codemem

Name: codemem
Author: jeang42

by jeang42version 0.1.0i★ –iRuns on your computer

Registry nameio.github.jeang42/codemem

Install

Overview

Description from the maker (original English)

Shared memory for coding agents: projects, reusable code, sessions and commits across machines

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: Streamable HTTP
Category: Search & AI memory

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
You fill in yourself: CODEMEM_DATA, CODEMEM_DB, CODEMEM_HOST, CODEMEM_PORT, OLLAMA_URL, CODEMEM_EMBED, GIT_ROOT

You need

PyPIPython’s uv installed (for the uvx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "codemem": {
      "command": "uvx",
      "args": [
        "codemem-mcp",
        "serve"
      ],
      "env": {
        "CODEMEM_DATA": "your-value",
        "CODEMEM_DB": "your-value",
        "CODEMEM_HOST": "your-value",
        "CODEMEM_PORT": "your-value",
        "OLLAMA_URL": "your-value",
        "CODEMEM_EMBED": "your-value",
        "GIT_ROOT": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add codemem --env CODEMEM_DATA=your-value --env CODEMEM_DB=your-value --env CODEMEM_HOST=your-value --env CODEMEM_PORT=your-value --env OLLAMA_URL=your-value --env CODEMEM_EMBED=your-value --env GIT_ROOT=your-value -- uvx codemem-mcp serve

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "codemem": {
      "command": "uvx",
      "args": [
        "codemem-mcp",
        "serve"
      ],
      "env": {
        "CODEMEM_DATA": "your-value",
        "CODEMEM_DB": "your-value",
        "CODEMEM_HOST": "your-value",
        "CODEMEM_PORT": "your-value",
        "OLLAMA_URL": "your-value",
        "CODEMEM_EMBED": "your-value",
        "GIT_ROOT": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "codemem": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "codemem-mcp",
        "serve"
      ],
      "env": {
        "CODEMEM_DATA": "your-value",
        "CODEMEM_DB": "your-value",
        "CODEMEM_HOST": "your-value",
        "CODEMEM_PORT": "your-value",
        "OLLAMA_URL": "your-value",
        "CODEMEM_EMBED": "your-value",
        "GIT_ROOT": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

Values you fill in

CODEMEM_DATA env
Directory for the database and backups
CODEMEM_DB env
Path to the SQLite database (overrides CODEMEM_DATA)
CODEMEM_HOST env
Address to bind. The server has no authentication; use 127.0.0.1 unless the network is trusted
CODEMEM_PORT env
Port for MCP (/mcp) and the web UI. The transport URL assumes 8055
OLLAMA_URL env
Ollama base URL for embeddings (semantic search). Without it, search is BM25 only
CODEMEM_EMBED env
Set to false to disable embeddings entirely
GIT_ROOT env
Directory of bare git repos to read for the commit feed

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account jeang42, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Search & AI memoryi

More stars than 0% of the other 7251 servers in this category
Published to the registry more recently than 48% of the other 7251 servers in this category
Basic checks equal to or better than 100% of the other 7251 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is codemem safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.1.0) reached the registry 42 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.

What can I use instead?

In the same category: Context7, Codebase Memory, Exa

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Context7

by upstash

Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.

Computer or cloud★ 64,224MITUpdated today

Install

Codebase Memory

by DeusData

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

Runs on your computer★ 48,148MITUpdated 20 days ago

Install

Exa

by exa-labs

Connect AI agents to Exa for web search, content fetching, and multi-step research.

Runs in the cloud★ 5,213MITUpdated last month

Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

codemem

Your coding agents keep rebuilding what you already have. codemem remembers what they built, across every project and every machine, and scores each piece on evidence of whether it worked.

It is an MCP server for Claude Code and other MCP clients. It knows what projects exist, where they live, what reusable pieces they contain, what each session did and decided, every commit pushed to the git host, and how to do recurring things. Everything is searchable from any machine, from an agent, or from the web UI. It is written to *during* work, not after.

One Python process, SQLite, no external services required.

What makes it different

Inventory scripts snapshot a directory and you read the report once. Registries list what people published. codemem does neither.

Trust from evidence, not from stars. Every project and asset gets a computed score from how recently it changed, how much work went into it, whether it is actually deployed and running, whether anything else imports it, and whether a human vouched for it. verify records "I ran it today and it works" and restarts the freshness clock. Scores are recomputed on every sync, so they decay when you stop touching something.
It finds the copies you forgot. Discovery mines every repo at HEAD for scripts, modules, service units, Dockerfiles and MCP servers, hashes their functions, and links repos that share code. It will tell you that you wrote the same retry wrapper in three places.
Agents feed it automatically. A session hook records what each Claude Code session did, and gives the next session a brief on the project it just opened. The catalogue builds itself.
Maturity is a first-class label. authoritative, usable, experimental, antiquated, sunset, broken, junk, each with a reason. Search ranks by it, and you can exclude the ratings you should not build on.
Your code stays where it is. codemem stores metadata: names, descriptions, imports, symbols, function hashes, commit records. It does not copy your source anywhere.

Endpoints

Endpoint	What
`http:// :8055/mcp`	MCP (streamable HTTP) for Claude Code and other MCP clients
`http:// :8055/`	Web UI: search, projects, assets, notes, activity, docs. Dark mode.
`http:// :8055/api/…`	JSON API used by the UI (see docs/architecture.md)
`http:// :8055/health`	liveness

Normally runs on the git host, the machine holding the bare repos, so it can read them directly.

Security: codemem has no authentication. It is built for a trusted network, and anyone who

can reach the port can read and write everything. Do not expose it to the internet without an

authenticating proxy in front of it. See docs/architecture.md.

Requirements

Python 3.11 or newer, and git. Optional: a git host with bare repos for the commit feed, Gitea for descriptions and web links, and Ollama for semantic search, drafted descriptions and the review pass. Everything works without the optional pieces; search falls back to BM25 alone.

Why

A developer with many project folders across several machines has no way for a new Claude Code session to know that a retry wrapper, a Gradio helper, a GPU monitor or a data pipeline already exists somewhere. So they get rebuilt. Snapshot inventory scripts (run, read, forget) do not fix that. codemem is the live, writable layer: it is written to during work, not after.

The content is whatever is there. codemem does not filter or judge. Each project carries an audience: unrestricted (the default), professional, or employer, so a search or a view can exclude one when the context calls for it. Nothing is hidden unless asked, with one exception: cloned third-party repos are marked origin = vendor and stay out of search and lists until you ask for them. See docs/USER_GUIDE.md.

Install from PyPI

The package is codemem-mcp; the command it installs is codemem.

pip install codemem-mcp # or: uv tool install codemem-mcp / pipx install codemem-mcp codemem serve # MCP at http://localhost:8055/mcp, web UI at http://localhost:8055/

uvx codemem-mcp serve # or run it without installing

Data goes to ~/.codemem/ unless CODEMEM_DB or CODEMEM_DATA says otherwise. Register it with Claude Code:

claude mcp add --transport http --scope user codemem http://localhost:8055/mcp

That is the server alone. For the systemd units, the commit feed and the session hooks, use the quick start below from a clone of the repository.

Run with Docker

docker build -t codemem . docker run --rm -p 127.0.0.1:8055:8055 codemem # throwaway database docker run -d -p 127.0.0.1:8055:8055 -v codemem-data:/data codemem # keep it in a volume

No authentication. Anyone who can reach the port can read and write everything. Keep the

127.0.0.1: in -p: a bare -p 8055:8055 publishes the port on every interface, and Docker's

port rules bypass most host firewalls.

The image needs none of the optional pieces: embeddings are off (CODEMEM_EMBED=0) and there is no git host. Pass -e OLLAMA_URL=... -e CODEMEM_EMBED=1 to turn semantic search on.

Quick start

Server (once, on the git host):

./install.sh # venv, user-scope systemd units, seed, backfill, gitea, scan, embed

Client (each machine, once):

CODEMEM_URL=http:// :8055 client/install-client.sh # Linux/macOS: MCP server + SessionStart/SessionEnd hooks client\install-client.ps1 # Windows PowerShell (set $env:CODEMEM_URL first)

Then in any Claude Code session the codemem tools are available and every session starts with a brief of the current project (if codemem knows it) and ends with an automatic session record.

What Claude sees

Tool	Use
`search`	hybrid BM25 + embedding search over everything. First call before building anything
`project_brief`	everything about one project, by name or working directory
`list_projects`	filter by status, tag, machine, audience, visibility
`update_project`	description, purpose, status, tags, audience, origin (own/vendor), visibility, maturity
`register_asset`	record a reusable script/module/prompt/skill/service with a one-line usage
`find_assets`	search or list assets by kind/tag/project, or by imported library
`log_session`	what was done, decided, used, abandoned, and what is next
`add_note`	decision, howto, resource, issue, idea
`delete_note`	remove a note written by mistake, with its index and embedding rows
`link_items`	project uses / could-reuse / supersedes / derived-from another
`rate`	maturity: authoritative, usable, experimental, antiquated, sunset, broken, junk, with a why
`verify`	"I ran it today and it works": restarts the computed trust score's freshness clock
`handoff` / `list_handoffs`	track one implementation replacing another through candidate, shadow, verified, promoted
`howto`	how to publish, add a machine, use codemem, plus whatever docs are ingested
`activity`	commits and sessions across all machines, last N days
`add_scan_root` / `scan_path`	register a directory to scan; scan now (server machine)
`stats`	counts, machines, index coverage
`help`	workflow, tool list, label vocabularies. Also `/codemem` in Claude Code, `/codemem` searches

Where the data comes from

Git host: every bare repo in GIT_ROOT is backfilled; a post-receive hook posts each push to /ingest/push so new commits appear within seconds. See docs/git-commit-feed.md.
Gitea (optional): descriptions, topics and web URLs, via its API with a read token.
Local scan: project directories under registered roots, per machine. On the server this is automatic; other machines run client/codemem_agent.py once a root is registered.
Discovery: every own repo is mined at HEAD for scripts, modules, units, Dockerfiles, prompts and MCP servers, recorded as auto-discovered assets, with shared-code links between repos.
Docs: markdown from CODEMEM_DOC_SOURCES (this repo by default), re-hashed every sync.
Claude Code: session records from the hook, plus whatever Claude writes with the tools.
Local model (optional, via Ollama): embeddings for semantic search, drafted descriptions, and a targeted review of near-duplicate functions and thinly described code.

Layout

codemem/ the server package config.py every tunable, env-overridable db.py schema, connection, single FTS5 index store.py all writes (keeps the index in step) search.py BM25 + Ollama embeddings, reciprocal rank fusion gitsync.py bare-repo backfill, push ingest, push.log, Gitea scan.py project discovery + location records discover*.py asset discovery, shared-code linking (core is shared with the remote agent) trust.py computed trust scores review.py targeted model review describe.py model-drafted project descriptions knowledge.py doc ingest, howto/asset seed server.py MCP tools, HTTP routes, JSON API cli.py serve | backfill | gitea | docs | seed | scan | embed | reindex | backup | sync | discover | review | trust | describe | purge web/ the single-file web UI (+ vendored marked.js) client/ hook, remote scan agent, slash command, per-OS installers systemd/ user-scope units: service, sync timer (6h), backup timer (02:45) docs/ user guide, architecture, git-commit-feed, clients, operations, publishing, python-vs-typescript server.json MCP Registry entry (PyPI package codemem-mcp) glama.json Glama listing maintainers Dockerfile container image: throwaway /data, no optional services

Storage: $CODEMEM_DB (default ~/.codemem/codemem.db, SQLite, WAL). Backups: $CODEMEM_BACKUP_DIR (default ~/.codemem/backups/).

Status and contributing

Extracted from a system that has been running daily against 165 projects, 735 assets and 2,000+ commits across three machines. It is stable for that use, but it has had one operator, so expect rough edges the moment your layout differs from that one. Issues and pull requests welcome; please open an issue before a large change so we can agree on the shape. See CONTRIBUTING.md for how to run it locally and the two rules that are not negotiable, and SECURITY.md for what it stores and how to report a vulnerability.

Run scripts/smoke.sh before pushing: it boots the server against a throwaway database and checks that health, the web UI, the JSON API and the schema all come up.

License

Apache License 2.0. See LICENSE.

codemem

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

Values you fill in

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Search & AI memoryi

Common questions

Alternatives

Context7

Codebase Memory

Exa

README from the maker

codemem

What makes it different

Endpoints

Requirements

Why

Install from PyPI

Run with Docker

Quick start

What Claude sees

Where the data comes from

Layout

Status and contributing

License