kemory
The command-line client for Kemory, a persistent memory vault for AI agents. You need a Kemory account; sign up at kemory.sekondbrain.ai.
Connect your MCP clients in one command
uvx kemory connect --host all
This signs you in through the browser, writes the Kemory MCP server entry into every MCP client installed on this machine (Claude Code, Claude Desktop, Codex, Cursor, VS Code, Gemini CLI, Windsurf, Cline, Kiro, Grok, Continue, Warp and others), and checks that the connection works. Restart the clients it lists afterwards. Without --host, only Claude Code is connected; --host codex and so on pick one client. It is safe to re-run.
This package contains the native kemory binary for your platform (macOS, Linux or Windows x64); it has no Python dependencies.
Install
uv tool install kemory # or: pipx install kemory
Also available with npx kemory and brew install sekondbrainailabs/s9n/kemory.
Common commands
kemory doctor # check sign-in, network and MCP setup
kemory recall <query> # search your memories
kemory ask <question> # an answer with its evidence
kemory --help # everything else
Source, issues and documentation: https://github.com/SeKondBrainAILabs/kemory-cli
License
MIT
1 maintainer
Metadata
1 maintainer
Release files for kemory 0.7.4
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Built distributions (wheels)
| File | Reset | |||
|---|---|---|---|---|
| kemory-0.7.4-py3-none-win_amd64.whl | Python 3 | none | Windows x86-64 | Details |
| kemory-0.7.4-py3-none-manylinux_2_17_x86_64.manylinux2014_x86_64.musllinux_1_1_x86_64.whl | Python 3 | none | Linux glibc 2.17+ x86-64, Linux musl 1.1+ x86-64 | Details |
| kemory-0.7.4-py3-none-manylinux_2_17_aarch64.manylinux2014_aarch64.musllinux_1_1_aarch64.whl | Python 3 | none | Linux glibc 2.17+ ARM64, Linux musl 1.1+ ARM64 | Details |
| kemory-0.7.4-py3-none-macosx_12_0_x86_64.whl | Python 3 | none | macOS 12.0+ x86-64 | Details |
| kemory-0.7.4-py3-none-macosx_12_0_arm64.whl | Python 3 | none | macOS 12.0+ ARM64 | Details |
Total release size: 19.6 MB
Release files / kemory-0.7.4-py3-none-win_amd64.whl
| Download URL | kemory-0.7.4-py3-none-win_amd64.whl |
|---|---|
| Size | 4.1 MB |
| Tags | Python 3 Windows x86-64 |
|
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
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Transparency logRelease files / kemory-0.7.4-py3-none-manylinux_2_17_x86_64.manylinux2014_x86_64.musllinux_1_1_x86_64.whl
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|---|---|
| Size | 4.0 MB |
| Tags | Linux glibc 2.17+ x86-64 Linux musl 1.1+ x86-64 Python 3 |
|
SHA-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
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Transparency logRelease files / kemory-0.7.4-py3-none-manylinux_2_17_aarch64.manylinux2014_aarch64.musllinux_1_1_aarch64.whl
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|---|---|
| Size | 3.6 MB |
| Tags | Linux glibc 2.17+ ARM64 Linux musl 1.1+ ARM64 Python 3 |
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SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
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Transparency logRelease files / kemory-0.7.4-py3-none-macosx_12_0_x86_64.whl
| Download URL | kemory-0.7.4-py3-none-macosx_12_0_x86_64.whl |
|---|---|
| Size | 4.1 MB |
| Tags | Python 3 macOS 12.0+ x86-64 |
|
SHA-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
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|
Provenance
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Transparency logRelease files / kemory-0.7.4-py3-none-macosx_12_0_arm64.whl
| Download URL | kemory-0.7.4-py3-none-macosx_12_0_arm64.whl |
|---|---|
| Size | 3.7 MB |
| Tags | Python 3 macOS 12.0+ ARM64 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
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