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Enterprise-Grade-Agentic-RAG-System-for-Multi-Format-Document-Intelligence-using-MCP
A Retrieval-Augmented Generation (RAG) chatbot for multi-format document question answering, using embeddings, FAISS, and OpenAI’s GPT models. Built with Streamlit for an interactive UI and structured using the Model Context Protocol (MCP) to handle document ingestion, semantic search, and context-aware responses.
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Python
Quality signals
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InstallMCPRun via uvx (Python)
Universal installANY TOOL
$ npx skillcity@latest Manchulaharshitha/Enterprise-Grade-Agentic-RAG-System-for-Multi-Format-Document-Intelligence-using-MCPAuto-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 enterprise-grade-agentic-rag-system-for-multi-format-document-intelligence-using-mcp
MCP Configuration
Add this to your claude_desktop_config.json
{
"mcpServers": {
"enterprise-grade-agentic-rag-system-for-multi-format-document-intelligence-using-mcp": {
"command": "uvx",
"args": [
"enterprise-grade-agentic-rag-system-for-multi-format-document-intelligence-using-mcp"
]
}
}
}Loading README…
Ask a simulated agent to run this skill. It loads the real SKILL.md and reasons over your task with NVIDIA.
enterprise-grade-agentic-rag-system-for-multi-format-document-intelligence-using-mcp — 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