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agentic-rag-mcp-system
An Agentic RAG system built on Model Context Protocol (MCP) to decouple tool execution from agent logic, enabling scalable and modular AI workflows.
1stars
1forks
Python
agentic-ragautonomous-agentschromadbllm-agentsmcpmodel-context-protocolmulti-agent-systemsopenaipythonquery-refinementragsemantic-search
Quality signals
ActiveNo testsNo CIThin docsNo licenseNew
InstallMCPRun via uvx (Python)
Universal installANY TOOL
$ npx skillcity@latest mpapachrys/agentic-rag-mcp-systemAuto-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 agentic-rag-mcp-system
MCP Configuration
Add this to your claude_desktop_config.json
{
"mcpServers": {
"agentic-rag-mcp-system": {
"command": "uvx",
"args": [
"agentic-rag-mcp-system"
]
}
}
}Loading README…
Ask a simulated agent to run this skill. It loads the real SKILL.md and reasons over your task with NVIDIA.
agentic-rag-mcp-system — 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