Projects sharing features with MiMo Code

MemGPT is a memory management framework and external memory layer for large language models. It functions as a platform for building stateful AI agents that maintain a persistent identity and continuous context across multiple sessions. The system enables agents to bypass fixed context window limitations by using a virtual context windowing approach. This allows models to manage their own memory through internal commands to search, update, and delete stored information within a hierarchical structure of short-term working context and long-term archival storage. The framework provides a local

Claude Code is a command-line interface and multi-agent orchestration framework designed for autonomous software engineering. It enables AI agents to perform codebase modifications, debugging, and Git workflow management while coordinating multiple specialized agents to decompose and execute complex engineering tasks in parallel. The system distinguishes itself through a high degree of isolation and safety, utilizing Git worktrees to create independent working directories for concurrent agents and implementing a tiered permission system that combines user rules, project policies, and OS-level

This repository is a static analysis of the Claude Code terminal coding assistant, based on a reading of its TypeScript source. It documents how the agent is built, from its startup path and a single shared execution core to the streaming tool-call loop, sub-agents, and terminal interface layers. It is a reference and study resource about the agent rather than the agent itself. The analysis centers on a few areas. One is the shared core that routes queries, sub-agents, tools, and permission checks through the same control flow. Another is memory: layered, file-based records that users can ins

This repository is a study resource for the Claude Certified Architect Foundations exam. It brings together a written study guide, scenario-based practice questions, and Anki flashcard decks. The guide explains the exam format, the 100–1000 scoring scale with a passing score of 720, and the five weighted domains. It also covers realistic scenarios such as customer support agents, multi-agent research, code review pipelines, and structured data extraction. The curriculum covers designing tool-using agents. It explains how to build an agent loop driven by the model's stop reason, and how to coo

PraisonAI is an autonomous AI agent platform that coordinates multiple LLM-powered agents for research, planning, and execution of complex workflows. It functions as a multi-agent orchestration framework, a workflow builder, and a Model Context Protocol server, while also providing retrieval-augmented generation through vector knowledge bases. Agents can interact via CLI, web, or standardized protocols with sandboxed code execution. The platform distinguishes itself with a rich set of agent communication protocols, including A2A, REST, WebSocket, voice and telephony integration, and MCP, allo

This project is a structured educational resource and technical guide for designing and implementing autonomous systems using large language models. It provides a comprehensive curriculum and code samples focused on agentic design patterns, autonomous development, and the creation of systems capable of planning and executing multi-step tasks. The resource details the implementation of agentic retrieval-augmented generation, where models autonomously plan and refine data searches. It covers a wide array of orchestrators and design patterns, including metacognitive reflection for self-correctin

Cipher is an AI agent orchestration framework and LLM context memory layer. It provides a collaborative AI knowledge base and a context synchronization service that allows AI agents and CLI tools to maintain a persistent, structured memory of project decisions and codebase patterns across different sessions and machines. The system distinguishes itself through a version-controlled context model, using branches and commits to track how project knowledge evolves. It features a hierarchical knowledge store where information is organized as markdown files and can be synchronized between local env

Capsule Memory is a Rust library that gives AI agents durable, file-backed memory. Knowledge is kept in a plain file inside each project workspace, and the library reads that file every time a prompt is built and appends its contents to the language model's system context. Decisions, preferences, and project facts therefore carry over between separate sessions without being retyped. Because memory lives in ordinary files in the project folder, notes stay scoped to each project and are easy to read, edit, and version alongside the code. A size guard caps how much memory is injected. When conte

RedisInsight is a graphical user interface and management tool for browsing, analyzing, and administering Redis databases. It provides a visual environment for exploring key-value data structures, managing database instances, and performing data analysis across different operating systems and deployments. The tool distinguishes itself by providing dedicated visual managers for complex operations, including a vector database manager for configuring embeddings and similarity searches, a query workbench for executing raw commands and Lua scripts, and a performance monitoring dashboard for tracki

This project is a Rust-based AI agent framework and tool orchestrator that provides a command-line interface for interacting with large language models. It functions as an AI tool orchestrator that routes client requests to language servers and manages the planning and handoffs between specialized agents to solve complex tasks. The system distinguishes itself as a language porting validator, using deterministic mocks and specifications to verify feature parity between different language implementations of a codebase. It further extends agent capabilities by acting as a Model Context Protocol

Lazycodex is a plugin package that installs an agent harness into the Codex coding assistant with a single command. It adds planning, execution, review and diagnostic workflows to existing sessions, built around a plan-execute-verify loop: a decision-complete plan is drafted before any code is written, carried out step by step with progress saved after each item, and repeated until an independent reviewer confirms with concrete evidence that the work is finished. The harness also provides multi-agent orchestration. Specialist roles such as explorer, librarian and planner are adopted by child

Obsidian Mind is an Obsidian vault template that gives AI coding agents persistent, linked memory. Knowledge is stored as git-tracked markdown notes with frontmatter and wikilinks, so lessons, decisions and context carry over between sessions, repositories and machines. One shared instruction file, set of hook scripts and set of commands serve Claude Code, Codex CLI and Gemini CLI against the same notes. What sets it apart is how it manages agent context. A startup briefing loads goals, active projects, recent changes and open tasks under an enforced byte budget, shrinking low-value sections

ai-memory is a self-hosted long-term memory server for coding agents. It captures prompts, tool calls, and session boundaries through lifecycle hooks and compiles them into searchable, git-versioned markdown wiki pages that later sessions can recall. It also acts as a Model Context Protocol server, exposing search, recall, and page read and write operations over standard input and HTTP streaming, and it can run without any language model configured, using rule-based summaries. What sets it apart is that it works across vendors. An installer wires hooks, tool-server entries, routing instructio

This is a written reference for designing, building and operating production AI systems, aimed at engineers who work with large language models. It is organized as chapters, worked case studies and interview-preparation material rather than as installable software. The central topics are tool-using LLM agents, retrieval-augmented generation, cost and model selection, evaluation and observability, and security and compliance, with explicit trade-offs among latency, cost, accuracy and safety. The agent material covers control loops such as ReAct and plan-and-execute, graph-based orchestration,

Oh My Hermes (Hermes Orchestrator) is a workflow layer that sits on top of the Hermes agent runtime. It routes requests to staged skills, external coding executors, and verification gates, through chat or a terminal interface. Completion is evidence-gated: every status carries a stage and confidence, and work is marked verified only after tests, reviews, or CI checks have actually passed. It is also distributed as a catalog of installable workflow skills and plugin hooks, for Hermes and other coding-agent hosts. Its main focus is multi-agent coding delegation. Scoped tasks are handed to codin

pstack-claude is a plugin and skills pack for AI coding assistants. It bundles rigorous engineering workflows, step-by-step playbooks, routing hooks, model settings and subagent definitions, and translates them so the same content runs natively on many coding harnesses. Its skills are derived from upstream sources, with local forks and translations preserved and licensing provenance recorded. The distinctive parts are cross-harness porting and multi-agent orchestration. Tool names, model names and subagent types are pretranslated into each runtime's equivalents before installation, so nothing

ClaraVerse is a self-hostable AI chat workspace where users talk to cloud or local language models while keeping conversations, memories, and documents on their own infrastructure. It connects to hosted providers such as OpenAI, Anthropic, and Google as well as local servers like Ollama and LM Studio, and it accepts users' own API keys. Chat history is stored in the browser by default, with encrypted cloud sync available only if the user opts in. Beyond chat, the workspace coordinates teams of AI agents on shared tasks, with human review gates before any work is accepted. It includes a drag-a

This project provides a system for managing agent context and session memory, featuring an agent context compactor, an AI session memory manager, and a tool output sandbox. It functions as a middleware layer and server extension for the Model Context Protocol to optimize context windows and reduce token usage. The system optimizes agent performance by sandboxing tool outputs and externalizing large data sets, replacing raw I/O with pointers and concise summaries. It employs a persistent knowledge base that indexes session history and tool outputs for retrieval via full-text search, ensuring s

This project is an agentic development framework and autonomous software engineering system. It utilizes a coordinated network of specialized LLM agents to automate the full software development lifecycle, from codebase exploration and architectural planning to implementation and automated refactoring. The system is distinguished by an agentic memory system and a test-driven development orchestrator. It maintains project continuity across sessions by capturing architectural learnings and state in a persistent semantic database and enforces code quality through an automated cycle of generating

an ambient intelligence library

Headroom is an AI gateway proxy and token optimizer designed to reduce the cost and latency of large language model interactions. It functions as an intermediary that intercepts traffic between clients and providers to apply context compression, request routing, and format translation. The system differentiates itself through a Model Context Protocol server implementation that delivers compression and retrieval tools to compatible AI hosts. It employs a content-aware compression pipeline and tiered importance scoring to trim redundant data from logs and tool outputs while preserving essential

Vibe-coding is an agentic workflow manager and AI coding orchestrator designed to guide autonomous agents through software development. It serves as a development framework that organizes the process of building software using large language models through structured planning, iterative validation, and a defined cycle of implementation. The project distinguishes itself through a focused context management system and project memory bank, which uses dedicated files to maintain consistent architectural context across sessions. It employs constraint-based guidance to enforce project-specific codi

Toonflow-app is an agent orchestration platform designed to automate complex creative workflows and content production pipelines. It coordinates tiered hierarchies of agents to decompose tasks and transform scripts into storyboards and short-form comic videos. The platform features a non-linear infinite canvas workflow editor for arranging scripts and assets, supporting parallel production and backtracking. It utilizes a dynamic prompt manager that externalizes agent behaviors into markdown files for real-time tuning and a vector-based memory store to maintain consistent session context throu

Claude-mem is an agentic memory persistence system designed to provide AI assistants with long-term context across multiple development sessions. It functions as a background orchestrator that captures, summarizes, and indexes interaction history, allowing models to maintain continuity and recall technical decisions from past tasks. By utilizing a vector-augmented context engine, the system injects relevant historical observations into active sessions, ensuring that AI agents remain informed without exceeding finite token budgets. The project distinguishes itself through an endless memory arc

MemMachine is a centralized memory management server and model-agnostic memory layer for large language models. It functions as a persistence layer that stores user profiles and conversational context, providing a decoupled data store that prevents vendor lock-in by serving different AI models through a consistent API. The system implements the Model Context Protocol to share persistent agent memories and session data with compatible AI clients. It utilizes a multi-tiered memory hierarchy, combining a graph-based conversation store for episodic interactions with a vector knowledge base for se

This is an open-source Python SDK for building and orchestrating production-grade AI agents. It provides a unified framework for creating conversational agents that can use tools, maintain state, and coordinate across multiple language model providers including OpenAI, Anthropic, Google, Amazon Bedrock, and locally-hosted models. The SDK supports multi-agent orchestration through graphs, teams, and swarms, allowing several specialized agents to collaborate on complex tasks. Agents can be composed as callable tools that other agents invoke, and the framework includes policy handlers that inspe

This project is a conversational AI bot that integrates large language models into WeChat accounts to provide automated responses in private and group chats. Built on the WeChaty bot framework, it functions as a bridge that enables real-time conversational interactions between a messaging account and an AI model. The system acts as an AI multimedia gateway and context manager, supporting the generation of images from text and the transcription of audio files within the chat interface. It tracks interaction histories to manage token limits and maintains coherent conversations through custom sy