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RAG_demo_with_monitor
This application takes input from user via PDF and databricks table, updates vector index, calls MCP server for internal policies and ask LLM to answer in case the policy is not present in MCP server. Application creates monitoring logs and provide precision and MRR of the retrieval.
1stars
0forks
Python
databricks-connectmcp-serverpdf-processingrag-pipelinevector-embeddings
Quality signals
StaleNo testsNo CIThin docsNo licenseNew
InstallMCPRun via uvx (Python)
Universal installANY TOOL
$ npx skillcity@latest mayankag22/RAG_demo_with_monitorAuto-detects the skill or MCP server in this repo and installs it for Claude Code, Codex, Cursor, Cline, OpenCode, Gemini CLI, Anti-Gravity, OpenClaw and Hermes.
Requires Node.js 18+ (ships with npx).
Or install manually
uvx rag_demo_with_monitor
MCP Configuration
Add this to your claude_desktop_config.json
{
"mcpServers": {
"rag_demo_with_monitor": {
"command": "uvx",
"args": [
"rag_demo_with_monitor"
]
}
}
}Loading README…
Ask a simulated agent to run this skill. It loads the real SKILL.md and reasons over your task with NVIDIA.
rag_demo_with_monitor — sandboxAI sandbox
Pick a quick prompt below or type your own — watch the agent execute this skill step by step.
guest@skillcity:~$Try a prompt