BeClaude

rag-implementation

New
28.2kSmitheryDocumentationby wshobson

Build Retrieval-Augmented Generation (RAG) systems for LLM applications with vector databases and semantic search. Use when implementing knowledge-grounded AI, building document Q&A systems, or integrating LLMs with external knowledge bases.

First seen 5/24/2026

Install & Usage

1
Open your MCP config
~/.claude.json
2
Add the server config

Add the configuration to "mcpServers": { "rag-implementation": { "command": "...", "args": [] } }

3
Restart Claude Code
/mcp
View source on GitHub
documentationai-&-ml

Security Audits

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Frequently Asked Questions

What is rag-implementation?

Build Retrieval-Augmented Generation (RAG) systems for LLM applications with vector databases and semantic search. Use when implementing knowledge-grounded AI, building document Q&A systems, or integrating LLMs with external knowledge bases.

How to install rag-implementation?

To install rag-implementation: open your mcp config (~/.claude.json), then add the config to "mcpServers": { "rag-implementation": { "command": "...", "args": [] } }. Finally, /mcp in Claude Code.

What is rag-implementation best for?

rag-implementation is a mcp categorized under Documentation. It is designed for: documentation, ai-&-ml. Created by wshobson.