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mcp-server-infranodus MCP Server

infranodus/mcp-server-infranodus

Score: 50.8 ↓ 3.3% Rank #17434 MCP Server
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The official InfraNodus MCP server

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Overview

infranodus/mcp-server-infranodus is a TypeScript MCP server licensed under MIT. The official InfraNodus MCP server

Ranked #17434 out of 24846 indexed tools.

Ecosystem

TypeScript MIT

Score Breakdown

StarsFreshnessIssue HealthContributorsDependents
Stars 15% 103

103 stars → growing community

Freshness 25% 1mo ago

Last commit 1mo ago → moderate activity

Issue Health 25% 20%

1/5 issues closed → many open issues

Contributors 10% 1

1 contributor → solo project

Dependents 25% 0

No dependents → no downstream usage

npm Downloads N/A
PyPI Downloads N/A
Forks 27
Description Brief
License MIT

Weights: Freshness 20% · Issue Health 20% · Dependents 22% · Stars 10% · Contributors 8% · How we score →

How to Improve

Description low impact

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Freshness high impact

Last commit was 38 days ago — a recent commit would boost your freshness score

Issue Health high impact

You have 4 open vs 1 closed issues — triaging stale issues improves health

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AgentRank score for infranodus/mcp-server-infranodus
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Matched Queries

"mcp server""mcp-server"

From the README

# 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](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)
- Genera
Read full README on GitHub →

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