LNR-server-02-cascading-failure-scenario-simulatio

LNR-server-02-cascading-failure-scenario-simulatio

This server is to precess files for LNR.

Category
Visit Server

README

āš ļø Important Notice āš ļø

As the paper is under review, all contents in this repository are currently not permitted for reuse by anyone until this announcement is removed. Thank you for your understanding! šŸ™

1. Overview & Objectives

This repository contains the complete implementation, experimental data, and supplementary results for the paper ƗƗƗ developed by XXX University in China, and .

Pending publication, the code is shared under a restrictive license. Once the paper is accepted, the repository will transition to a MIT license. Please contact the corresponding author for any inquiries regarding academic use during the review period.

2. Videos of agents operation

2.1 Operation of the developed prototype

↓↓↓ A snippet of using the developed prototype to run the TS-ReAct-based agents driven by GPT-4o

↓↓↓ A snippet of updating the tool kit in the prototype

The full video to showcase the prototype and tool kit updating can be found in:

2.2 Operation of agents based on ReAct pattern

↓↓↓ A snippet of running the ReAct-based agents driven by GPT-4o, GPT-4, and GPT-3.5 Turbo.

The full video can be found here ()

↓↓↓ A snippet of running the ReAct-based agents driven by Qwen2.5, Deepseek-V3, Gemma-2, Llama-3.1, and Mixtral MoE.

The full video can be found here ()

2.3 Operation of agents based on TS-ReAct pattern

↓↓↓ A snippet of running the TS agent based on TS-ReAct pattern.

The full video can be found here ()

↓↓↓ A snippet of running the ReAct agent based on TS-ReAct pattern.

The full video can be found here ()

3. Repository Structure

4. Acknowledgments

This work heavily relies on excellent open-source projects, including but not limited to:

  • LangGraph & LangChain
  • Hugging Face MTEB leaderboard
  • NetworkX, PyTorch Geometric, and numerous LLM providers (OpenAI, Anthropic, Qwen, Llama, etc.)

We are deeply grateful to all contributors of these foundational work.

5. How to Reuse This Repository

5.1 Importing the Lifeline Recovery Tool Set

  1. Copy all tool definition files from tools/ into your target agent directory.
  2. Import the tools using the standardized registry pattern shown in the example notebooks.

5.2 Running Baseline ReAct Agents

  • Directory: agents_reAct/
  • Supports 8 different LLMs (GPT-4o, Claude-3, Llama-3.1-405B, Qwen2.5, etc.)
  • Ready-to-run scripts with configuration YAMLs

5.3 Running the Proposed GraphRAG + MCP Agents

  • Directory: agents_graphRAG_MCP/
  • Same 8 backbone LLMs
  • Includes GraphRAG index construction scripts and MCP search configurations

5.4 Running the Interactive Prototype

  • Directory: prototype/
  • Dynamic tool registration/hot-reloading
  • Web-based GUI + terminal interface
  • Supports on-the-fly addition of new recovery actions

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured