shno-labs/mem-forge

MemForge

<p align="center"> <img src=".github/assets/memforge-banner.png" alt="MemForge - Agent memory layer" width="100%"> </p> <p align="center"> <a href="https://github.com/shno-labs/mem-forge/actions/workflows/ci.yml"><img alt="CI" src="https://github.com/shno-labs/mem-forge/actions/workflows/ci.yml/badge.svg"></a> <img alt="Python 3.12+" src="https://img.shields.io/badge/python-3.12%2B-3776AB"> <img alt="License Apache 2.0" src="https://img.shields.io/badge/license-Apache--2.0-blue"> <img alt="Status alpha" src="https://img.shields.io/badge/status-alpha-f59e0b"> <img alt="Code style Ruff" src="https://img.shields.io/badge/code%20style-ruff-111827"> </p>

Self-evolving, evidence-based agent memory layer for Codex, Claude Code, and development teams.

Status: alpha. APIs, storage formats, and integration packaging may change while the project settles.

MemForge (mem-forge) is a self-evolving memory layer for AI coding agents. It turns scattered team context into structured, source-traced memories that agents can search, verify, and reuse.

It connects to the systems teams already use, such as Confluence, Jira, GitHub Pages, Microsoft Teams, and long coding-agent sessions. On each sync, MemForge extracts durable facts, decisions, procedures, and conventions while preserving source evidence and history.

AI coding assistants often start each session blind to institutional context. MemForge bridges that gap through MCP-enabled agent plugins, an admin API, and integrations, with review flows for superseded facts and contradictions.

What It Does

• Ingests source context from genes such as wiki pages, issue trackers, GitHub Pages, Teams exports, and generated agent-session packages.
• Extracts durable facts, decisions, procedures, and conventions with quality gates before persistence.
• Stores memory, provenance, review state, full-text search, and vector search in a local or self-hosted service.
• Ships thin MCP proxies for Codex