Observed since 20 Oct, 21:36 UTC
No superseded metadata states collected. Unchanged observations do not create new revisions.
Give your agent a filing cabinet.
Give your agent a filing cabinet.
Ask an agent what it remembers about you and there's usually no way to check the answer. The memory lives inside a vector index or a database somewhere, opaque even when the agent gets it right.
agent-cabinet keeps everything your agent learns as ordinary text
files: each memory is a Markdown file with a short YAML header. You can
read, edit, or delete each memory directly, or query it later.
Obsidian is a great tool, and you can even tell agent-cabinet to write into an Obsidian vault
instead of its own directory.
There are two main differences.
First, who's writing. Obsidian is built for a person writing by hand,
so its frontmatter is freeform: that flexibility is the point.
agent-cabinet's frontmatter is structured and schema-validated
instead, following the ORC
spec for shaping this kind of claim. Nothing else catches a malformed
or missing field for an agent writing unsupervised.
Second, Obsidian is an application first. Extending it means writing a
plugin that runs inside Obsidian itself, not linking a library into your
own service, so another program can't just call into it directly.
agent-cabinet is meant to be a dependency that applications build on, not an application in itself.
From your project's git repo, run:
pip install agent-cabinet
agent-cabinet init
init creates a .cabinet directory at your project's root and tells
your agent it exists, by writing to AGENTS.md/CLAUDE.md (see below).
That only works if your agent actually reads one of those files —
most do it automatically, but check yours does, or has actually picked up
the change, before assuming it knows agent-cabinet is there.
agent-cabinet remember "The user prefers dark mode." --kind preference --basis stated
agent-cabinet recall "theme preference" --json
Either you or your agent can run these directly.
To see what's stored, you have two options:
.cabinet directory and read the files directly. Each entry
is one .md file with YAML frontmatter. There's no export step, no
hidden format, so you can just read it.agent-cabinet has built-in ranked search. See
agent-cabinet recall "<query>" above.On init, agent-cabinet finds the project root by walking up from your
current directory until it finds .git (or the current directory, if
you're not in a git repo yet).
This project root will then hold two new entries:
.cabinet is a directory built at <project root>/.cabinet.AGENTS.md, created if it doesn't exist yet, with a short block
telling your agent agent-cabinet is available. This is the file most
agents (Cursor, Copilot, Codex, Windsurf, Cline, ...) read natively, so
it's the source of truth.CLAUDE.md, created if it doesn't exist yet, with a one-line
@AGENTS.md import. Claude Code is the one agent that won't otherwise
ever load AGENTS.md on its own, so this is what tells it to — a
no-op for every other agent.Want .cabinet somewhere else, like inside an Obsidian
vault? Override with --root <path> or the
AGENT_CABINET_ROOT environment variable. Note this only moves
.cabinet: AGENTS.md/CLAUDE.md always go to the project root
found above, regardless of --root.
Promoting a note to a fact is just adding evidence to the same entry:
call file() on the same id with evidence/provenance filled in
and overwrite=True, and it replaces the note in place. Those fields
are optional on file() too, though. What actually makes something a
fact is only ever whether they're filled in, not which function wrote
the entry.
remember() writes down what you tell it, exactly as told. file() is
for a claim something else has already checked, usually a pipeline that
computed it and can show its work: a dict with an id, a type, a
scope saying where it came from, and the statement itself required,
plus optional evidence and provenance fields for showing that work.
(This shape is called ORC,
short for OpenReasoningComponents, in case you want other tools to read
the same files; you don't need to know that name to use any of this.)
Here's the actual file remember("The DB is Postgres, not MySQL.")
writes:
---
id: example-project/the_db_is_postgres_not_mysql
type: domain_knowledge
scope: { source: example-project }
---
The DB is Postgres, not MySQL.
And this promotes it in place, once something verifies the claim:
cabinet.file({
"id": "example-project/the_db_is_postgres_not_mysql",
"type": "domain_knowledge",
"scope": {"source": "warehouse-connection-check"},
"statement": "The DB is Postgres 16.2, confirmed by direct connection.",
"evidence": {"confirmed_by": "SELECT version() -> PostgreSQL 16.2"},
"provenance": {"derivation": "check_db_dialect", "derivation_version": "a1b2c3"},
}, overwrite=True)
Which overwrites the file in place to be:
---
id: example-project/the_db_is_postgres_not_mysql
type: domain_knowledge
scope: { source: warehouse-connection-check }
evidence: { confirmed_by: "SELECT version() -> PostgreSQL 16.2" }
provenance: { derivation: check_db_dialect, derivation_version: a1b2c3 }
---
The DB is Postgres 16.2, confirmed by direct connection.
The server is one command: agent-cabinet mcp. As with most local MCP
servers, it defaults to stdio. Your client runs the command itself and
owns the process, so there's nothing you start or keep running yourself.
Here's how to point common clients at it (all three clients below can already call agent-cabinet remember/recall
directly as shell commands once you run agent-cabinet init).
Claude Code
claude mcp add agent-cabinet -- agent-cabinet mcp
Cursor
Add to .cursor/mcp.json:
{ "mcpServers": { "agent-cabinet": { "command": "agent-cabinet", "args": ["mcp"] } } }
Codex CLI
codex mcp add agent-cabinet -- agent-cabinet mcp
Multiple clients
Want one server shared by more than one client, or a client on another
machine? agent-cabinet mcp --transport http --port 7879 binds a port
instead. You run and keep that one alive yourself; clients point at
http://localhost:7879/mcp.
The same remember/recall calls, direct from Python, the way you'd
embed agent-cabinet in your own service instead of shelling out:
from agent_cabinet import Cabinet
cabinet = Cabinet("./.cabinet", namespace="example-project")
cabinet.remember("User said the DB is Postgres, not MySQL.", basis="stated")
cabinet.recall("database")[0].body
# 'User said the DB is Postgres, not MySQL.'
--root takes any directory, so pointing it at a folder inside a real
vault works as-is:
agent-cabinet init --root ~/MyVault/agent-notes
Every entry is a standard frontmatter Markdown file, so Obsidian shows it as a real note: Properties panel, full-text search, all of it.
Two things worth knowing. relations/links are plain strings
(acme/other), not Obsidian's [[wikilink]] syntax, so they won't wire
into Obsidian's own graph view or backlinks panel on their own. And
hand-editing a note through Obsidian's Properties UI is exactly the kind
of edit this is built to tolerate: a required field going missing, or the
id property getting retyped, produces a clean error for that one entry
rather than breaking recall() for the rest of the cabinet.
agent-cabinetagent-cabinet is meant to be a foundation other systems build on,
not a finished memory system. Most memory needs (versioning,
multi-agent sync, semantic search) are use-case-specific, so the
substrate underneath stays simple and deterministic instead of
guessing at which one any given system will need. Every opinion below
follows from that.
agent-cabinet, dependencies are declared explicitly, not extracted
from conversation the way Zep
does it, so an edge is never wrong, but it also only exists if
something actually declared it: no hallucinated dependency, but no
free discovery of one nobody wrote down either. Automatic discovery
is a layer you can add on top, not something decided here.agent-cabinet, a memory just records whether a belief was stated,
inferred, observed, or assumed, not a numeric confidence score the
way
Mem0
computes one, so you get a category you can read instead of a number
you just have to trust. A computed score, if you want one, is a
layer to add on top.agent-cabinet, dedup, schema
validation, and ranked search are guarantees the code provides, not
rules written into AGENTS.md and hoped for every session, so a
forgotten rule can't let duplicate notes pile up or a malformed file
break search unexpectedly: the common guarantee every use case would
otherwise have to build for itself.agent-cabinet, results are ranked with BM25 over a
small, rebuildable index, not a vector database the way
Memsearch pairs markdown
with one, so there's no embedding API key or vector store to run,
and deleting the index by accident costs nothing: it just rebuilds
from the files. Semantic search is a layer to add on top, not a
dependency baked in for everyone.agent-cabinet, the same entry just gets more evidence added
directly, not a new linked record the way
Memora creates when it
supersedes a claim, so there's never a question of which of two
records is current: there's only ever one. A use case that wants
lineage can build it on relations and metadata instead.Apache-2.0.
Download counts and popularity will appear here as the collector receives them.
| Version | Published | Direct dependencies | Open version |
|---|---|---|---|
| 0.1.2Yanked | 16 Sept 2026 | 8 |
This describes our collected data; it is not a security assessment.
Observed since 20 Oct, 21:36 UTC
No superseded metadata states collected. Unchanged observations do not create new revisions.
package:ec604d30220501d166fa2818642749bad80f5a9968a34a576b5326e9d4326be2