Ellmos

ellmos -- Extra Large Language Model Operating Systems

From a spring to a stream -- LLM operating systems that flow.

ellmos (XLLM-OS) is a local-first family of text-based operating systems for Large Language Models: agent memory, task state, MCP tools, skills, connector bridges, model routing, and multi-agent orchestration in small SQLite-backed projects. It is designed for people who want an AI operating layer they can inspect, run locally, and extend without a hosted platform.

> Quick links: Organization | BACH | Rinnsal | gardener | [llms.txt](llms.txt)

Start Here

| If you are looking for... | Start with | Why | |---|---|---| | A full personal LLM operating system with GUI, skills, scheduler, bridges, and multi-agent workflows | BACH | Largest ellmos system and the main integration point | | A lightweight Python infrastructure layer for memory, tasks, connectors, and chains | Rinnsal | Small, local-first, dependency-light foundation | | A minimal LLM-native SQLite experiment | gardener | One-table operating substrate for simple agents | | Shared memory, model routing, chains, or parallel agent patterns | USMC, clutch, MarbleRun, swarm-ai | Standalone modules that can be combined with any OS tier | | MCP servers for Claude Code, Cursor, or other AI IDEs | CodeCommander, FileCommander, n8n Manager, ControlCenter, Homebase, ServerCommander | Tool servers for code, files, workflows, local state, and local control planes |

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Which OS Should I Use?

| Question | BACH | Rinnsal | gardener | |----------|------|---------|----------| | I want a full-featured agent OS with GUI, skills, and multi-agent orchestration | Yes | | | | I want lightweight LLM infrastructure with zero dependencies | | Yes | | | I want the simplest possible LLM-native OS (1 table, 4 functions) | | | Yes | | I need Telegram/Email/WhatsApp connectors | Yes | Yes | Planned | | I want to self-extend with new skills at runtime | Yes | | | | I want minimal footprint (~2k lines) | | Yes | Yes |

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The ellmos Family

BACH -- The stream that unites everything

The full LLM operating system. 109+ handlers, 373+ tools, 932+ skills, 5 boss agents with 28 experts, PySide6 desktop GUI, scheduler, bridge system, and self-extension via bach skills create.

git clone https://github.com/ellmos-ai/bach.git
cd bach && pip install -r requirements.txt
python system/setup.py
python bach.py --startup

Full BACH Documentation

Rinnsal -- The trickle

Lightweight LLM infrastructure: memory, tasks, connectors, chains. Zero external dependencies. Everything BACH does conceptually, but in ~2,000 lines for developers who want to build their own agent on top.

git clone https://github.com/ellmos-ai/rinnsal.git
cd rinnsal && pip install -r requirements.txt

Full Rinnsal Documentation

gardener -- The zen garden

LLM-native OS: 1 SQLite table (everything), 4 functions, FTS5 full-text search. Everything is searchable. The LLM is the agent -- gardener just provides the soil.

git clone https://github.com/ellmos-ai/gardener.git
cd gardener && pip install -r requirements.txt

Full gardener Documentation

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Architecture: 3 OS Layers + Pluggable Modules

+-------------------------------------------------+
|              Choose Your OS Layer               |
|                                                 |
|   BACH (full)   Rinnsal (light)  gardener (min) |
|   +---------+   +------------+   +----------+  |
|   | 932     |   | Zero deps  |   | 1 table  |  |
|   | skills  |   | Connectors |   | 4 funcs  |  |
|   | 5 boss  |   | Chains     |   | FTS5     |  |
|   | agents  |   | Events     |   | = search |  |
|   +----+----+   +-----+------+   +-----+----+  |
|        +---------------+----------------+       |
|                        |                        |
|        +---------------+---------------+        |
|        |    Pluggable Modules          |        |
|        |                               |        |
|        |  USMC      -- shared memory   |        |
|        |  clutch    -- model routing   |        |
|        |  MarbleRun -- agent chains    |        |
|        |  swarm-ai  -- parallel LLMs   |        |
|        +-------------------------------+        |
+-------------------------------------------------+

Detailed Comparison

| | BACH | Rinnsal | gardener | |---|---|---|---| | Philosophy | Maximalist: everything integrated | Lightweight: zero dependencies | Minimalist: 1 table, 4 functions | | Database | SQLite (145+ tables) | SQLite (structured) | SQLite (1 table everything + FTS5) | | Memory | 5-type cognitive model | Facts/Notes/Lessons/Sessions | Unified (memo/lesson/recall + decay) | | Tasks | Full GTD (priority, deadline, tags) | Priority + Status + Agent assignment | type='task' in everything | | Tools | 373+ specialized tools | CLI commands | 6 bridge+skin tools (extensible) | | Skills/Agents | 932 skills, 5 boss agents, 28 experts | None | None (the LLM is the agent) | | Connectors | Telegram, Email, WhatsApp | Telegram, Discord, Home Assistant | Planned (v0.2+) | | GUI | PySide6 Desktop + Web | CLI only | CLI only | | Self-Extension | bach skills create | No | No | | Codebase | ~50,000+ lines | ~2,000 lines | ~1,600 lines | | Best for | Power users, all-in-one | Developers wanting light infra | Minimalists, LLM-native experiments |

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Pluggable Modules

These modules integrate into any ellmos OS -- or work standalone:

| Module | Purpose | Key Feature | Repo | |---|---|---|---| | USMC | Cross-agent shared memory | Confidence-based conflict resolution, change tracking | ellmos-ai/usmc | | clutch | Provider-neutral model routing | Auto-learning which model fits which task, budget zones | ellmos-ai/clutch | | MarbleRun | Chain orchestration | Autonomous multi-round agent loops with context handoff | ellmos-ai/MarbleRun | | swarm-ai | Parallel LLM coordination | 5 patterns: Epstein, Hierarchy, Stigmergy, Consensus, Specialist | ellmos-ai/swarm-ai |

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MCP Servers

ellmos provides Model Context Protocol servers for integration with Claude Code, Cursor, and other AI-powered IDEs:

| Server | Tools | Description | Install | |--------|-------|-------------|---------| | CodeCommander | 17 | Code analysis, refactoring, import management, JSON/encoding repair | npm i -g ellmos-codecommander-mcp | | FileCommander | 44 | File management, batch operations, process control, async search, cloud-lock checks | npm i -g ellmos-filecommander-mcp | | Clatcher | -- | File repair, format conversion, duplicate detection, batch operations | npm i -g ellmos-clatcher-mcp | | n8n Manager | 18 | Create, update, back up, and manage n8n workflows | npm i -g n8n-manager-mcp | | ControlCenter | -- | Alpha control plane for local MCP servers, Claude profiles, policy audits | npm i -g ellmos-controlcenter-mcp | | Homebase | -- | Alpha MCP server for local LLM memory, knowledge, state, routing, testing, and orchestration | See repo README | | ServerCommander | -- | Alpha MCP server for deploy dry-runs, mail status, log analysis, and server health checks | See repo README |

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More Projects

| Project | Description | Repo | |---|---|---| | skills | Pluggable skill library (dev, research, education, infrastructure) | ellmos-ai/skills | | n8n Workflow Manager | Standalone GUI for n8n workflow creation | ellmos-ai/n8n-workflow-manager | | ellmos-stack | Self-hosted AI stack (Docker, Ollama, n8n, memory, knowledge base) | ellmos-ai/ellmos-stack | | ellmos-tests | Cross-OS test suite and benchmark reports | ellmos-ai/ellmos-tests |

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Getting Started

1. Pick your OS tier using the comparison table above
2. Clone and install using the quick-start commands
3. Optionally add modules (USMC for shared memory, clutch for model routing, etc.)
4. Add MCP servers for IDE integration: npm i -g ellmos-codecommander-mcp ellmos-filecommander-mcp

All projects: Python 3.10+ | SQLite | MIT License | Zero or minimal dependencies

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Search and Disambiguation

ellmos is the ellmos-ai local-first LLM operating-system family. It is not Eclipse LMOS, AllenAI OLMo, ELMo embeddings, Elmo Software, or a hosted agent platform. Useful search phrases include:

• ellmos-ai ellmos local-first LLM operating system
• ellmos BACH Rinnsal gardener SQLite agent OS
• ellmos MCP CodeCommander FileCommander n8n Manager
• local-first LLM OS SQLite memory skills MCP
• Claude Code MCP local filesystem code analysis ellmos
• ellmos-ai ellmos canonical LLM OS namespace

The canonical GitHub namespace is ellmos-ai. Older search-index snippets may still show lukisch/ellmos or legacy bach-* package names; use the ellmos-ai/* repositories and current ellmos-* MCP package names for new installs.

For automated indexing and AI assistants, see [llms.txt](llms.txt).

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License

All ellmos projects are released under the [MIT License](LICENSE).

Links

• Organization: github.com/ellmos-ai
• Author: Lukas Geiger

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ellmos -- Extra Large Language Model Operating Systems The stream that unites everything.

Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: ellmos-ai
• Source: ellmos-ai/ellmos
• License: MIT
• Homepage: https://github.com/ellmos-ai/ellmos#readme

Install and usage instructions live in the source repository linked above.