Install
Quick install
npx skills add https://github.com/dannwaneri/vectorize-mcp-workernpx skills add dannwaneri/vectorize-mcp-worker --agent claude-codenpx skills add dannwaneri/vectorize-mcp-worker --agent cursornpx skills add dannwaneri/vectorize-mcp-worker --agent codexnpx skills add dannwaneri/vectorize-mcp-worker --agent opencodenpx skills add dannwaneri/vectorize-mcp-worker --agent github-copilotnpx skills add dannwaneri/vectorize-mcp-worker --agent windsurfMore install options
Shorthand — useful for multi-skill repos:
npx skills add dannwaneri/vectorize-mcp-workerManual — clone the repo and drop the folder into your agent's skills directory:
git clone https://github.com/dannwaneri/vectorize-mcp-worker.gitcp -r vectorize-mcp-worker ~/.claude/skills/Vectorize MCP Worker
Edge-native MCP server patterns for production RAG
What is it?
An edge-native MCP (Model Context Protocol) server designed for production RAG (Retrieval-Augmented Generation) workloads. Built on Cloudflare Workers, it provides vector search, document indexing, and semantic retrieval capabilities at the edge. Ideal for building AI applications that need fast, scalable knowledge retrieval.
How to use it?
Deploy the MCP worker to Cloudflare Workers, then configure it as an MCP server:- Index documents - Upload and vectorize your content for semantic search
- Search - Query your indexed content using natural language
- Retrieve - Get relevant context for RAG pipelines
The worker runs at the edge for low-latency responses and scales automatically with Cloudflare's infrastructure. It supports the MCP protocol for seamless integration with AI agents.
Key Features
- Edge-native deployment on Cloudflare Workers for low latency
- Vector search and semantic document retrieval
- MCP protocol support for AI agent integration
- Production-ready RAG pipeline infrastructure
- Automatic scaling via Cloudflare's global networkView on GitHub
GitHub Stats
StarsForksLast UpdateAuthordannwaneriLicenseMITVersion1.0.0Categories
Developer ToolsAI & MLTags
mcpragdevFeatures
Related Skills
More from Developer ToolsContext Engineering
Context engineering techniques8.3kmuratcankoylanDeveloper ToolsAI & ML00
Build MCP Server
MCP server development guide with agent-centric design principles, workflow-first approach, and dual Python (FastMCP) / TypeScript implementation support433NeoLabHQAI & MLDeveloper Tools00
prompt-engineering
Teaches well-known prompt engineering techniques and patterns, including Anthropic best practices and agent persuasion principles433NeoLabHQDeveloper ToolsAI & ML00
---
Source: https://github.com/dannwaneri/vectorize-mcp-worker
Author: dannwaneri
License: https://opensource.org/licenses/MIT
GitHub Stars: 12
Tags: mcp, rag, dev
SKILL.md source
--- name: Vectorize MCP Worker description: Edge-native MCP server patterns for production RAG --- # Vectorize MCP Worker Edge-native MCP server patterns for production RAG What is it? An edge-native MCP (Model Context Protocol) server designed for production RAG (Retrieval-Augmented Generation) workloads. Built on Cloudflare Workers, it provides vector search, document indexing, and semantic retrieval capabilities at the edge. Ideal for building AI applications that need fast, scalable knowledge retrieval. ## How to use it? Deploy the MCP worker to Cloudflare Workers, then configure it as an MCP server: * Index documents - Upload and vectorize your content for semantic search * Search - Query your indexed content using natural language * Retrieve - Get relevant context for RAG pipelines The worker runs at the edge for low-latency responses and scales automatically with Cloudflare's infrastructure. It supports the MCP protocol for seamless integration with AI agents. ## Key Features * Edge-native deployment on Cloudflare Workers for low latency * Vector search and semantic document retrieval * MCP protocol support for AI agent integration * Production-ready RAG pipeline infrastructure * Automatic scaling via Cloudflare's global networkView on GitHub ### GitHub Stats StarsForksLast UpdateAuthordannwaneriLicenseMITVersion1.0.0 ### Categories Developer ToolsAI & ML ### Tags mcpragdev ### Features ## Related Skills More from Developer Tools ### Context Engineering Context engineering techniques 8.3kmuratcankoylanDeveloper ToolsAI & ML00 ### Build MCP Server MCP server development guide with agent-centric design principles, workflow-first approach, and dual Python (FastMCP) / TypeScript implementation support 433NeoLabHQAI & MLDeveloper Tools00 ### prompt-engineering Teaches well-known prompt engineering techniques and patterns, including Anthropic best practices and agent persuasion principles 433NeoLabHQDeveloper ToolsAI & ML00 --- **Source**: https://github.com/dannwaneri/vectorize-mcp-worker **Author**: dannwaneri **License**: https://opensource.org/licenses/MIT **GitHub Stars**: 12 **Tags**: mcp, rag, dev
Related skills 6
running-claude-code-via-litellm-copilot
Use when routing Claude Code through a local LiteLLM proxy to GitHub Copilot, reducing direct Anthropic spend, configuring ANTHROPIC_BASE_URL or ANTHROPIC_MODEL overrides, or troubleshooting Copilot proxy setup failures such as model-not-found, no localhost traffic, or GitHub 401/403 auth errors.
skills-cli
Use when users ask to discover, install, list, check, update, remove, back up, restore, sync, or initialize Agent Skills, mention `bunx skills`, `npx skills`, `skills.sh`, or `skills-lock.json`, ask "find a skill for X", or want help extending agent capabilities with installable skills.
repo-intake-and-plan
Narrow RigorPilot helper for README-first deep learning repo reproduction. Use when the task is specifically to scan a repository, read the README and common project files, extract documented commands, classify inference, evaluation, and training candidates, and return the smallest trustworthy reproduction plan to the main orchestrator. Do not use for environment setup, asset download, command execution, final reporting, paper lookup, or end-to-end orchestration.
image-to-video
Animate any still image on RunComfy — this skill is a smart router that matches the user's intent to the right i2v model in the RunComfy catalog. Picks HappyHorse 1.0 I2V (Arena #1, native audio, identity preservation) for general animations, Wan 2.7 with `audio_url` for custom-voiceover lip-sync, or Seedance 2.0 Pro for multi-modal animation from image + reference video + reference audio. Bundles each model's documented prompting patterns so the caller gets sharper output without burning ite...
video-edit
Edit existing video on RunComfy — this skill is a smart router that matches the user's intent to the right edit model in the RunComfy catalog. Picks Wan 2.7 Edit-Video (general restyle / background swap / packaging swap, identity + motion preservation), Kling 2.6 Pro Motion Control (transfer precise motion from a reference video to a target character), or Lucy Edit Restyle (lightweight identity-stable restyle / outfit swap). Bundles each model's documented prompting patterns so the skill gets...
nano-banana-2
Generate images with Google Nano Banana 2 (Gemini-family flash-tier text-to-image) on RunComfy — bundled with the model's documented prompting patterns so the skill gets sharper output than naive prompting against the same model. Documents Nano Banana 2's strengths (rapid iteration, in-image typography rendering, predictable framing, optional web-grounded context), the resolution-tier pricing, the safety-tolerance dial, and when to route to Nano Banana Pro / GPT Image 2 / Flux 2 / Seedream in...