mem0ai / mem0
Universal memory layer for AI Agents
github.com/mem0ai/mem0Indexed at 001c235Up to date with upstream
About this codebase
1,491 files and 8,251 symbols in 11 modules, led by TypeScript (569 files) and Python (370).
Built from the index
Code health
This codebase scores 7.1 out of 10 for code health, which we rate good. It also scores maintainability 7.9 and static performance 9.9 out of 10. The three are scored separately and never blended into one number. Risk is concentrated, as it usually is: 94 of 1,491 files are git hotspots, and they average 4.3 — which is where the fixes pay off most.
On the leaderboards:#1 of 4 Agent memory layers#16 of 44 Python repos
Do next
1 thing worth doing this quarter.
Worth planning
Delete 136 unused symbols and files (1,702 lines)
Nothing in the graph reaches them, across 51 files; every reader and agent pays to skip them.
- symbols
- 136
- lines
- 1,702
- safe to delete
- Yes(inferred)
Medium effort
Improve what Repowise can see
Add a test coverage report
Without one, Repowise cannot tell tested code from untested code, so every test-related action says “unknown”.
- line coverage
- Unknown, no report
Small effort
Use mem0ai/mem0 in your agent
Point Claude Code, Cursor, Codex or VS Code at this repository. Your agent gets the index this page is built from: cited answers, callers, history and health for any file.
https://api.repowise.dev/mcp/mem0ai/mem0One command, run anywhere. Adds the server to your local Claude Code config.
Docsclaude mcp add --transport http repowise https://api.repowise.dev/mcp/mem0ai/mem0 \ --header "Authorization: Bearer rw_live_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
This repo is public, so anyone with a Repowise account and an API key can connect.
Try asking
- get_overview()
- get_answer("how is mem0 put together?")
- get_why("why is mem0 structured this way?")
Prefer local? pip install repowise && repowise init indexes your own checkout, no account needed.
Go deeper
- OverviewEverything the index found, what changed this week, commits and decisions.
- DocumentationModule-by-module documentation, 1,310 pages, 0 written by a model.
- ArchitectureDependency graph, layers and third-party dependencies.
- Code healthEvery file's score, the findings behind it, tests and refactoring plans.
- CommitsEach commit's effect on code health, with agent provenance.
- ContributorsWho owns what, and where one person holds most of the knowledge.
- DecisionsArchitectural decisions mined from commits and pull requests.
- Ask this codebaseSign inGrounded answers over the indexed code.
Maintain this repo? Claim the page
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Use this repo from Claude or ChatGPT
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https://api.repowise.dev/mcp/mem0ai/mem0For maintainers
Add a badge to your README
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Repowise badge
Links to this page, with no score on it. Adding it also re-indexes the repo every week.
[](https://repowise.dev/repo/mem0ai/mem0?src=badge_wiki)Code health badge
The repo's health score out of 10, from the latest index.
[](https://repowise.dev/repo/mem0ai/mem0?src=badge_health)Code health card
A larger card with the score, its change since the last index, and when it was measured. The HTML version follows the reader's light or dark theme.
[](https://repowise.dev/repo/mem0ai/mem0?src=badge_card)How mem0ai/mem0 works
Universal memory layer for AI Agents This page is a map of the mem0ai/mem0 repository, written primarily in Python, rebuilt from the source each time it is indexed. Repowise parses every symbol, computes a dependency graph, scores per-file code health from complexity, duplication, test coverage and churn, mines git history for hotspots and ownership, and lifts the architectural decisions into documentation you can read here or query through MCP.
The codebase has 1,491 files and 8,251 symbols in 11 modules, led by TypeScript, Python and JavaScript. Code health is 7.1 out of 10, rated good.
Use the links above to open each view, or connect this repository to your agent for grounded answers inside Claude, Cursor, Codex or VS Code.