Louvain community detection
Louvain community detection for graphology.
Given a graph instance detects communities using the Louvain Method
Leiden/Louvain community detection for ngraph.graph (JS)
[NODE ONLY] Given a graph instance detects communities using the Louvain Method
Community finding algorithm.
graph algorithm
Javascript implementation of the directed louvain algorithm for community detection.
Miscellaneous indices for graphology.
Louvain community detection for Javascript
CSL style for Université Catholique de Louvain - Histoire (Français)
Pure-TypeScript implementation of the Leiden community-detection algorithm (Traag, Waltman & van Eck, 2019). Zero runtime dependencies. Faster than graspologic across the standard benchmark portfolio.
Local semantic code graph for AI agents. Adds codebase-aware MCP tools (search, dependencies, architecture map) to Claude Code, Cursor, Windsurf, and Codex — runs entirely on your laptop, no API keys, no cloud.
Local semantic index layer for codebases. Structural code intelligence via tree-sitter + SQLite, with MCP server for Claude Code.
TypeScript port of the Java networkanalysis package that provides data structures and algorithms for network analysis.
Give your AI agents a map of your repo before they edit.
Standalone Node MCP server: semantic search + knowledge graph + vault editing for Obsidian, no plugin required.
A Jupyter widget using sigma.js to render interactive networks.
[](https://doi.org/10.5281/zenodo.15501897) [](https://www.npmjs.com/package/code-health-meter)
Entity-anchored graph memory with vector search and community detection for Claude Code
Given a community structure creates a coarse graph
Codebase analysis tool with structured, git-friendly output
Infomap optimizes the map equation, which exploits the information-theoretic duality between the problem of compressing data, and the problem of detecting and extracting significant patterns or structures within those data.
Official CLI for Brainbase — query and manage your knowledge graph with Neo4j graph intelligence
A Rust library for building and querying knowledge graphs using SQLite as the backend, with graph algorithms, vector search, and RAG support
Self-evolving knowledge substrates through biological computing primitives
PostgreSQL knowledge graph extension with graph algorithms and pgvector integration
Leiden community detection — find densely-connected clusters in weighted graphs
Graph processing module for SciRS2 (scirs2-graph)
GPU-first embedded graph database for code analysis (call graphs, dependencies, AST traversals)
Core library for Engram -- persistent semantic memory for AI agents
Pure-Rust, high-performance graph & network analysis library — 1200+ APIs, zero unsafe, igraph-compatible
A high-performance network clustering library implementing community detection algorithms like Louvain and Leiden. Features efficient graph representation, abstract grouping systems, and K-NN graph creation from high-dimensional data. Provides parallel computation support via Rayon for handling large networks.
Talon CLI: hybrid retrieval over Obsidian vaults and markdown corpora, with grounded answers, MCP server, and agent-native output.
Core retrieval engine for Talon: hybrid search (BM25 + semantic + reranker), indexing, and graph-aware ranking over markdown corpora.
Omics data structures for the Cyanea bioinformatics ecosystem
Ruby implementation of Louvain community detection method
Waw is a ruby web framework that aims at thinking the web another way. It's has been originally designed in the ReQuest research project of the University of Louvain, has been entirely rewritten in ruby, and is still actively developped to reach its first real stable version ;-)