Metadata-Version: 2.4
Name: mesa-memory
Version: 0.9.2
Summary: Enterprise AI agent memory engine
Author: MESA Core Team
License: MIT License
        
        Copyright (c) 2026 MESA Core Team
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
        in the Software without restriction, including without limitation the rights
        to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
        copies of the Software, and to permit persons to whom the Software is
        furnished to do so, subject to the following conditions:
        
        The above copyright notice and this permission notice shall be included in all
        copies or substantial portions of the Software.
        
        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
        IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
        FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
        AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
        LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
        OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
        SOFTWARE.
        
Project-URL: Homepage, https://github.com/Yasou13/MESA
Project-URL: Repository, https://github.com/Yasou13/MESA
Project-URL: Documentation, https://github.com/Yasou13/MESA/tree/main/docs
Project-URL: Changelog, https://github.com/Yasou13/MESA/blob/main/CHANGELOG.md
Project-URL: Issues, https://github.com/Yasou13/MESA/issues
Keywords: ai,memory,agents,knowledge-graph,llm,cognitive
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Python: >=3.11
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: aiosqlite>=0.22.0
Requires-Dist: anyio>=4.0.0
Requires-Dist: httpx>=0.28.0
Requires-Dist: mcp<2.0.0,>=1.30.0
Requires-Dist: cryptography>=42.0.0
Requires-Dist: uvicorn>=0.29.0
Requires-Dist: fastapi>=0.139.0
Requires-Dist: starlette>=1.3.1
Requires-Dist: slowapi>=0.1.9
Requires-Dist: prometheus_client>=0.20.0
Requires-Dist: openai>=2.36.0
Requires-Dist: ollama>=0.6.1
Requires-Dist: pydantic>=2.13.0
Requires-Dist: pydantic-settings>=2.14.0
Requires-Dist: lancedb>=0.30.0
Requires-Dist: pyarrow>=24.0.0
Requires-Dist: kuzu>=0.0.11
Requires-Dist: numpy>=2.2.0
Requires-Dist: tenacity>=9.0.0
Requires-Dist: psutil>=7.0.0
Requires-Dist: structlog>=24.0.0
Requires-Dist: python-dotenv>=1.2.0
Requires-Dist: tiktoken>=0.12.0
Requires-Dist: alembic>=1.13.0
Requires-Dist: sqlalchemy>=2.0.51
Requires-Dist: typing_extensions>=4.16.0
Provides-Extra: adapters
Requires-Dist: anthropic>=0.100.0; extra == "adapters"
Provides-Extra: ml
Requires-Dist: torch>=2.11.0; extra == "ml"
Requires-Dist: transformers>=5.8.0; extra == "ml"
Requires-Dist: tokenizers>=0.22.0; extra == "ml"
Requires-Dist: safetensors>=0.7.0; extra == "ml"
Requires-Dist: huggingface_hub>=1.14.0; extra == "ml"
Requires-Dist: sentence-transformers>=3.0.0; extra == "ml"
Provides-Extra: loadtest
Requires-Dist: aiohttp>=3.14.3; extra == "loadtest"
Requires-Dist: locust>=2.29.0; extra == "loadtest"
Provides-Extra: dev
Requires-Dist: pytest>=7.4.0; extra == "dev"
Requires-Dist: pytest-asyncio>=0.23.0; extra == "dev"
Requires-Dist: pytest-cov>=4.1.0; extra == "dev"
Requires-Dist: pytest-benchmark>=4.0.0; extra == "dev"
Requires-Dist: cyclonedx-bom>=5.1.0; extra == "dev"
Requires-Dist: mypy>=1.10.0; extra == "dev"
Requires-Dist: black>=24.0.0; extra == "dev"
Requires-Dist: ruff>=0.4.0; extra == "dev"
Requires-Dist: datasets>=2.14.0; extra == "dev"
Requires-Dist: PyYAML>=6.0.0; extra == "dev"
Dynamic: license-file

# MESA — Memory Engine for Structured Agents

[![MESA CI](https://github.com/Yasou13/MESA/actions/workflows/ci.yml/badge.svg?branch=main)](https://github.com/Yasou13/MESA/actions/workflows/ci.yml?query=branch%3Amain)
[![Release](https://img.shields.io/github/v/release/Yasou13/MESA)](https://github.com/Yasou13/MESA/releases/latest)
[![License: MIT](https://img.shields.io/github/license/Yasou13/MESA)](https://github.com/Yasou13/MESA/blob/main/LICENSE)
[![Python: 3.11+](https://img.shields.io/badge/Python-3.11%2B-3776AB?logo=python&logoColor=white)](https://github.com/Yasou13/MESA/blob/main/pyproject.toml)

MESA is an LLM-independent, source-linked memory engine for AI applications. It stores documents with exact provenance (document, revision, passage) and returns verifiable, scoped evidence over HTTP, Python SDK, and MCP. MESA returns evidence; it never writes the final answer or hallucinates sources.

Package version: **0.9.2**. V4 is the current API. Production qualification remains at the release candidate stage: **NO-GO** until the [release gates](https://github.com/Yasou13/MESA/blob/main/docs/release.md) pass.

## Installation

```bash
pip install mesa-memory
```

Supported on Linux and macOS natively. On Windows, run via Docker or WSL.

## Start the server

```bash
mesa start
```

Starts the local server on `http://127.0.0.1:8000`, initializes storage at `~/.mesa/data`, and creates credentials at `~/.mesa/credentials.json` (mode 0600).

## Add and search documents

In another terminal, add and search documents immediately:

```bash
mesa add document.txt --source file://document.txt
mesa search "your query"
```

## Python SDK

```python
from mesa_client import Mesa

mesa = Mesa()
mesa.add(open("document.txt").read(), source="file://document.txt")
print(mesa.context("your query"))
```

`Mesa()` uses `MESA_API_KEY` and `MESA_BASE_URL` when they are set, otherwise the local credentials in `~/.mesa/credentials.json`.

## Connect MCP clients

Generate a ready-to-paste configuration block for Claude Desktop or any MCP client:

```bash
mesa mcp-config
```

## Internal models (optional)

Models stay off by default. Documents are stored and found through BM25 lexical search without any model running. `FactExtractionService` owns canonical V4 extraction when explicitly enabled (`MESA_EXTRACTION_ENABLED=true`).

To enable semantic vector search with local Ollama, add to `~/.mesa/.env`:

```bash
MESA_MODEL_ENABLED=true
MESA_EMBEDDING_MODEL=ollama:bge-m3
# To also enable open-ended fact extraction (defaults to false):
# MESA_EXTRACTION_ENABLED=true
# MESA_LLM_MODEL=ollama:qwen2.5:7b
```

Local `openai_compatible` servers (such as vLLM started with `--port 8001`, at `MESA_LLM_BASE_URL=http://127.0.0.1:8001/v1`; MESA itself uses port 8000) are also allowed with `MESA_EXTERNAL_PROVIDER_ENABLED=false` on a local endpoint (`localhost`, `127.0.0.1`, `::1`, `host.docker.internal`) and require no API key (D31). For cloud model providers (OpenAI, Anthropic), set `MESA_EXTERNAL_PROVIDER_ENABLED=true` and provide the required API keys.

## Graph toggle

To run without the Kùzu graph database, set:

```bash
MESA_GRAPH_ENABLED=false
```

GRAPH lanes end `SKIPPED`, and turning the flag back on later backfills the graph at startup.

## Docker

Run MESA in a single-user local container (D32):

```bash
docker compose -f docker-compose.v4.yml up --build -d
```

Credentials are written to `/var/lib/mesa/credentials.json` in the container volume:

```bash
docker compose -f docker-compose.v4.yml exec mesa-v4 cat /var/lib/mesa/credentials.json
docker compose -f docker-compose.v4.yml exec -T mesa-v4 mesa add - --source file://document.txt < document.txt
docker compose -f docker-compose.v4.yml exec mesa-v4 mesa search "your query"
```

No variables are required; models and external providers default off. If you set `MESA_API_KEY` and `MESA_PRINCIPAL_ID` for existing HTTP clients, the server accepts that key too, and the `mesa` commands inside the container use it first; add `-e MESA_API_KEY=` after `exec` to use the local credentials instead. The image includes `adapters`; build with `--build-arg MESA_EXTRAS=ml,adapters` to add local sentence-transformers. Ollama defaults to `http://host.docker.internal:11434` (the Docker host).

## Google Colab

Run MESA with GPU-accelerated Ollama in Colab:
[Colab Quickstart](https://github.com/Yasou13/MESA/blob/main/examples/colab_quickstart.ipynb)

## Development

```bash
uv sync --locked --python 3.11
```

See [testing](https://github.com/Yasou13/MESA/blob/main/docs/testing.md) for local tests, and [docs/testing.md](https://github.com/Yasou13/MESA/blob/main/docs/testing.md) for test markers.

## Documentation

- [Getting Started Guide](https://github.com/Yasou13/MESA/blob/main/docs/getting-started.md)
- [Configuration Reference](https://github.com/Yasou13/MESA/blob/main/docs/configuration.md)
- [API Reference](https://github.com/Yasou13/MESA/blob/main/docs/api-reference.md)
- [MCP Integration Guide](https://github.com/Yasou13/MESA/blob/main/README_MCP.md)
- [Architecture](https://github.com/Yasou13/MESA/blob/main/ARCHITECTURE.md)
- [Documentation Index](https://github.com/Yasou13/MESA/blob/main/docs/README.md)

## License

[MIT](https://github.com/Yasou13/MESA/blob/main/LICENSE).
