.0
- Open a saved vector collection from disk for read-write or read-only use, enabling vector search and document retrieval.Apache 2.0
- Screen a brand name for US trademark conflicts against the USPTO database with similarity analysis and an overall risk rating.MIT
- Search by meaning, not exact wording. Embed a query locally, rank rows by vector similarity, and return paraphrases and synonyms with relevance scores.Apache 2.0
Matching MCP Servers
- AlicenseNot gradedqualityDmaintenanceIn-memory vector store with TF-IDF vectorization and cosine similarity search, paid per call via x402 micropayments.MIT
- -licenseNot gradedqualityCmaintenanceTurn SEC EDGAR filings into a searchable vector database, enabling natural language queries over company filings through Claude Desktop.
Matching MCP Connectors
Stateless NMI + cosine fusion with entropy-driven alpha calibration
Read and write open-source flashcards through split read/write MCP tools.
- Combine metadata filters with vector similarity to retrieve relevant documents. Pre-filter by tags, numeric ranges, or full-text before KNN ranking.MIT
- Set up an HNSW vector index for fast similarity search on graph nodes. Requires label, property, dimensions, and metric to index existing and future vectors.Apache 2.0
- Search for similar documents by vector similarity, with optional scalar filters like age > 25.Apache 2.0
- Search Zvec vector stores by converting natural language queries into embeddings and retrieving similar items from a specified collection.Apache 2.0
- Search Code-Fundi repositories with semantic search, grep over docs, or grep over code. Returns matching files with similarity scores, paths, and optional documentation.MIT
- Find relevant content across namespaces using natural language queries or vector similarity. Filter results by metadata or keywords for precise discovery.Apache 2.0
- 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
- Convert text into a numeric vector for semantic search, RAG, and similarity. Supports multiple languages.MIT
- Find all rows within a given distance of a query vector for threshold-based similarity search, enabling de-duplication, similarity gating, and clustering pre-passes. Results are ordered by distance and limited to avoid large result sets.MIT
- Search memories by natural-language query with optional importance and similarity filters. Returns ranked results with similarity scores.MIT
- Generate dense embedding vectors from text for similarity search using OpenAI's embedding API.Apache 2.0
- Search persistent memory using semantic similarity to retrieve relevant memories and related knowledge graph facts.MIT
- Search US patent applications and grants from USPTO data. Get titles, inventors, applicants, status, classification codes, and Patent Center URLs.MIT
- Create a vector index on a vector field in Baidu Vector Database to enable efficient similarity searches for AI applications.Apache 2.0