codemem
Ingests commit history and repository metadata from Git hosts, enabling activity tracking, project discovery, and search across commits.
Fetches project descriptions, topics, and web URLs from Gitea's API to enrich project metadata.
Uses Ollama for semantic search embeddings, drafted project descriptions, and targeted review of near-duplicate or thinly described code.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@codememsearch for a retry wrapper before rebuilding one"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
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.
verifyrecords "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.
Related MCP server: mcp-chest-memory
Endpoints
Endpoint | What |
| MCP (streamable HTTP) for Claude Code and other MCP clients |
| Web UI: search, projects, assets, notes, activity, docs. Dark mode. |
| JSON API used by the UI (see docs/architecture.md) |
| 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.
Quick start
Server (once, on the git host):
./install.sh # venv, user-scope systemd units, seed, backfill, gitea, scan, embedClient (each machine, once):
CODEMEM_URL=http://<host>: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 |
| hybrid BM25 + embedding search over everything. First call before building anything |
| everything about one project, by name or working directory |
| filter by status, tag, machine, audience, visibility |
| description, purpose, status, tags, audience, origin (own/vendor), visibility, maturity |
| record a reusable script/module/prompt/skill/service with a one-line usage |
| search or list assets by kind/tag/project, or by imported library |
| what was done, decided, used, abandoned, and what is next |
| decision, howto, resource, issue, idea |
| remove a note written by mistake, with its index and embedding rows |
| project uses / could-reuse / supersedes / derived-from another |
| maturity: authoritative, usable, experimental, antiquated, sunset, broken, junk, with a why |
| "I ran it today and it works": restarts the computed trust score's freshness clock |
| track one implementation replacing another through candidate, shadow, verified, promoted |
| how to publish, add a machine, use codemem, plus whatever docs are ingested |
| commits and sessions across all machines, last N days |
| register a directory to scan; scan now (server machine) |
| counts, machines, index coverage |
| workflow, tool list, label vocabularies. Also |
Where the data comes from
Git host: every bare repo in
GIT_ROOTis backfilled; a post-receive hook posts each push to/ingest/pushso 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.pyonce a root is registered.Discovery: every own repo is mined at HEAD for scripts, modules, units, Dockerfiles, prompts and MCP servers, recorded as
auto-discoveredassets, 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, python-vs-typescriptStorage: $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.
Copyright © 2026 Jeff Angelcyk.
This server cannot be deployed
Maintenance
Related MCP Connectors
Shared, governed long-term memory for AI agents across tools and sessions via MCP and REST.
- MemocoreOAuthai.memocore
Shared memory for all your AI agents, your whole team and every MCP client — save, search, recall.
Persistent memory for AI agents — log and recall conversation context over MCP.
Persistent AI memory shared across Claude, ChatGPT, coding agents, and compatible MCP clients.
Related MCP Servers
- AlicenseNot gradedqualityAmaintenanceProvides persistent memory for AI coding agents via MCP, allowing them to recall fragility, decisions, and bugs across sessions.241 npm3MIT
- AlicenseNot gradedqualityBmaintenanceProvides a persistent, local-first memory for coding agents over MCP, enabling automatic recall and recording of past work, failures, and decisions to reduce repetition and token usage.MIT
- AlicenseNot gradedqualityBmaintenanceProvides persistent, searchable memory and knowledge capture for AI-assisted development, enabling agents to retain decisions, bugs, and patterns across sessions and projects.MIT
- AlicenseNot gradedqualityCmaintenanceProvides persistent memory and task management for coding agents via MCP tools, enabling mid-session recall and capture of durable knowledge.176 npm10MIT