memra-local
Local-first memory server for AI agents. Offline, private, fast.
memra-local gives your coding agent persistent memory that lives entirely on your machine — no account, no network, no data leaves the laptop. Works with Claude Code, Cursor, Zed, Droid, Hermes Agent, OpenClaw, and any MCP-compatible client.
When you're ready to sync across devices or share with a team, a single command pushes your local namespace to Memra Cloud. Same tools, same API, your choice.
Install
pip install memra-local
memra mcp # start the MCP server
Requires Python 3.10+.
Wire it into your editor
Claude Code / Cursor
{
"mcpServers": {
"memra": {
"command": "memra",
"args": ["mcp"]
}
}
}
Zed
{
"context_servers": {
"memra": {
"command": { "path": "memra", "args": ["mcp"] }
}
}
}
Droid (Factory.ai) / Hermes Agent / OpenClaw
See usememra.com/install for client-specific snippets.
What you get
- Flat-file memory in
~/.memra/— plain YAML, inspectable, greppable, diff-able - MCP server exposing
memra_add,memra_recall,memra_get,memra_list,memra_supersede,memra_history, and more - Local embeddings via
fastembed(ONNXmultilingual-e5-small, ~100 languages) — no OpenAI key, no PyTorch - Sync to cloud optional:
memra sync enable <namespace> --api-key memra_live_...
Commands
memra mcp # MCP server over stdio
memra status # store health: scope, memory count, disk usage, sync
memra hooks install # optional — auto-capture decisions/patterns as you work
memra --help # full CLI reference
Docs + source
- Install snippets and client configs: https://usememra.com/install
- Memra Cloud (hosted EU): https://usememra.com
- Source: https://github.com/usememra/memra-local
License
BUSL-1.1. Change Date 2030-04-17 — on that date the license auto-converts to Apache-2.0. Until then, personal and non-production use are unrestricted; commercial production use requires a separate license.
Metadata
Release files for memra-local 4.6.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| memra_local-4.6.2.tar.gz | 47.1 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| memra_local-4.6.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 100.4 kB
Release files / memra_local-4.6.2.tar.gz
| Download URL | memra_local-4.6.2.tar.gz |
|---|---|
| Size | 47.1 kB |
| Tags | Source |
|
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? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.14.7
|
Release files / memra_local-4.6.2-py3-none-any.whl
| Download URL | memra_local-4.6.2-py3-none-any.whl |
|---|---|
| Size | 53.3 kB |
| Tags | Python 3 |
|
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? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.14.7
|