https://github.com/evermind-ai/everos
One portable memory layer for every AI agent: local-first, Markdown-native, user-owned, and self-evolving across apps, tools, and workflows.
https://github.com/evermind-ai/everos
agent-memory agentic-ai ai chats clawdbot clawdbot-skill llm long-term-memory mcp memory memory-management python3 rag skills
Last synced: 1 day ago
JSON representation
One portable memory layer for every AI agent: local-first, Markdown-native, user-owned, and self-evolving across apps, tools, and workflows.
- Host: GitHub
- URL: https://github.com/evermind-ai/everos
- Owner: EverMind-AI
- License: apache-2.0
- Created: 2025-10-28T15:09:32.000Z (8 months ago)
- Default Branch: main
- Last Pushed: 2026-07-03T00:51:19.000Z (6 days ago)
- Last Synced: 2026-07-03T02:24:53.566Z (6 days ago)
- Topics: agent-memory, agentic-ai, ai, chats, clawdbot, clawdbot-skill, llm, long-term-memory, mcp, memory, memory-management, python3, rag, skills
- Language: Python
- Homepage: https://evermind.ai/everos
- Size: 2.23 MB
- Stars: 10,078
- Watchers: 109
- Forks: 831
- Open Issues: 41
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
- Citation: CITATION.md
- Security: SECURITY.md
- Notice: NOTICE
Awesome Lists containing this project
- awesome-ChatGPT-repositories - EverOS - Self-evolving memory across Agent and platform. The one portable memory layer for every agent they use - Claude Code, Codex, OpenClaw, Hermes, and more (The latest additions π / Usage)
README
[Website](https://evermind.ai) Β· [Documentation](https://docs.evermind.ai) Β· [Blog](https://evermind.ai/blogs) Β· [δΈζ](README.zh-CN.md)
Table of Contents
- [Why Ever OS](#why-ever-os)
- [Quick Start](#quick-start)
- [Use Cases](#use-cases)
- [Documentation](#documentation)
- [Star Us](#star-us)
- [EverMind Ecosystems](#evermind-ecosystems)
- [Contributing](#contributing)
## Why Ever OS
EverOS is a Python library and local-first memory runtime for agents and
makers. It gives one portable memory layer across coding assistants, apps,
devices, and workflows from day one. It stores conversations, files, and agent
trajectories as readable Markdown, then syncs local SQLite and LanceDB indexes
for fast retrieval and self-evolving reuse.
Title
EverOS
Other Agent Memory Libraries
Markdown source of truth
β
Canonical .md files that are readable, editable, diffable, and Git-versioned
β Usually API, vector, graph, dashboard, or database state
Direct file editing
β
Edit .md files; cascade watcher syncs
β Usually SDK, API, dashboard, or backend update paths
Local three-part stack
β
Markdown + SQLite + LanceDB; no MongoDB, Elasticsearch, or Redis required
β Often depends on managed services, vector DBs, graph DBs, or server stacks
User + agent tracks
β
User episodes/profile and agent cases/skills are separate first-class surfaces
β Usually centered on chat history, profiles, entities, facts, or retrieval records
Orthogonal retrieval
β
Search by user_id, agent_id, app_id, project_id, and session_id
β Usually app, namespace, tenant, thread, or graph scoped
Knowledge Wiki
β
Editable, source-backed Markdown knowledge pages with taxonomy, CRUD APIs, and topic search
β Usually separate from memory, trapped in a dashboard, or not tied back to source files
Reflection
β
Offline memory evolution that merges episode clusters and refines profiles and skills between sessions
β Usually retrieval-only memory with little background consolidation or long-horizon improvement
## Quick Start
> Goal: play with the memory visualizer first, then start EverOS, write one
> real memory, and search it back.
### 0. Prerequisites
- Python 3.12+
- No API keys are needed for `everos demo`.
- To run the real server-backed memory flow, create two provider keys before
`everos init`:
| Capability | Provider | Used for | Fill these `.env` slots |
| --- | --- | --- | --- |
| Chat + multimodal | [OpenRouter](https://openrouter.ai/) | `LLM` / `MULTIMODAL` | `EVEROS_LLM__API_KEY`, `EVEROS_MULTIMODAL__API_KEY` |
| Embedding + rerank | [DeepInfra](https://deepinfra.com/) | `EMBEDDING` / `RERANK` | `EVEROS_EMBEDDING__API_KEY`, `EVEROS_RERANK__API_KEY` |
You can use other OpenAI-compatible providers by changing the matching
`*__BASE_URL` fields in `.env`.
### 1. Install
```bash
uv pip install everos
# or: pip install everos
```
### 2. Play With The Demo
Run this before configuring API keys or starting the server:
```bash
everos demo
```
The command asks for one memory and one recall question, then opens a
full-screen terminal UI. This is an educational visualizer: it is hardcoded,
local to the CLI, and does not connect to the EverOS server. Its job is to make
the memory lifecycle visible: conversation -> memory sphere -> recall -> source
proof -> confetti. See [docs/everos-demo.md](docs/everos-demo.md) for the demo
scope and TUI source layout.
The sphere moves through ingest, extraction, indexing, recall, source reveal,
and a confetti burst after the first memory lands. Press `r` to replay and `q`
to quit.
For the looping showroom view used in README media, run:
```bash
everos demo --cinematic
```
If your shell is not interactive, or you want a copyable preview, use:
```bash
everos demo --plain
```
### 3. Configure
Generate a starter `.env` file, then fill the four API key slots shown in the
generated comments. With the default setup, paste your OpenRouter key into the
`LLM` / `MULTIMODAL` slots and your DeepInfra key into the `EMBEDDING` /
`RERANK` slots.
```bash
everos init
# or, from a source checkout:
cp .env.example .env
```
`everos init` writes `./.env` by default. Use `everos init --xdg` to
write `${XDG_CONFIG_HOME:-~/.config}/everos/.env` instead.
### 4. Start EverOS
```bash
everos server start
```
Keep the server running, then open a second terminal and check it:
```bash
curl http://127.0.0.1:8000/health
```
Expected response:
```json
{"status":"ok"}
```
`everos server start` searches for `.env` in this order: `--env-file ` β
`./.env` (cwd) β `${XDG_CONFIG_HOME:-~/.config}/everos/.env` β `~/.everos/.env`.
The endpoint stack is OpenAI-protocol compatible (OpenAI / OpenRouter / vLLM /
Ollama / DeepInfra) - override `*__BASE_URL` in the generated `.env` to point
at any of them.
Now make the demo real. In the second terminal, run:
```bash
everos demo --live
```
Live demo mode connects to the running server and performs the real
`/health` -> `/api/v1/memory/add` -> `/api/v1/memory/flush` ->
`/api/v1/memory/search` flow before opening the same memory sphere UI. Use
`--server-url ` if your server is not on `http://127.0.0.1:8000`.
### 5. Try Your First Memory
Add a tiny conversation:
```bash
TS=$(($(date +%s)*1000))
curl -X POST http://127.0.0.1:8000/api/v1/memory/add \
-H 'Content-Type: application/json' \
-d "{
\"session_id\": \"demo-001\",
\"app_id\": \"default\",
\"project_id\": \"default\",
\"messages\": [
{\"sender_id\": \"alice\", \"role\": \"user\", \"timestamp\": $TS, \"content\": \"I love climbing in Yosemite every spring.\"},
{\"sender_id\": \"alice\", \"role\": \"user\", \"timestamp\": $((TS+10000)), \"content\": \"My favorite coffee shop is Blue Bottle in SOMA.\"}
]
}"
```
Force extraction for the local demo:
```bash
curl -X POST http://127.0.0.1:8000/api/v1/memory/flush \
-H 'Content-Type: application/json' \
-d '{"session_id":"demo-001","app_id":"default","project_id":"default"}'
```
Search it back:
```bash
curl -X POST http://127.0.0.1:8000/api/v1/memory/search \
-H 'Content-Type: application/json' \
-d '{
"user_id": "alice",
"app_id": "default",
"project_id": "default",
"query": "Where do I like to climb?",
"top_k": 5
}'
```
You should see the Yosemite memory in the response. If the result is empty on
the first try, wait a moment and retry; Markdown is written synchronously, while
the local index catches up in the background.
> [!TIP]
> **First memory unlocked.**
> You just gave EverOS a fact, flushed it into durable Markdown-backed memory,
> and searched it back through the local index. That is the core loop.
> Want to see the source of truth? Open `~/.everos` and inspect the generated
> Markdown files.
For annotated responses and the Markdown files EverOS creates, see
[QUICKSTART.md](QUICKSTART.md).
### Optional: Ingest Multimodal Files
To ingest non-text content (image / pdf / audio / office documents)
through `/api/v1/memory/add` `content` items, install the optional
extra:
```bash
uv pip install 'everos[multimodal]' # or: pip install 'everos[multimodal]'
```
This pulls in `everalgo-parser` (with the `[svg]` bundle for SVG
support via cairosvg) and wires up the multimodal LLM client
(`EVEROS_MULTIMODAL__*` fields in `.env`, defaults to
`google/gemini-3-flash-preview` via OpenRouter).
**Office document support requires LibreOffice as a system dependency.**
The parser shells out to `soffice` (LibreOffice's headless renderer) to
convert `.doc` / `.docx` / `.ppt` / `.pptx` / `.xls` / `.xlsx` to PDF
before feeding the result into the multimodal LLM. Without LibreOffice,
office uploads return HTTP 415 with a clear error message; PDF / image
/ audio / HTML / email parsing is unaffected.
Install on the host before serving office documents:
```bash
brew install --cask libreoffice # macOS
sudo apt-get install -y libreoffice # Debian / Ubuntu
```
### For Contributors
```bash
git clone https://github.com/EverMind-AI/EverOS.git
cd EverOS
uv sync # creates ./.venv and installs deps
source .venv/bin/activate # or prefix commands with `uv run`
everos demo --plain # try the local educational demo; no API keys needed
everos init # paste OpenRouter + DeepInfra keys into .env
everos --help
make test
```
[](#readme-top)
## Use Cases
Now that you have had your first successful EverOS moment, explore what people
are building with persistent memory across agents, apps, and community
integrations.
Use cases show what persistent memory makes possible in real products and
workflows. Some examples are packaged in this repository; others point to
external demos or integrations you can study and adapt.
[](https://evermind.ai/usecase_reunite)
#### Reunite - Find With EverOS
Parents describe what they remember. Children describe what they recall. Reunite uses semantic memory to surface the connections.
[Learn more](https://evermind.ai/usecase_reunite)
[](https://github.com/tt-a1i/hive)
#### Hive Orchestrator
Browser-native hive-mind for CLI coding agents - Claude Code, Codex, Gemini, and OpenCode collaborate as real PTY processes via a team protocol.
[Code](https://github.com/tt-a1i/hive)
[](https://github.com/tt-a1i/evermemos-mcp)
#### AI Coding Assistants With EverOS
Universal long-term memory layer for AI coding assistants, powered by EverOS.
[Code](https://github.com/tt-a1i/evermemos-mcp)
[](https://github.com/yuansui123/AI-Data-Technician-EverMemOS)
#### AI Data Technician
An agentic AI system that learns from scientist interaction to inspect, analyze, and classify high-dimensional time series data - with persistent memory that improves across sessions.
[Code](https://github.com/yuansui123/AI-Data-Technician-EverMemOS)
#### Rokid AI Assistant With EverOS
Connect to EverOS within Rokid Glasses enabling long-term memory for all of your smart activities.
Coming soon
#### Creative Assistant With Memory
Creative assistant with long-term memory, so your creative context stays available across sessions.
Coming soon
[](https://github.com/xunyud/Earth-Online)
#### Earth Online Memory Game
Earth Online is a memory-aware productivity game that turns everyday planning into a living quest log.
[Code](https://github.com/xunyud/Earth-Online)
[](https://github.com/golutra/golutra)
#### Multi-Agent Orchestration Platform
Golutra presents a multi-agent workforce for engineering teams, extending the IDE model from a single assistant to coordinated agents.
[Code](https://github.com/golutra/golutra)
[](https://github.com/Yangtze-Seventh/taste-verse)
#### Your Personal Tasting Universe
Record, visualize, and explore your tasting journey through an immersive 3D star map.
[Code](https://github.com/Yangtze-Seventh/taste-verse)
[](https://github.com/kellyvv/OpenHer)
#### EverOS Open Her
Build AI that feels. Open-source persona engine - personality emerges from neural drives, not prompts. Inspired by Her.
[Code](https://github.com/kellyvv/OpenHer)
[](https://chromewebstore.google.com/detail/ruminer-browser-agent/lbccjohfpdpimbhpckljimgolndfmfif)
#### Browser Agent For Personal Memory
Ruminer brings persistent memory to a browser agent so it can carry personal context across web tasks.
[Plugin](https://chromewebstore.google.com/detail/ruminer-browser-agent/lbccjohfpdpimbhpckljimgolndfmfif)
[](https://github.com/nanxingw/EverMem)
#### EverMem Sync With EverOS
One command to connect any AI coding CLI to EverMemOS long-term memory.
[Code](https://github.com/nanxingw/EverMem)
[](https://github.com/mco-org/mco)
#### MCO - Orchestrate AI Coding Agents
MCO equips your primary agent with an agent team that can work together to solve complex tasks.
[Code](https://github.com/mco-org/mco)
[](https://github.com/onenewborn/StudyBuddy-public)
#### Study Buddy With Self-Evolving Memory
Study proactively with an agent that has self-evolving memory.
[Code](https://github.com/onenewborn/StudyBuddy-public)
[](https://github.com/TonyLiangDesign/MemoCare)
#### Alzheimer's Memory Assistant
Empowering individuals with advanced memory support and daily assistance.
[Code](https://github.com/TonyLiangDesign/MemoCare)
[](https://github.com/AlexL1024/NeuralConnect)
#### Memory-Driven Multi-Agent NPC Experience
An iOS sci-fi mystery game where players explore and uncover the truth.
[Code](https://github.com/AlexL1024/NeuralConnect)
[](https://github.com/elontusk5219-prog/Mobi)
#### Mobi Companion
An iOS app where users create, nurture, and live with a personalized AI companion called Mobi.
[Code](https://github.com/elontusk5219-prog/Mobi)
[](https://github.com/JaMesLiMers/EvermemCompetition-Spiro)
#### AI Wearable With Memory
A context-native AI wearable that listens to everyday life and converts conversations into memory.
[Code](https://github.com/JaMesLiMers/EvermemCompetition-Spiro)
[](docs/migration-to-1.0.0.md)
#### Legacy OpenClaw Agent Memory
Archived pre-1.0.0 plugin reference. New integrations should use the current EverOS API.
[Learn more](docs/migration-to-1.0.0.md)
[](https://github.com/TEN-framework/ten-framework/tree/04cb80601374fa9e35b4e544b2dbd23286ca7763/ai_agents/agents/examples/voice-assistant-with-EverMemOS)
#### Live2D Character With Memory
Add long-term memory to a real-time Live2D character, powered by [TEN Framework](https://github.com/TEN-framework/ten-framework).
[Code](https://github.com/TEN-framework/ten-framework/tree/04cb80601374fa9e35b4e544b2dbd23286ca7763/ai_agents/agents/examples/voice-assistant-with-EverMemOS)
[](https://screenshot-analysis-vercel.vercel.app/)
#### Computer-Use With Memory
Run screenshot-based analysis with computer-use and store the results in memory.
[Live Demo](https://screenshot-analysis-vercel.vercel.app/)
[](use-cases/game-of-throne-demo)
#### Game Of Thrones Memories
A demonstration of AI memory infrastructure through an interactive Q&A experience with *A Game of Thrones*.
[Code](use-cases/game-of-throne-demo)
[](use-cases/claude-code-plugin)
#### Claude Code Plugin
Persistent memory for Claude Code. Automatically saves and recalls context from past coding sessions.
[Code](use-cases/claude-code-plugin)
[](https://main.d2j21qxnymu6wl.amplifyapp.com/graph.html)
#### Memory Graph Visualization
Explore stored entities and relationships in a graph interface. Frontend demo; backend integration is in progress.
[Live Demo](https://main.d2j21qxnymu6wl.amplifyapp.com/graph.html)
[](#readme-top)
## Documentation
- [docs/everos-demo.md](docs/everos-demo.md) β Demo scope and TUI source layout
- [docs/how-memory-works.md](docs/how-memory-works.md) β Markdown, SQLite, LanceDB, and recall flow
- [docs/use-cases.md](docs/use-cases.md) β Full use-case gallery and integration examples
- [docs/engineering.md](docs/engineering.md) β Contributor engineering reference: build, test, CI, conventions
- [docs/migration-to-1.0.0.md](docs/migration-to-1.0.0.md) β Legacy API migration notes
- [CHANGELOG.md](CHANGELOG.md) β Release notes
- [CONTRIBUTING.md](CONTRIBUTING.md) β How to contribute
[](#readme-top)
## Star Us
If EverOS is useful to your agent stack, please star the repo. It helps more
builders discover the project and gives the memory ecosystem a stronger signal
to keep improving.
### Star History
[](https://www.star-history.com/#EverMind-AI/EverOS&Date)
[](#readme-top)
## EverMind Ecosystems
EverMind is an open-source ecosystem for long-term memory, self-evolving
agents, AI-native interfaces, and memory evaluation.
EverMind Open-Source Ecosystem
Memory Runtime
EverOS - the local memory operating system and research-backed runtime for agent and user memory.
Self-Improving Agent Harness
Raven - the self-improving agent harness that brings memory, proactivity, context control, and skill evolution into terminal-native agents.
Algorithm Engine
EverAlgo - stateless extraction, ranking, parsing, and memory operators that power EverOS.
Hypergraph Memory
HyperMem - hypergraph memory for long-term conversations, with its own benchmark-backed topic -> episode -> fact retrieval method.
Benchmarks
EverMemBench Β· EvoAgentBench - evaluation suites for conversational memory and agent self-evolution.
Long-Context Research
MSA - Memory Sparse Attention for scalable latent memory and 100M-token contexts.
Personal Memory Layer
EverMe - CLI and agent plugin suite for cross-device, cross-agent personal memory.
Developer Integrations
evermem-claude-code Β· everos-plugins - plugins, skills, and migration tooling for AI coding agents.
Together, these repositories form EverMind's research-to-runtime stack: new memory methods, reusable algorithms, benchmark evidence, and practical agent integrations.
[](#readme-top)
## Contributing
Contributions are welcome across the whole repository: memory methods, benchmark coverage, use-case examples, documentation, and bug fixes. Browse [Issues](https://github.com/EverMind-AI/EverOS/issues) to find a good entry point, then open a PR when you are ready.
> [!TIP]
>
> **Welcome all kinds of contributions** π
>
> Help make EverOS better. Code, documentation, benchmark reports, use-case write-ups, and integration examples are all valuable. Share your projects on social media to inspire others.
>
> Connect with one of the EverOS maintainers [@elliotchen200](https://x.com/elliotchen200) on π or [@cyfyifanchen](https://github.com/cyfyifanchen) on GitHub for project updates, discussions, and collaboration opportunities.
### Code Contributors
[](https://github.com/EverMind-AI/EverOS/graphs/contributors)
### License
[Apache License 2.0](LICENSE) β see [NOTICE](NOTICE) for third-party attributions.
### Citation
If you use EverOS in research, see [CITATION.md](CITATION.md).
[](#readme-top)