⚠️ This is Intuit's fork of MIRIX. The README below describes the upstream OSS project. For this fork's integration with the Enterprise Context & Memory Service (ECMS), see
CLAUDE.mdanddocs/ARCHITECTURE.md. Key differences:
- Screen activity capture is not used — memories come from conversations only.
- ECMS imports MIRIX as a Python library and does not run MIRIX's FastAPI app.
- Agent chaining is disabled; each agent runs exactly once per save.
- A provenance sidecar (
memory_source,memory_citation,source_message) is written alongside every memory (VEPAGE-760).
MIRIX - Multi-Agent Personal Assistant with an Advanced Memory System
Your personal AI that builds memory through screen observation and natural conversation
| 🌐 Website | 📚 Documentation | 📄 Paper | 💬 Discord
Key Features 🔥
- Multi-Agent Memory System: Six specialized memory components (Core, Episodic, Semantic, Procedural, Resource, Knowledge Vault) managed by dedicated agents
- Screen Activity Tracking: Continuous visual data capture and intelligent consolidation into structured memories
- Privacy-First Design: All long-term data stored locally with user-controlled privacy settings
- Advanced Search: PostgreSQL-native BM25 full-text search with vector similarity support
- Multi-Modal Input: Text, images, voice, and screen captures processed seamlessly
Quick Start
Step 1: Backend & Dashboard (Docker):
docker compose up -d --pull always
- Dashboard: http://localhost:5173
- API: http://localhost:8531
Step 2: Create an API key in the dashboard (http://localhost:5173) and set as the environmental variable MIRIX_API_KEY.
Step 3: Client (Python, mirix-client, https://pypi.org/project/mirix-client/):
pip install mirix-client
Now you are ready to go! See the example below:
from mirix import MirixClient
client = MirixClient(
api_key="your-api-key",
base_url="http://localhost:8531",
)
client.initialize_meta_agent(
config={
"llm_config": {
"model": "gemini-2.0-flash",
"model_endpoint_type": "google_ai",
"api_key": "your-api-key-here",
"model_endpoint": "https://generativelanguage.googleapis.com",
"context_window": 1_000_000,
},
"embedding_config": {
"embedding_model": "text-embedding-004",
"embedding_endpoint_type": "google_ai",
"api_key": "your-api-key-here",
"embedding_endpoint": "https://generativelanguage.googleapis.com",
"embedding_dim": 768,
},
"meta_agent_config": {
"agents": [
{
"core_memory_agent": {
"blocks": [
{"label": "human", "value": ""},
{"label": "persona", "value": "I am a helpful assistant."},
]
}
},
"resource_memory_agent",
"semantic_memory_agent",
"episodic_memory_agent",
"procedural_memory_agent",
"knowledge_vault_memory_agent",
],
},
}
)
client.add(
user_id="demo-user",
messages=[
{"role": "user", "content": [{"type": "text", "text": "The moon now has a president."}]},
{"role": "assistant", "content": [{"type": "text", "text": "Noted."}]},
],
)
memories = client.retrieve_with_conversation(
user_id="demo-user",
messages=[
{"role": "user", "content": [{"type": "text", "text": "What did we discuss on MirixDB in last 4 days?"}]},
],
limit=5,
)
print(memories)
For more API examples, see samples/run_client.py.
License
Mirix is released under the Apache License 2.0. See the LICENSE file for more details.
Contact
For questions, suggestions, or issues, please open an issue on the GitHub repository or contact us at founders@mirix.io
Join Our Community
Connect with other Mirix users, share your thoughts, and get support:
💬 Discord Community
Join our Discord server for real-time discussions, support, and community updates: https://discord.gg/S6CeHNrJ
🎯 Weekly Discussion Sessions
We host weekly discussion sessions where you can:
- Discuss issues and bugs
- Share ideas about future directions
- Get general consultations and support
- Connect with the development team and community
📅 Schedule: Friday nights, 8-9 PM PST
🔗 Zoom Link: https://ucsd.zoom.us/j/96278791276
📱 WeChat Group
You can add the account ari_asm so that I can add you to the group chat.
Acknowledgement
We would like to thank Letta for open-sourcing their framework, which served as the foundation for the memory system in this project.
1 maintainer
Metadata
1 maintainer
Release files for jl-ecms-client 0.91.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| jl_ecms_client-0.91.0.tar.gz | 96.6 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| jl_ecms_client-0.91.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 215.0 kB
Release files / jl_ecms_client-0.91.0.tar.gz
| Download URL | jl_ecms_client-0.91.0.tar.gz |
|---|---|
| Size | 96.6 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
ed6a7c2697451598ad2e6815145de38b26dd0feaf01377c14befedf82928589b
|
|
BLAKE2b-256 checksum How to use checksums |
ac13cce707cfcbcb67d405a1376a94e42a8eaf6ff2ddc3c8acf8c4ffee2bbd3e
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.12.13
|
Release files / jl_ecms_client-0.91.0-py3-none-any.whl
| Download URL | jl_ecms_client-0.91.0-py3-none-any.whl |
|---|---|
| Size | 118.4 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
ab692ad2388c9b50e99df7bb51406b1cc47c80f9e654742dc8e4b901ee358af5
|
|
BLAKE2b-256 checksum How to use checksums |
ae29a7d9727aa92cecc1a0fb62a5f23e39c76d90b9bd3a41a345e5b3eb88801f
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.12.13
|
