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metadata
title: MCP-Powered RAG and Research Topic
emoji: 🌍
colorFrom: green
colorTo: blue
sdk: gradio
sdk_version: 5.32.1
app_file: app.py
pinned: false
license: mit
short_description: MCP-Powered RAG and Research Topic
tag: mcp-server-track

👁 MCP Powered RAG and Research Topic 🌍

I present to you an MCP-powered RAG and Research Topic.

RAG Tool uses the GroundX storage by eyelevel.ai to fetch the knowledge base. The knowledge base is a document that contains information about the SU-35 aircraft, including its features, capabilities, and specifications. Please check this PDF to formulate queries on Sukhoi.

The Research Tool is implemented using a multi-agent workflow using LlamaIndex (ResearchAgent, WriteAgent, and ReviewAgent).
The agents use Nebius provided LLM.

Available Tools

search_knowledge_base_for_context

  • Description: Searches and retrieves relevant context from a knowledge base based on the user's query.
  • Example Queries:
    • "What are the main features of fuel system of SU-35."
    • "What are the combat potential of SU-35."

research_write_review_topic

  • Description: Helps with writing a report with research, writing, and review on any topic.
  • Example Queries:
    • "Write me a report on the history of the internet."
    • "Write me a report on origin of the universe."
    • "Write me a report on the impact of climate change on polar bears."

How to Use

  • Use the MCP RAG Tool tab above to query the knowledge base.
  • Use the Research Tool tab above to write report on any topic.

Watch the Demo Video here

Link to Demo on Youtube

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference