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650,522 tools. Updated 2026-10-14 01:26

"An open-source vector database for similarity search and AI applications" matching MCP tools:

  • 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
  • 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
  • Open a saved vector collection from disk for read-write or read-only use, enabling vector search and document retrieval.
    Apache 2.0
  • Retrieve the top-K most similar vertices to a query vector using vector similarity search. Provide vertex type, vector attribute, and query vector to get ranked results with distance scores.
    Apache 2.0

Matching MCP Servers

  • F
    license
    Not graded
    quality
    B
    maintenance
    Enables stateless similarity search over pre-computed vector corpora using NMI and cosine fusion with entropy-calibrated weighting. Provides tools for ranking, scoring, outlier detection, and alpha calibration for AI agents.
    -
  • A
    license
    Not graded
    quality
    D
    maintenance
    In-memory vector store with TF-IDF vectorization and cosine similarity search, paid per call via x402 micropayments.
    MIT

Matching MCP Connectors

  • 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 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
  • Convert text into a numeric vector for semantic search, RAG, and similarity. Supports multiple languages.
    MIT
  • Generate vector representations for texts via Forge's hosted API to power semantic search, RAG, clustering, or similarity; use query/document input types.
    MIT
  • Search memories by natural-language query with optional importance and similarity filters. Returns ranked results with similarity scores.
    MIT
  • Search persistent memory using semantic similarity to retrieve relevant memories and related knowledge graph facts.
    MIT
  • Perform a KNN vector similarity search on vectors stored in Redis hash data structures, returning the nearest neighbors for a given query vector.
    MIT
  • Search US patent applications and grants to get inventor, applicant, status, classification codes, and Patent Center URLs.
    MIT
  • Find similar vector embeddings in Zilliz Cloud collections using vector similarity search with optional filtering and result customization.
    Apache 2.0