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@ruvector/wasm

Initialize WebAssembly bindings for client-side HNSW vector search in browsers and edge runtimes.

1|Updated Feb 8, 2026
Search Tags:#edge computing#vector database#client-side#wasm#webassembly#similarity search
One-click install
npx skills add https://github.com/ricable/cli-skills-builder --skill ruvector-wasm
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: @ruvector/wasm
Source: https://github.com/ricable/cli-skills-builder/tree/main/.claude/skills/ruvector-wasm
Command: npx skills add https://github.com/ricable/cli-skills-builder --skill ruvector-wasm

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill enables high-performance vector search directly within browser and edge runtimes, eliminating the need for a dedicated server for similarity search.

Core Features & Use Cases

  • Client-Side Vector Database: Store and search embeddings client-side using WebAssembly.
  • Edge Deployments: Ideal for Cloudflare Workers, Deno Deploy, and other edge environments.
  • Use Case: Embed user-generated content on a website and perform real-time similarity searches without server roundtrips.

Quick Start

Initialize the WebAssembly module and create a new vector database instance.

Frequently Asked Questions about @ruvector/wasm

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I run vector similarity search directly in the browser?▼

You can run vector similarity search directly in the browser by using WebAssembly bindings to initialize a client-side HNSW database, eliminating the need for a dedicated server roundtrip.

Can I perform client-side vector search in edge computing environments?▼

Yes, you can perform client-side vector search in edge computing environments like Cloudflare Workers or Deno Deploy by executing WASM-based vector operations directly within edge runtimes.

How do I persist a WASM vector database locally?▼

To persist a WASM vector database locally, you use the serialization functionality provided by the module to save the client-side search index state after performing vector operations.

What is the best way to handle real-time similarity search without a backend?▼

The best way to handle real-time similarity search without a backend is embedding user-generated content on the website and using WebAssembly to execute HNSW search client-side.

Do I need to initialize WebAssembly before using a client-side vector database?▼

Yes, you must initialize the WebAssembly module before instantiating the vector database to ensure the environment is ready for HNSW similarity search and portable vector operations.

Does this approach support serverless similarity search for edge deployments?▼

Yes, this approach supports serverless similarity search for edge deployments by leveraging WASM-based embeddings to execute high-performance vector queries directly within the edge runtime.

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