llm-context

Context management for long-context LLMs, agents, and vibe coding. Instantly build context for an entire repo, selected files, folders, and GitHub issues to generate structured AI-XML context with real-time token counting.

Open-source Rust TemporalStore for LLM context management, temporal features, and risk control

CLI tool to produce MD context files from many sources, to help interact with LLMs (ChatGPT, Llama3, Claude, etc.).

export any codebase to a single LLM-ready markdown prompt

Give any local LLM a billion-token memory. Open-source, local-first context + memory engine for Ollama and AI agents — runs on your own machine, free. 🧠⚡

Persistent, governed memory for chat clients, IDEs, & agents. Share memory across clients without losing scope, provenance, or auditability.

Turn any folder or Git repo into safe, token-efficient context for LLMs, AI chats, and coding agents like Claude Code, Codex, and Cursor — local-first GUI, TUI, CLI, and a read-only MCP server with Live Context, agent journal, Smart Ignore, secret/PII redaction, Git scopes, and code compression. Windows, macOS, Linux.

CodeStory is a codebase grounding engine that preindexes code into a knowledge graph and enriches it with semantic context. Paired with coding agents, it results in fewer tokens, fewer tool calls, and remains 100% local.

Rolling context compression for Claude Code — never hit the context wall. Auto-compresses old messages while keeping recent context verbatim. Zero config, zero latency. Works as a Claude Code plugin.

Memory management and retrieval for Claude Code

converts webpage content into Markdown format, optimized for LLM training and context

An MCP server that provides tools for exploring large OpenAPI schemas

Context-Optimized Memory Bank — Reduce AI token usage with structured documentation and cache-aware reading strategies

Research repository for TokenMizer, a graph-structured session-memory system for long-horizon LLM context management. This repository contains the benchmark suite, the labelled evaluation corpus, all raw results, and the manuscript for the associated paper.

AI Context Kit provides a structured, instruction-based framework for context-aware AI collaboration across LLM providers. It includes authoritative specs, canonical templates, and skills workflows for creating and validating user context and project AGENTS.md files.

🚀 A lightweight and convenient application that downloads any GitHub repository as a single, well-structured text file. Built with TypeScript, Node.js, GitHub REST API.

Clone any GitHub repo and flatten it into a file-tree diagram plus one consolidated code file - quick repo context for LLMs

Shared memory layer for AI coding tools. One local SQLite DB, every tool reads the same verified facts. Local-first, zero cloud.

Agent-readable knowledge base for reproducing and operating embodied-AI simulation toolchains. Five-layer docs (quickstart / concepts / field notes / troubleshooting / code), plus a cross-project layer of reproduction workflow, issue taxonomy, selection guide, best practices and terminology mapping.

Статический анализ выгрузок конфигураций 1С:Предприятие: индексирует метаданные, управляемые формы и BSL-модули в машиночитаемый контекст для LLM-инструментов. Python-библиотека и CLI.