InfraNodus의 지식 그래프 및 텍스트 네트워크 분석 기능을 LLM 워크플로우와 Claude Desktop과 같은 AI 어시스턴트에 통합하는 모델 컨텍스트 프로토콜(MCP) 서버입니다.

npm에서 이용 가능: https://www.npmjs.com/package/infranodus-mcp-server

개요

InfraNodus MCP Server는 LLM 워크플로우와 AI 어시스턴트가 고급 네트워크 과학 알고리즘을 사용해 텍스트를 분석하고, 지식 그래프를 생성하며, 콘텐츠 공백을 감지하고, 핵심 주제와 개념을 식별할 수 있도록 지원합니다. 그래프 이론과 네트워크 분석을 활용하여 비구조화된 텍스트를 구조화된 통찰로 변환합니다.

특징

그걸 쓸 수 있어

• 기존 InfraNodus 지식 그래프를 LLM 워크플로우 및 AI 채팅에 연결합니다
• 담화 내 주요 주제 클러스터를 중요한 뉘앙스를 놓치지 않으면서 식별하기 (표준 LLM 워크플로우보다 더 효과적)
• 담론에서 내용 공백을 식별하기 (콘텐츠 제작 및 연구에 유용함)
• 어떤 텍스트에서든 새로운 지식 그래프를 생성하여 LLM 응답을 보완하기
• 지식 그래프를 사용하여 메모리에서 엔터티와 관계를 저장하고 검색할 수 있습니다.

사용 가능한 도구

1. generate_knowledge_graph

• 텍스트를 시각적 지식 그래프로 변환하기

InfraNodus MCP Server

A Model Context Protocol (MCP) server that integrates InfraNodus knowledge graph and text network analysis capabilities into LLM workflows and AI assistants like Claude Desktop.

Available on npm: https://www.npmjs.com/package/infranodus-mcp-server

Overview

InfraNodus MCP Server enables LLM workflows and AI assistants to analyze text using advanced network science algorithms, generate knowledge graphs, detect content gaps, and identify key topics and concepts. It transforms unstructured text into structured insights using graph theory and network analysis.

Features

You Can Use It To

• Connect your existing InfraNodus knowledge graphs to your LLM workflows and AI chats
• Identify the main topical clusters in discourse without missing the important nuances (works better than standard LLM workflows)
• Identify the content gaps in any discourse (helpful for content creation and research)
• Generate new knowledge graphs from any text and use them to augment your LLM responses
• Save and retrieve entities and relations from memory using the knowledge graphs

Available Tools

1. generate_knowledge_graph

   • Convert any text into a visual knowledge graph
   • Extract topics, concepts, and their relationships
   • Identify structural patterns and clusters
   • Apply AI-powered topic naming
   • Perform entity detection for cleaner graphs

2. analyze_existing_graph_by_name

   • Retrieve and analyze existing graphs from your InfraNodus account
   • Access previously saved analyses
   • Export graph data with full statistics

3. analyze_text

   • Analyze a text, URL, or YouTube transcript
   • Extract and analyze a graph from text or URL; provide either text or url
   • Get topics, clusters, statements, graph structure, and AI summary as requested

4. generate_content_gaps

   • Detect missing connections in discourse
   • Identify underexplored topics
   • Generate research questions
   • Suggest content development opportunities

5. generate_topical_clusters

   • Generate topics and clusters of keywords from text using knowledge graph analysis
   • Make sure to beyond genetic insights and detect smaller topics
   • Use the topical clusters to establish topical authority for SEO
   • Returns AI-generated overviews of the topical clusters (topicalClusterSummaries), summarizing the discourse each cluster represents — useful for SEO-optimized content creation. Enabled by default; set generateTopicalSummaries: false to increase processing speed or if the summary request fails

6. generate_contextual_hint

   • Generate a topical overview of a text and provide insights for LLMs to generate better responses