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पब्लिशर की अपनी कमांड। PlugMCP एंडपॉइंट नहीं।
Host a copy with our keys and logs.
uvx memory-hive-mcp==0.1.9Claude Code में लोकल कमांड के लिए इंस्टॉल लिंक नहीं है। नीचे दी गई कमांड कॉपी करें और टर्मिनल में चलाएँ।
HIVE_MODE=<value> HIVE_DB=<value> HIVE_AGENT_ID=<value> HIVE_AGENT_TOKEN=<secret> HIVE_MCP_URL=<value> claude mcp add io.github.330899935-hive-memory -- uvx memory-hive-mcp==0.1.9टर्मिनल में चलाएँ।
{ "mcpServers": { "io.github.330899935-hive-memory": { "command": "uvx", "args": [ "memory-hive-mcp==0.1.9" ], "env": { "HIVE_MODE": "<value>", "HIVE_DB": "<value>", "HIVE_AGENT_ID": "<value>", "HIVE_AGENT_TOKEN": "<secret>", "HIVE_MCP_URL": "<value>" } } }}claude_desktop_config.json
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लॉन्चपब्लिशर से
Also known as: Apiary Memory · 记忆蜂巢 · Memory Hive · 蜂巢 ·
apiary-memoryon PyPI andio.github.330899935/apiary-memoryon the MCP Registry (from v0.2.0) · old namesmemory-hive-mcp/hive-memory(v0.1.9 and earlier) still install and still work. Not affiliated with hive.com (team collaboration) or the Claude Code plugin.
Local-first memory over MCP. Built-in SQLite store; runs standalone. Agents propose; you confirm.
hive-mcpLocal-first personal memory for AI agents, over MCP. Your agents can search what you have confirmed and propose what they think you should keep; only you can confirm it. Everything lives in one file on your own disk, and nothing is sent anywhere.
It runs on its own. A working SQLite memory store ships inside this package — no account, no cloud, no daemon, no dependencies.
pip install apiary-memory
Desktop app, no terminal: download apiary-memory-0.2.0.mcpb and double-click it.
Measured on 2026-10-27, on one MacBook with the Hive running locally — script and raw output in bench/:
Retrieval used each entry's own title as the query — an easy set. It shows the index is complete and ranks correctly on exact terms, not how well it answers a question asked in your own words. Run bench/bench_search.py on your own Hive.
A complete, if modest, memory server. On a machine with nothing else installed:
Storage is SQLite at ~/.memory-hive/hive.db by default. Search is lexical — character bigrams
for Chinese, words for Latin script — so it ranks well when the words overlap and finds nothing
when they do not. There are no embeddings and no vector index. Every response says
"mode": "local" so you can always tell which engine answered.
Without the app, the database is plain SQLite: it is not encrypted. That is stated here rather than discovered later — see Honest limits.
Apiary Memory for macOS is the same design with the expensive parts built: eight vaults with four of them locked behind a PIN (Argon2id-wrapped key, AES-256 at rest), a daily evolution log, multi-agent identity management, and a UI for reading and confirming. It also answers MCP itself, with richer ranking.
If the app is running, this package uses it and leaves the local file alone. If it is not, the local store answers. You do not have to choose up front:
One rule holds in every mode: if the app is running and answers with an error, that error is returned unchanged. Falling back on a refusal would write your memory into a second database while your client believed it had reached the app. Silent data forking is worse than an error message, so a reply from the app is final. The fallback fires on a connection failure, and on nothing else.
pip install apiary-memory # the server: apiary-memory (was apiary-memory)
# the human's CLI: apiary-memory-cli (was apiary-memory-cli)
Python 3.8 or newer. There is nothing else to install — the package uses only the standard
library, and sqlite3 is part of it.
From a checkout:
git clone https://github.com/330899935/apiary-memory
cd apiary-memory
PYTHONPATH=src python -m hive_mcp.stdio
Any MCP host that can run a stdio command will work. The minimum is the command; everything else is optional.
Claude Desktop — ~/Library/Application Support/Claude/claude_desktop_config.json:
{
"mcpServers": {
"apiary-memory": {
"command": "apiary-memory",
"env": { "HIVE_MODE": "local" }
}
}
}
Cursor — ~/.cursor/mcp.json, same mcpServers shape.
Any host that only speaks HTTP — start the app and point it at http://127.0.0.1:8768/mcp
with the headers X-Hive-Agent and X-Hive-Token. This package is the stdio path; the HTTP
endpoint belongs to the app.
None, for the local store — install the package and it works. A running app is a prerequisite
only for the app's own features: encrypted vaults, the evolution log, and multi-agent identity.
If you want those, install the Hive app (macOS,
version 1.4.5 or newer) and leave HIVE_MODE at auto.
The six tools are the whole surface. They are the same six whether the app or the local store
answers; only the ranking behind them differs — and, for two inputs, whether they exist at all.
The app accepts precomputed embeddings (recall.query_vector, propose.vector); the local
store has no embedder, so tools/list omits those two wherever the local store can answer,
including under auto where the app might stop answering mid-session. A field that would be
accepted and silently ignored is not advertised at all.
The same rule covers wording. recall.query is described as the lexical ranker it is wherever
the local store can answer — words and character bigrams, no embeddings — and as the app's
index-based ranking with query_vector for meaning wherever only the app can answer. A
description is a claim about what will happen to the input, so it is narrowed with the inputs.
Defaults are not narrowed, they are shared. Omit limit and you get 10 from recall and 8 from
get_context; omit compact and bodies come back trimmed; omit ttl on say and the card
lives 24 hours. Both engines answer those numbers identically, because a default is a number in
the schema rather than a capability one engine lacks. store.py holds each one as a named
constant, and the tests compare the answer against the advertised number instead of a second
hand-written copy of it.
Two properties are worth stating plainly, because they are the product:
propose succeeding means "queued", not "stored". recall will not return it until a
human confirms it.manage has no approve action. There is no path from an agent to a confirmed memory.
That is not an omission; it is the design.tools/list is one surface for both engines, and an answer should be too: a model that has
to branch on which engine replied will eventually branch wrong. board therefore answers
the app's shape, field for field — items, unread, count, cursor, reader — and
cursor is the id of the newest card, the same kind of value the app returns.
The cursor is what a poll carries across an engine switch, which is why it gets the space.
Under auto one call can be answered by the app and the next by the local store. Before 0.1.9
the local engine answered a float epoch timestamp and read the app's card id with float(),
so a cursor fetched from the app came back as a full re-read of the board and nothing said
so; a float sent the other way matched no card id, and the app answered with its newest
limit, equally quietly.
A cursor can still fail to resolve: its card expired (cards live 24 hours by default), or it
was issued by the other engine, whose ids are CB… in the app and msg_… here. Neither
engine can resume from that, so both return the newest window — but this one also sets
since_unknown and a note saying which of those happened. unread counts every live card
after the cursor and count counts what the answer carries, so unread > count means the
page did not cover everything waiting, and the note says so in words.
Three shapes are not unified, because the engines really do hold different data:
recall entry names its vault vault from the local store and wh from the app;get_context returns one flat digest locally and one bucket per warehouse (context,
keyed by warehouse name) from the app;roster entries share agent_id; locally they also carry messages and last_seen,
while the app adds its registry card — display name, seat, leases, current task — which a
SQLite file has no way to know.Agents propose. You confirm. The confirmation lives in a terminal, in a command you have to type — deliberately not a tool an agent can call.
apiary-memory-cli list # what is waiting
apiary-memory-cli show <id> # read one in full
apiary-memory-cli approve <id> # confirm it, or --all
apiary-memory-cli reject <id> # drop it for good
apiary-memory-cli search "deploy key" # search confirmed memory
apiary-memory-cli forget <id> # soft delete, reversible
apiary-memory-cli restore <id> # undo forget
apiary-memory-cli stats # counts and the database path
apiary-memory-cli export --out dump.json
apiary-memory-cli path
--db <path> on any command points at a different database. HIVE_DB does the same from the
environment.
~/.memory-hive/hive.db, unless HIVE_DB says otherwise. One SQLite file; copy it to back it
up, delete it to start over.
The board keeps its messages in the same file, so there is only ever one thing to back up. Cards
expire: 24 hours unless ttl says otherwise, clamped to between 60 seconds and 30 days, which
is what the app does too — a board that grows forever stops being a board.
Chinese text is indexed as single characters plus overlapping character bigrams; Latin text as words. A query is scored by how much of it the entry covers, then nudged by recency — a 10% multiplier, enough to break ties and not enough to overturn relevance.
This is a ranker, not an understander.
0.8 means "closer than 0.4 for this query", not "80% confident".
They are not comparable across queries.tools/list says "words and character
bigrams ... no embeddings" here, and that sentence is true of this engine. It is narrowed per
engine like the embedding inputs are, because the app's answer to the same question differs.recall says so and mentions how many
entries are awaiting confirmation, rather than returning a plausible neighbour.HIVE_AGENT_ID and HIVE_AGENT_TOKEN are not required to use the local store. They are
read straight from the environment and never written to disk by this package.
Written down because a memory tool that oversells itself is worse than one that does less.
stats reports
"encrypted": false instead of leaving you to find out.recall."no confirmed memory matched this query" with entries pending. Correct behaviour. Confirm
them: apiary-memory-cli list, then approve.
A call fails with a message about HIVE_AGENT_ID. The app answered and refused the
credential. The call did not fall back to the local store, on purpose. Register an agent in
the app and set both variables, or set HIVE_MODE=local if you meant to use the local file.
"Hive app not reachable ... and HIVE_MODE=remote forbids the local fallback". You asked for
the app only and it is not running. Start it, or drop HIVE_MODE=remote.
Where did my memory go? apiary-memory-cli stats prints the database path. If HIVE_MODE
is auto and the app is running, the app has been answering — the local file is untouched by
design.
PYTHONPATH=src python -m unittest discover -s tests -v
The suite needs no running app and no network: it stands up its own fake backend where a real
response is required, and points HIVE_DB at a temporary file so a test never touches a real
memory database.
Layout:
src/hive_mcp/store.py the memory engine (SQLite, stdlib only)
src/hive_mcp/stdio.py the MCP server: routing, envelopes, the app bridge
src/hive_mcp/cli.py the human's half: review and confirm
src/hive_mcp/tools.json the tool surface snapshot for the offline path
MIT. Your memory file is yours; nothing here phones home.
Local-first memory over MCP. Built-in SQLite store; runs standalone. Agents propose; you confirm.
{ "mcpServers": { "io.github.330899935-hive-memory": { "command": "uvx", "args": [ "memory-hive-mcp==0.1.9" ], "env": { "HIVE_MODE": "<value>", "HIVE_DB": "<value>", "HIVE_AGENT_ID": "<value>", "HIVE_AGENT_TOKEN": "<secret>", "HIVE_MCP_URL": "<value>" } } }}टूल
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FAQ
इस पेज पर Cursor, Claude Desktop, Claude Code या VS Code के लिए stdio कॉन्फ़िग कॉपी करें। यह पब्लिशर का इंस्टॉल इस्तेमाल करता है, PlugMCP प्रॉक्सी नहीं।
पब्लिशर ने ये एनवायरनमेंट वेरिएबल बताए हैं: HIVE_MODE, HIVE_DB, HIVE_AGENT_ID, HIVE_AGENT_TOKEN, HIVE_MCP_URL।
Memory Hive stdio पर लोकल चलता है।
पिछली जाँच 2026-11-08 को हुई। Local-first memory over MCP. Built-in SQLite store; runs standalone. Agents propose; you confirm.