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Agent Memory & RAG

Athena

Athena is a Python developer tool that stores AI coding-agent context as plain Markdown on disk and uses session commands to load and save that context over time. It is described as portable across Claude Code, Google Antigravity, Cursor, Gemini CLI and Visual Studio Code, with memory retrieval based on keyword search and optional vectors.

Explore the practical guide ↓

Independent OpenViST project profile, based on linked sources.

Athena — OpenViST project profile in Agent Memory & RAG.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use Athena when recurring coding-agent work would benefit from carrying project context between sessions, especially when switching among its listed environments.

Who it is for

  • Developers who want coding agents to recall project context across sessions.
  • People who work across the listed IDEs or CLI environments and want context stored outside a single model provider.

Documented uses

  • Load prior project context at the start of an agent session.
  • Save session notes and canonical facts for later work.
  • Keep agent context in local Markdown files that can be version-controlled.
  • Use the same context workflow across supported coding environments.
Before you choose

Requirements & limits

The repository is public and identifies the project as MIT-licensed. The README documents a Python installation and local setup.

  • Athena’s context is stored as plain Markdown on disk, rather than only in a provider-managed memory store.
  • The local installation is described as having no cloud dependencies; cloud sync and reranking are part of the separate full install.
  • The README describes governance as partial and lists known bypasses for some destructive commands.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Set up Athena for a coding environment

Install Athena locally, initialize it for a supported IDE, and check the setup.

Before you start

  • Python 3
  • A supported coding environment, such as Claude Code, Antigravity, Cursor, Gemini CLI or VS Code

Steps

  1. Clone the Athena-Public repository and enter its directory.

  2. Create and activate a Python virtual environment.

  3. Install the local package with the command below.

    Documented command
    pip install -e ".[local]"

  4. Run athena init --ide with the identifier for the chosen environment, then run athena doctor.

Expected outcome

Athena is installed locally, initialized for the selected IDE, and its doctor check has been run.

Guide limitations

  • This setup uses the local extra and does not include cloud dependencies.
  • The README directs users to the getting-started guide for Windows and advanced configuration.
Documentation 1 ↗
Source-based practical guide

Carry context through an Athena session

Load saved context at the start of work and save the session when finished.

Before you start

  • Athena initialized for a coding environment
  • Access to that environment’s AI chat panel

Steps

  1. Enter /start in the IDE's AI chat panel to load context.

  2. Work in the chat as usual.

  3. Enter /end to save the session.

Expected outcome

The session routine loads prior context and saves the current work for later sessions.

Guide limitations

  • The README describes this routine but does not prescribe project-specific memory content.
Documentation 1 ↗
Evidence and transparency

Sources & review

Official repository ↗
Source record details
Source availability
Active
Sources checked
9 October 2026
Original website title
winstonkoh87/Athena-Public · Official homepage title · retained in its source language
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