Tools tagged with "Knowledge graphs"

OpenLore helps developers keep AI coding agents grounded in large or unfamiliar repositories. It maps code relationships and retains architectural decisions so agents can find relevant context and check proposed changes.

llmwiki-cli gives AI agents a local Markdown wiki for building and maintaining a personal knowledge base. It's for people who want an agent to organize their information while keeping the wiki files on their own machine.

Palace gives AI coding agents persistent memory of project decisions, conventions and fixes. Developers can carry that context between sessions in Cursor, Claude Code, Codex and Claude Desktop.

LongMemory gives LLM applications and AI agents persistent memory across sessions. Developers can use it to retain project decisions and conversation context while distinguishing current facts from information that was true earlier.

Zengram gives AI agents a shared memory across sessions and machines. It's for people using multiple assistants who want a discovery recorded by one agent to be available to the others.

FlashRAG is an open source Python toolkit for researchers and developers comparing retrieval-augmented generation (RAG) methods or building their own. It combines implemented research methods with prepared benchmark datasets and reported results, so experiments don't have to start with a separate codebase for each approach. It uses the MIT license.

PentAGI automates authorized penetration testing for security engineers, researchers and red teams. Its specialized AI agents turn a target and a plain-language goal into testing work you can follow through a web interface.

MiniRAG is a Python framework for developers building question-answering tools over their own data with small language models. It targets on-device applications where larger models and heavier retrieval systems are difficult to use.

OpenContracts is a self-hosted document intelligence platform for teams working with legal archives, research libraries or internal policies. It connects documents through citations and annotations, giving people and AI agents a shared record of how source material relates. The code is open source under the MIT license; the public website also provides collections readers can browse.

Memorix keeps project memory for AI coding agents across chats and switches between tools. It's for developers who want decisions, fixes and unfinished work to remain available to the next session.

txtai is a Python framework for developers building search, chat with their data, and AI agents on their own hardware. It combines a searchable knowledge store with model workflows, so applications can retrieve context and act on it.

MEX keeps project knowledge alongside code so engineers and their AI coding agents can share context across teammates and sessions. Architecture, requirements and decisions live in readable Markdown that travels with the repository through Git.

LeanCTX helps developers control the information their AI coding tools receive. It runs locally between those tools and project files or command output, while your existing application keeps control of the model and workflow.

Kwipu helps people query a document folder or Obsidian vault and trace answers back to their notes. It connects information across documents so you can investigate project decisions, people and their roles, or relationships between ideas.

Ruflo is an AI agent framework for developers who want Claude Code and Codex to work as coordinated teams. It adds specialist roles and shared context for projects that involve coding, testing, architecture and documentation.

Code Graph RAG helps developers understand and change unfamiliar repositories, including monorepos that mix languages. It maps code relationships into a knowledge graph so questions and edits can use context across files.

Flexible GraphRAG is a self-hosted platform for teams building document search and AI chat that use both text and relationships between entities. It extracts knowledge graphs from documents and combines graph retrieval with vector similarity and full-text search. You can run it standalone or in Docker. It's open source under Apache 2.0.

SurrealDB is a database for developers building AI agents, knowledge graphs and applications with several kinds of data. It lets application records and retrieval data share one engine.

Atomic is a personal knowledge base for people who want to find connections across their notes and saved reading. It organizes Markdown notes, web clips, and articles into a knowledge graph you can search and explore.

Graphiti is a Python framework for developers building AI agents that need to remember information as it changes. It turns conversations, structured records and unstructured text into a queryable graph with a history of facts.

GrapeRoot is a local MCP context tool for developers using AI coding assistants on projects that require repeated file exploration. It selects relevant code before each prompt reaches the assistant and remembers earlier work.

LLM Wiki is a desktop AI knowledge base for people building a research library or personal reference collection. It creates lasting, linked pages from your documents and updates them as your sources change.

JARVIS RD Assistant is an open source, self-hosted workspace for researchers who want to search scientific literature and trace AI-generated answers back to papers. It runs on your own hardware with Ollama and connects literature review with PDF annotation, learning cards and research projects. It uses the Apache 2.0 license.

total-agent-memory gives AI coding agents persistent memory of decisions, fixes and project conventions across sessions and repositories. It's for developers who don't want to keep explaining earlier work to Claude Code, Codex CLI, Cursor or another MCP client.

Remembra Relay saves coding session handoffs so developers can switch assistants or resume a project on another machine without reconstructing its progress. The next agent receives a brief of completed work, unfinished tasks and failing checks.

WeKnora is a self-hosted AI knowledge platform for teams that want to query documents, carry out tasks using them and organize them into a wiki. These functions share the same knowledge bases.

PersonalClaw is a self-hosted AI agent for one person who wants chat, ongoing tasks and personal knowledge in one web dashboard. It runs on Linux and macOS, with Docker support that also covers Windows. It's open source under MIT and is currently pre-1.0, with breaking changes expected. A one-time download supplies a tiny CPU model for offline chat without tools. Autonomous tool work needs your own Ollama model or a provider app.

Tessera is a self-hosted literature review workspace for researchers who want to find papers, keep reading notes and compare findings in one browser interface.

SoloMD is a Markdown editor for writers, researchers and developers who want plain text notes with AI assistance. It combines a Typora-style writing interface with tools for searching a note collection and letting agents work on it.

PipesHub connects company knowledge to AI search and agents for teams whose files and conversations sit across business apps. It can also supply that context to coding assistants and custom applications.

M Flow is a self-hosted memory engine for developers whose AI agents need to recall past conversations and work preferences. It runs in Python or Docker and supports Ollama for local model use, alongside providers such as OpenAI and Anthropic. Choosing a cloud provider sends model requests to that service.

Memind gives AI agents long-term memory for projects, user preferences and past tasks. Developers can use it to carry context between sessions while keeping links to the material each memory came from.

Lumina Note is a Markdown note-taking app for people who want AI help with writing and organizing a note collection. Its agent can work across the vault with your permission, while notes remain plain files you can edit and back up outside the app.

Neo4j LLM Graph Builder converts documents and web content into knowledge graphs for people building searchable collections or AI applications with Neo4j. It uses an LLM to identify entities, relationships, and their properties.