Metadata-Version: 2.4
Name: selfmemory
Version: 0.4.3.post7
Summary: Enhanced Memory Management for AI Agents with zero-setup simplicity
Author-email: SelfMemory Team <shrijayan@cpluz.com>
Maintainer-email: SelfMemory Team <shrijayan@cpluz.com>
License-Expression: Apache-2.0
Project-URL: Homepage, https://selfmemory.com
Project-URL: Repository, https://github.com/selfmemory/selfmemory
Project-URL: Documentation, https://github.com/selfmemory/selfmemory/wiki
Project-URL: Issues, https://github.com/selfmemory/selfmemory/issues
Project-URL: Changelog, https://github.com/selfmemory/selfmemory/blob/main/CHANGELOG.md
Keywords: memory,ai,ml,vector,search,embeddings,agents,llm,artificial-intelligence,qdrant,semantic-search
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Topic :: Database :: Database Engines/Servers
Classifier: Topic :: Text Processing :: Indexing
Classifier: Typing :: Typed
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Description-Content-Type: text/markdown
License-File: LICENSE.txt
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Requires-Dist: mcp[cli]>=1.13.0
Provides-Extra: enterprise
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Dynamic: license-file

# SelfMemory

**Store AI memories for you and your agents**

It is a open-source universal memory engine where users can store and retrieve their AI conversations and context across different models. Users can add memories through MCP, SDK, or a website selfmemory.com Over time, this will evolve into a one-stop memory hub with note-taking and chatbot features. For B2B, it becomes a knowledge backbone, storing project context, organizational knowledge, documents, and data sources to power company-wide AI systems.

## 🚀 Quick Start

```bash
pip install selfmemory
```

```python
from selfmemory import SelfMemory

memory = SelfMemory()

# Add memories
memory.add("I have a BMW bike.", user_id="demo")

# Search memories
results = memory.search("bike", user_id="demo")
print(results)
```

## 📚 Full Documentation

**Visit [docs.selfmemory.com](https://docs.selfmemory.com) for complete documentation, guides, and examples.**
**Changelog**: See [CHANGELOG.md](CHANGELOG.md) for a detailed list of changes and updates.

## 🔗 Links

- **Documentation**: [docs.selfmemory.com](https://docs.selfmemory.com)
- **GitHub**: [github.com/selfmemory/selfmemory](https://github.com/selfmemory/selfmemory)
- **Discord**: [discord.com/invite/YypBvdUpcc](https://discord.com/invite/YypBvdUpcc)
- **Brand Assets** (Logos, Slides, etc.): [Google Drive](https://drive.google.com/drive/folders/1paB9DkpPGv58_MC3P5C1el_Bw7lzYh-3?usp=sharing)
