Context7
Up-to-date docs for AI agents
Beschreibung vom Entwickler (englisches Original)
Shared memory for parallel AI coding agents. Local, free, with rooms and file claims.
Diese drei werden nie zu einer Punktzahl zusammengefasst: Meinungen, Messungen und Beliebtheit sind verschiedene Dinge.
Für diesen Server haben wir noch keine Zusammenfassung in einfacher Sprache geschrieben. Unten stehen die Fakten, die wir aus der Registry gelesen haben.
Wähle die KI-App, die du nutzt, und kopiere die Einstellungen.
Welche App nutzt du?
Wähle oben deine App. Wir merken sie uns, damit der Button beim nächsten Mal „In … installieren“ anzeigt.
Die .mcpb-Datei des Entwicklers herunterladen
Der Link führt zur Datei des Entwicklers selbst; wir hosten sie nicht und verpacken sie nicht neu. Öffne die Datei, dann installiert Claude Desktop sie.
Führe das in deinem Terminal aus
Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
Dieser Server läuft auf deinem Computer, und ChatGPT kann sich nur mit Servern im Internet verbinden. Wähle eine andere App.
Deine Auswahl bleibt in einem Cookie auf diesem Gerät; kein Konto nötig.
Diese Einstellungen werden aus dem Registry-Eintrag des Entwicklers erzeugt. Wenn in der README etwas anderes steht, folge der README.
Läuft auf deinem Computer; die Tool-Liste erscheint nach der Installation in deiner KI-App.
Wir prüfen Informationen, die jeder sehen kann; den Code haben wir nicht gelesen. Checks, die nicht zutreffen, werden nicht mitgezählt. · Geprüft am 7. Nov. 2026
Der Registry-Name wurde mit dem GitHub-Konto aryawidjaja bestätigt, dem das Repo gehört
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieser Server läuft auf deinem Computer; es gibt keinen Endpunkt im Internet
Läuft auf deinem Computer und nutzt stattdessen lokale Einstellungen
Läuft auf deinem Computer; Tool-Listen können wir nur von Endpunkten im Internet lesen
Verglichen mit allen aktiven Servern dieser Kategorie in der Registry. Sterne zählen nur, wenn dem Herausgeber das Repo gehört.
Er hat 1 von 1 zutreffenden Basischecks bestanden. Den Code haben wir nicht gelesen. Bevor du einen Schlüssel oder Token hinzufügst, sieh nach, welche Zugriffe der Server verlangt, und nutze einen Schlüssel, der nur die Berechtigungen hat, die du brauchst.
Die Registry nennt keinen erforderlichen Schlüssel, manche Server bitten dich aber bei der ersten Nutzung, dich anzumelden.
Er läuft auf deinem Computer. Deine KI-App startet ihn bei Bedarf, und die Daten laufen nicht über die Server des Entwicklers (außer der Server ruft selbst einen Onlinedienst auf).
Das GitHub-Repo wurde zuletzt – geändert, und die neueste Version (0.8.0) kam vor 3 Monaten in die Registry.
Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code. Außerdem brauchst du MCPB auf deinem Computer.
In derselben Kategorie: Context7, Codebase Memory, Exa
Server derselben Kategorie von anderen Entwicklern, sortiert nach Sternen.
So liest du eine Karte:★ GitHub-SterneiDrei Säulen: Bewertungen · Checks · NutzungiAktualisiert = neueste Version in der Registry veröffentlichti
Up-to-date docs for AI agents
Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.
Connect AI agents to Exa for web search, content fetching, and multi-step research.
Unverändert aus dem Repo des Entwicklers übernommen. PopNx MCP hat den Inhalt weder geprüft noch empfiehlt es ihn. HTML, Bilder und Skripte wurden entfernt. Links führen von dieser Website weg.
marrow
*Memory that keeps working after Claude's runs out — shared across your projects, machines and tools.*
Claude Code's built-in memory loads the first 200 lines of one file into every session. That is fine for a young project. A codebase two years old knows more than fits in 200 lines, and everything past the cut is simply dropped.
Marrow retrieves instead of loading. Ask a question and it returns the twenty memories that answer it, plus the ones linked to those, out of however many thousand you have.
At 1,000 project facts that is 2.1× less context per turn (p = 0.002) and $0.50 a task instead of $0.90. Numbers and method below.
It also does three things the built-in memory does not:
api recall what webapp knows.And because several agents share it, it also keeps them from colliding: a file another live session is editing is claimed, and every agent's actions land in one append-only, hash-chained record you can read.
Free forever, AGPL-3.0, runs on your machine. Every memory is a markdown file you can open and delete.
The usual way to tell an agent how your project works is to write it all into a CLAUDE.md, which it then reads on every single turn. That is fine for ten things. A codebase a couple of years old knows a thousand.
We gave a coding agent the same task and the same repo three ways: nothing, everything in a CLAUDE.md, and the same facts in Marrow. 75 runs.
uuid4 where ids are meant to be sortable, and wrote a naive timestamp. Both of the arms that had the knowledge got those right.Method: same fixture repo and prompt each time, graded by running the code rather than reading it, with bootstrap intervals and a permutation test over 6 runs per cell. There is more on the numbers at marrow.works.
Fair question, and the honest answer is that for a small project you may not need this.
Claude Code ships auto memory: Claude writes notes to ~/.claude/projects/ /memory/, and a MEMORY.md index is loaded into every session. It is on by default and it costs nothing. Use it and be happy until one of these starts to bite:
| Built-in auto memory | Marrow | |
|---|---|---|
| How memories reach the model | First 200 lines / 25KB of one index file, every session | Ranked retrieval: the matches, plus what they link to |
| What happens when it outgrows that | Claude is told to delete entries | Nothing; retrieval just searches more |
| Scope | One repository | Every project on the machine |
| Across your machines | No — "files are not shared across machines" | Yes, via a relay you run or Spinal Cloud |
| Across tools | Claude Code only | Claude Code, Cursor, Codex, any MCP client |
| Shared with teammates | No | Yes |
| Record of what agents did | No | Append-only, hash-chained, auditable |
| Flags memory that code has outgrown | No | Yes, for anchored Rust symbols |
The rule of thumb: under a hundred facts, one repo, one machine, one tool — use the built-in. Marrow starts paying for itself past that, and our own benchmark says so out loud (we lose at 10 facts).
The two are not exclusive. Auto memory is Claude's private scratchpad; Marrow is the shared record.
Claude Code, one command:
/plugin marketplace add aryawidjaja/marrow
/plugin install marrow@marrow
Then install the binaries it drives (`brew install aryawidjaja/marrow/marrow`, or
irm marrow.works/install.ps1 | iex on Windows) and restart.
Everything else — Cursor, Codex, Claude Desktop, or if you would rather not use a plugin:
brew install aryawidjaja/marrow/marrow # macOS/Linux; Windows: irm marrow.works/install.ps1 | iex
marrow setup # add --global to wire every repo at once
`marrow setup` seeds your brain with what it can work out about the repo on its own, so the first
session is not empty, and reports anything still missing. Restart your agent afterwards. The hooks need jq and never block your work when Marrow is unavailable. Already mid-session? Run `/marrow-save` to keep what is worth carrying forward.
Changed your mind? marrow uninstall puts everything back and keeps your memories. More ways to install, including the no-terminal Claude Desktop bundle, are further down.
The memory lives in .marrow/ in your project.
Marrow isn't a black box, it's a graph you can explore, like a second brain.
marrow-serve # opens the dashboard at http://localhost:8088
Every memory is a neuron, grouped into the area it belongs to, so the graph has real structure instead of being a hairball. Links connect memories that share a topic, a tag, or related meaning (from embeddings). Browse the tree, drag, zoom, click to read, filter, and add, edit, or delete memories right there. The Hive tab shows every project at once.
Every memory lives in an area of the project: auth, billing, infra. The agent files it as it writes, so the brain has a shape you can navigate instead of one flat heap.
project → area → topic → versions
marrow areas # the map: auth 11 · billing 10 · infra 23 · monitoring 10
Your agent sees that same map the moment a session starts, so it knows what the project knows before it answers. It can also weight a recall toward one area without hiding the rest:
marrow add --kind decision --topic jwt-expiry --area auth "We use 15-minute JWTs."
Nothing is forced. If a memory fits no area, it stays unfiled and is still fully searchable. A wrong area is worse than none.
By default each project has its own brain. Opt any project into a machine-wide hive with one command, and your agents can recall across all of them:
cd ~/code/webapp && marrow hub register --name webapp
cd ~/code/api && marrow hub register --name api
marrow hub recall "how do we do auth" # searches every project, tagged by project
Now an agent working in api can ask what webapp knows. In the dashboard, the Hive tab shows a central *core* neuron (you) with every project orbiting it, bridged where they share ideas.
Once a project joins the hive, its agents can open named rooms, ask each other questions, reply, and hand work over without relying on one giant chat. Claude Code, Codex, Cursor, and other MCP agents on the same machine can use the same channel.
Agents check the inbox when they start and before touching work another session may own. You can read every room in the dashboard's Channel tab, so the coordination stays visible instead of happening behind your back.
Each project is local and private by default. Share the *one* project you want synced, and the rest stay on your machine. It's like sharing a repo, not your whole disk.
# once, on a server (Docker, Fly.io, any host; see deploy/)
MARROW_TOKEN=$(openssl rand -hex 16) marrow-server
MARROW_TOKEN= marrow share --gateway https://your-gateway --space team-app
Same gateway + space + token on two machines routes their MCP memory tools to one remote project store. A decision saved through an agent on your laptop is available to an agent on your desktop. Every other project is untouched. The backbone currently uses one bearer token; run it on infrastructure you control over HTTPS and back up its data volume.
marrow status # shows whether this project is shared or local
marrow unshare # back to local, nothing is deleted
Your agent is told which mode it is working in. You can configure sharing from the dashboard's Manage Projects panel. The local dashboard still visualizes the local project store; shared-memory reads and writes happen through the agent's MCP tools. Full scope and deployment guidance are in deploy/README.md. Code anchors and freshness checks need the source tree, so they remain local-only.
Prebuilt binaries, no Rust:
curl -fsSL marrow.works/install.sh | sh
From source:
cargo install --git https://github.com/aryawidjaja/marrow marrow-cli marrow-mcp marrow-web marrow-server
This puts marrow, marrow-mcp, marrow-serve, and the cross-device marrow-server on your PATH.
irm marrow.works/install.ps1 | iex
Or with Scoop:
scoop install https://github.com/aryawidjaja/marrow/releases/latest/download/marrow.json
Either way you get marrow, marrow-mcp, marrow-serve and marrow-server, no admin rights, no Rust, semantic search already built in.
Just want it in Claude Desktop? Download marrow-mcp.mcpb from Releases and double-click. No terminal at all: it asks which project to remember and that is the whole setup.
The hooks that warm-start sessions and stop two agents editing the same file are shell scripts, so they need Git for Windows and jq. The installer says so if either is missing:
winget install Git.Git jqlang.jq
Without them memory still works; th
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