# MemDocs

> Use this tool when you need to maintain project context and knowledge continuity across AI sessions, particularly for complex AI projects that require persistent memory management. MemDocs generates structured documentation and stores machine-readable summaries, solving problems of knowledge loss and context switching between conversations. It takes in code repositories as input and outputs a .memdocs/ directory committed to git, providing a seamless interface for AI assistants to access project information.

Canonical page: https://skillsregistry.net/skills/smart-ai-memory-memdocs  
JSON: https://api.skillsregistry.net/v1/skills/smart-ai-memory-memdocs

## Description

Git-native memory management system for AI projects that generates structured documentation persisting across sessions. Stores machine-readable summaries in a .memdocs/ directory committed to git, enabling AI assistants to maintain project context between conversations. Uses tree-sitter for code parsing and Claude for summarization.

## Trust

- **Trust score (0–1):** 0.51
- **Verification tier:** scanned
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** file-system
- **Updated:** 2026-09-19

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/smart-ai-memory-memdocs)
- **Repository:** <https://github.com/smart-ai-memory/memdocs>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "smart-ai-memory-memdocs"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/smart-ai-memory-memdocs` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/smart-ai-memory-memdocs/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt