MemFork
Git for agent memory, shared by every AI tool on your machine. Fork, merge, discard and rewind what an agent remembers — forking costs the same whatever memory holds, so an agent can branch before a risky step and throw the branch away if it goes wrong — and hand work from one agent to another through a store every MCP client shares.
pip install memfork
One wheel, two things.
The engine, in your process
import memfork
db = memfork.Database()
db.put("plan:1", b"the original plan")
db.fork("attempt")
db.put("plan:1", b"a risky rewrite", branch="attempt")
db.get("plan:1").value # b'the original plan' — the fork is invisible here
db.merge("attempt") # or db.discard("attempt")
Branches are cheap because they share structure rather than copying. You can
also read memory as it was earlier: db.at("plan:1", seq).
The MCP server, for your agent clients
The same install puts the memfork command on your path:
memfork init # register the server with the MCP clients you have
memfork doctor # what is installed, and what is talking to it
Clients then get sixteen tools — store, recall, search, fork, merge, discard, time travel, and handing work from one agent to another — over one store they share. With a single client that still pays: its next session resumes where the last one stopped.
MemFork itself sends nothing anywhere: no cloud, no account, no telemetry. What an agent reads from it becomes part of that agent's prompt and goes wherever that agent already sends your code; with a local model the whole loop stays on your machine.
What is in memory and what is on disk
memfork.Database is in memory only. It does not write to disk, and it
does not see what an MCP client wrote: the durable, shared store belongs to the
MemFork daemon, which the memfork command starts when something needs it.
That split is deliberate — the engine is I/O-free by design — but it does mean a Python program that wants the shared memory talks to the server rather than importing it. Binding the durable store is later work.
More
Full documentation, the CLI reference and the design spec: https://github.com/memforkdb/memfork
Apache-2.0.
1 maintainer
Metadata
1 maintainer
Release files for memfork 0.3.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| memfork-0.3.0.tar.gz | 413.0 kB | Details |
Built distributions (wheels)
| File | Reset | |||
|---|---|---|---|---|
| memfork-0.3.0-cp39-abi3-win_arm64.whl | CPython 3.9 | abi3 | Windows ARM64 | Details |
| memfork-0.3.0-cp39-abi3-win_amd64.whl | CPython 3.9 | abi3 | Windows x86-64 | Details |
| memfork-0.3.0-cp39-abi3-musllinux_1_2_x86_64.whl | CPython 3.9 | abi3 | Linux musl 1.2+ x86-64 | Details |
| memfork-0.3.0-cp39-abi3-musllinux_1_2_aarch64.whl | CPython 3.9 | abi3 | Linux musl 1.2+ ARM64 | Details |
| memfork-0.3.0-cp39-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl | CPython 3.9 | abi3 | Linux glibc 2.17+ x86-64 | Details |
| memfork-0.3.0-cp39-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl | CPython 3.9 | abi3 | Linux glibc 2.17+ ARM64 | Details |
| memfork-0.3.0-cp39-abi3-macosx_11_0_arm64.whl | CPython 3.9 | abi3 | macOS 11.0+ ARM64 | Details |
| memfork-0.3.0-cp39-abi3-macosx_10_12_x86_64.whl | CPython 3.9 | abi3 | macOS 10.12+ x86-64 | Details |
Total release size: 47.4 MB
Release files / memfork-0.3.0.tar.gz
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