Infranodus Infranodus MCP server

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. generateknowledgegraph

• 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

1. analyzeexistinggraphbyname

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

1. analyzetext**

• 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

1. generatecontentgaps

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

1. generatetopicalclusters

• 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

1. generatecontextualhint

• Generate a topical overview of a text and provide insights for LLMs to generate better responses
• Use it to get a high-level understanding of a text
• Use it to augment prompts in your LLM workflows and AI assistants

1. generateresearchquestions

• Generate research questions that bridge content gaps from text, URL, or an existing InfraNodus graph
• Use them as prompts in your LLM models and AI workflows
• Use any AI model (included in InfraNodus API)
• Content gaps are identified based on topical clustering

1. generateresearchideas

• Generate innovative research ideas based on content gaps identified in the text
• Get actionable ideas to improve the text and develop the discourse
• Use any AI model (included in InfraNodus API)
• Ideas are generated from gaps between topical clusters

Shortened. The full README is on GitHub.