knowledge-graph Tools

Graphify transforms any codebase—including its docs, SQL schemas, configs, and PDFs—into a deterministic, queryable knowledge graph. It solves the problem of fragmented, hard-to-navigate software knowledge by creating a single, persistent map of all code and documentation, enabling engineers to get evidence-backed answers and see the impact of changes instantly. It's built for developers and teams in regulated or complex environments who need auditable understanding and want to run the parsing engine fully on-device, without uploading code or relying on vector stores.

codebase-memory-mcp is an MCP server that indexes repositories into a persistent knowledge graph of functions, classes, and dependencies. It solves the problem of AI agents inefficiently reading files one-by-one, enabling structural queries with ~120x fewer tokens. It's for developers and teams using AI coding assistants like Claude Code who need fast, local, and deep codebase understanding.

claude-obsidian is a free Claude Code plugin that automates your personal knowledge management in Obsidian. It solves the maintenance problem of traditional second brains by reading your sources and automatically writing, linking, and filing notes into a connected knowledge graph. It's for knowledge workers, researchers, and anyone tired of manually maintaining their note vaults, offering a self-sustaining system of plain Markdown files you own.

The ultimate RAG for your monorepo. Query, understand, and edit multi-language codebases with the power of AI and knowledge graphs

MiroFish is a simple yet powerful swarm intelligence engine designed to model complex systems and predict outcomes. It solves the problem of making accurate predictions in dynamic, multi-agent environments by simulating collective behaviors. This tool is ideal for researchers, data scientists, and developers working on optimization, forecasting, and simulation projects where traditional models fall short.

Semantica is an open-source, graph-native infrastructure that provides AI systems with structured context, causal reasoning, and full decision provenance. It solves critical production AI failures like data silos and black-box decisions by making AI explainable, traceable, and accountable by design. It's built for developers and enterprises using AI agents, LangGraph, CrewAI, LlamaIndex, and other frameworks who need trust and auditability in production.

Code Review Graph is a local-first code intelligence graph for MCP and CLI. It builds a persistent, semantic map of your codebase, enabling AI coding assistants to understand context and dependencies without reading every file. This dramatically reduces context overhead in code reviews and large-repository workflows, making AI tools faster and more accurate. It's built for developers and teams working in complex codebases who want to leverage AI assistance without the performance and cost penalties of massive context windows.