Atlantis

Atlas is a desktop application for source control and shared context across coding-agent sessions, developed by Pacifio. It runs Claude Code, Codex, its native agent, and agents from the ACP registry against a codebase, recording prompts, tool calls, file changes, and patches in local session storage. When a commit is created, Atlas links it to the session that produced it, preserving those checkpoint relationships through rebases and amends and allowing the session to be queried later. Before sending a prompt, Atlas resolves local @ mentions, combines project notes and agent memory, performs on-device semantic retrieval, and can add a handoff from a previous session. Markdown knowledge files, CLAUDE.md, AGENTS.md, plans, decisions, failures, file changes, skills, papers, and past sessions can therefore be shared between agents. The application also provides a code editor, Git operations and diffs, a terminal, a project knowledge base, research tools, a browser, spatial boards, and agent activity history. Atlas is local by default: code, notes, and sessions remain on the machine, secrets are scrubbed before persistence, and local mode works without an account or network. Optional organisations can sync across devices and teammates. The repository states that macOS is the supported platform; Linux and Windows builds are untested. It is distributed under the MIT license.

SwarmForge is a local, tmux-based orchestration platform for coordinating multiple AI agents across Git worktrees. It reads a project-local configuration that assigns roles, agent backends, worktrees, task or batch handling, and handoff propagation; launches each role in an isolated tmux session; and provides a browser-based pack cockpit for projects, tasks, approvals, clarifications, live status, agent-pane inspection, and teardown. Agents communicate through a daemon-delivered handoff protocol and helper scripts rather than direct tmux messages. The repository supplies two-pack, four-pack, and six-pack workflow templates with role prompts and constitution articles, while projects can define their own swarm topology. It runs locally with zsh, Git, tmux, Babashka, and at least one supported agent backend such as Claude, Codex, Copilot, or Grok; swarm state is kept in the working director

PentAGI is a self-hosted, AI-powered penetration-testing platform for security professionals, researchers, and ethical hackers. It uses a multi-agent system with specialized researcher, developer, executor, adviser, planner, and reflector roles to investigate targets, plan and execute testing tasks, operate professional security tools, and generate vulnerability reports. The platform runs operations in isolated Docker containers and includes more than 20 security tools, an isolated web scraper, external search integrations, PostgreSQL with pgvector for persistent results and semantic memory, and an optional Graphiti/Neo4j knowledge graph. Its agents use long-term, working, and episodic memory; chain summarization converts conversation chains into a structured ChainAST, summarizes older sections and oversized pairs, and rebuilds the chain when the result is smaller. Optional execution monitoring detects repeated or excessive tool calls and invokes a mentor for alternative strategies, while task planning decomposes a request into actionable subtasks before specialist agents execute it. PentAGI provides a React and TypeScript web interface, Go-based REST and GraphQL APIs with Bearer-token authentication, flow-scoped file management, Markdown and PDF report downloads, and monitoring integrations built around OpenTelemetry, Grafana, VictoriaMetrics, Jaeger, and Loki. It supports multiple hosted and local LLM providers, including OpenAI, Anthropic, Google Gemini, AWS Bedrock, Ollama, DeepSeek, GLM, Kimi, Qwen, and MiniMax, and can be deployed with Docker Compose or Podman. The project states that it is an autonomous and assistant-guided penetration-testing platform rather than a CALDERA-style breach-and-attack-simulation system with predefined campaigns; testing should be limited to systems for which the operator has authorization.

TeamAI is an open-source CLI for managing a team's skills, rules, documentation, agents, hooks, MCP configuration, environment settings, and knowledge across AI coding tools such as Claude Code, Codex, Cursor, CodeBuddy, WorkBuddy, and OpenCode. It is installed with npm as `teamai-cli` and uses a shared Git repository as the team's source of truth. The CLI distributes resources through an administrative `push` → review and merge → `pull` workflow. Session-start hooks can run `teamai pull` to synchronize the shared harness into project- or user-scoped local AI-tool directories; roles, tags, and subscribed source repositories control which resources members receive. TeamAI also provides a knowledge layer: `teamai import` and `teamai codebase` build a searchable team knowledge base and codebase graph, while `teamai recall` uses BM25 search with graph-boosted reranking and can deploy a recall subagent into supported AI tools. Code relationships are extracted with a WebAssembly tree-sitter parser for TypeScript/JavaScript, Python, and Go, with regex-based heuristic extraction as a fallback and for other languages. Additional commands support friction-based learning suggestions, privacy-scrubbed session summaries, maintenance of stale or low-confidence knowledge, usage digests, a web dashboard, member and role management, package and plugin installation, diagnostics, and uninstallation. The repository is maintained by Tencent and contributors and is licensed under MIT.

camelAI is an AI coding assistant platform built on Cloudflare Workers and Durable Objects. Each chat thread runs a coding agent in its own persistent workspace, retaining chat state and project files while providing workspace-aware tools. The platform connects to APIs, databases, email, Slack, Discord, and other services; supports application builds, notebook analysis, and SQL execution in isolated short-lived sandboxes; and provides previews and publishing through Workers for Platforms. Its agent harness is built on pi's lower-level agent-loop and state-management libraries. The agent uses native file tools and writes JavaScript rather than shell commands; Code Mode executes that JavaScript in fresh V8 isolates with explicit platform and connection methods. Project files are stored in WorkspaceFilesystem Durable Objects, using Durable Object SQLite for small files and R2 for larger ones, while Cloudflare Artifacts provides Git history. Linux sandbox containers are reserved for jobs requiring them, including builds, notebook analysis, and database queries, and credentials remain outside the execution sandbox. The platform can use Anthropic, OpenAI, OpenRouter, Bedrock, and custom model endpoints. Its repository is released under the MIT License and includes local development setup using Node.js, Bun, and a Cloudflare account.