Korely Memory MCP server
online · 100% uptimeai.korely/memory·v1.0.1Memory for AI agents that knows what is still true. Typed bi-temporal facts, EU-hosted.
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Korely Memory tools
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Public scan report
scanner v0.1.10 · 2026-10-15 · same rubric, same numbers if you re-run it
- –Code scanremote-only server, no package to scann/a
- Live reliabilityremote reachable in 471ms (auth required)20/20
- –Tool poisoningtools not inspected (endpoint requires auth); not countedn/a
- Auth qualityOAuth resource metadata advertised on 40115/15
- Maintenancelast push 0 days ago15/15
- Maintainer identityendpoint served from the registry-verified namespace domain8/10
How Korely Memory compares
Against every graded MCP server, from our own scans and uptime checks. Updated after each scan run.
- Safety score
- 97/100
- higher than 98% of 48,243 servers
- Uptime
- 100%
- of our recent checks; the typical remote server answers 100%
- Response time
- 1,011 ms
- faster than 13% of 30,027 servers
Release history: 2 versions in the registry since 2026-09-08, latest 2026-10-15, typically one every 37 days.
Install Korely Memory in Claude Code, Cursor or VS Code
claude mcp add --transport http memory https://api.korely.ai/agent/mcp
What the publisher says
From the Korely Memory repository's README, as published. We do not edit it. Read it on GitHub
Korely Memory
Memory for AI agents that knows what is still true.
Korely stores what your agent learns as typed facts with a validity window. When something changes, the old fact is superseded instead of overwritten. Your agent reads the current truth, and you can still ask what was true on any past date.
import time
from korely_memory import Korely
korely = Korely() # reads KORELY_API_KEY from the environment
korely.add("Maria is on the Pro plan, billed yearly.", user_id="maria")
korely.add("Maria downgraded to Free.", user_id="maria")
time.sleep(10) # facts are extracted server-side; see "Writes settle asynchronously"
ctx = korely.get_context(query="what plan is Maria on?", user_id="maria")
print(ctx.context)
# ## Known facts
# - Maria downgraded_to Free (since 2026-09-08)
# - Maria billing_frequency yearly (since 2026-09-08)
#
# Pro is gone from the current facts. It was superseded, not deleted.The exact predicate is chosen by the extractor, so downgradedto here might be subscribesto or plan on your run. What is guaranteed is the behaviour: the old value leaves the current set, and stays retrievable with its invalid_at.
Nothing was deleted. The Pro fact is still there, carrying invalid_at and a pointer to what replaced it:
korely.get_facts(user_id="maria", include_invalidated=True)
# Maria downgraded_to Free valid_from=... invalid_at=None
# Maria plan Pro valid_from=... invalid_at=2026-09-08T08:31:09ZTime travel over real dates
Pass timestamp when the event happened in the past, and facts inherit it as validfrom. Then asof answers over the world's timeline, not your ingestion order:
korely.add("Franco signed up on the Pro plan.", user_id="franco", timestamp="2026-01-15")
korely.add("Franco downgraded to Free.", user_id="franco", timestamp="2026-06-20")
korely.get_facts(user_id="franco", as_of="2026-03-01") # subscribes_to -> Pro plan
korely.get_facts(user_id="franco", as_of="2026-08-01") # subscribes_to -> Free
korely.get_facts(user_id="franco") # subscribes_to -> FreeWithout timestamp every fact starts being true the moment you write it, so as_of on an earlier date returns nothing. That is correct, and usually not what you want when you are importing history.
Writes settle asynchronously
add() returns as soon as the memory is stored, then extraction runs server-side. That means:
The time.sleep(10) above exists only so the snippet works when you paste it. You do not need it in production: an agent writes at the end of one turn and reads at the start of the next, and by then the facts are there.
If you do need to know exactly when, ask instead of guessing. Every memory carries a status of processing, ready, or error, and events() reports what is still in flight:
korely.events()
# {"events": [{"memory_id": "mem_...", "status": "ready", ...}], "processing": 0}processing: 0 means every write you sent has been extracted. Batch imports can wait on that one number instead of walking every id. If you can receive webhooks, fact_extracted pushes the same signal without polling.
Install
pip install korely-memory # Python, plus the `korely` CLI
npm install korely-memory # Node / TypeScriptBoth clients have zero runtime dependencies.
Get a key
The hobby tier is free and needs no signup form:
curl -X POST https://api.korely.ai/v1/agents/init \
-H 'Content-Type: application/json' \
-d '{"agent_caller": "your-name-here"}'The response carries a korlive key. Set it as KORELYAPIKEY and the SDK, the CLI, and the REST API all authenticate with it.
Shortened. The full README is on GitHub.
Nothing above is checked by us. What we check is on the safety report.
Korely Memory: common questions
- Is Korely Memory MCP server safe?
- Yes, by our scan: it is graded A (97/100). Read the Korely Memory safety report
- How do I install Korely Memory?
- It runs remotely at api.korely.ai. Add it to Claude Code, Cursor, VS Code or Claude Desktop with the snippets above, or call it through the mcp.market gateway without installing anything.
- Does Korely Memory need an API key?
- No key to paste: it signs you in with OAuth when your client connects.
- Is Korely Memory maintained?
- The last commit was 21 days ago (2026-10-15). The latest release is v1.0.1.
- Is Korely Memory up?
- 100% of our last 28 checks got an answer. We check remote servers about four times a day.
- What can I use instead of Korely Memory?
- Servers from other publishers that do the same job: Knowl MCP server.
- How does Korely Memory compare with other MCP servers?
- safety score 97/100 (higher than 98% of 48,243 servers); uptime 100% (of our recent checks; the typical remote server answers 100%); response time 1,011 ms (faster than 13% of 30,027 servers). Full comparison.
Alternatives to Korely Memory
Same job from other publishers: the closest match first, then the best rated.
KnowlPersistent memory for AI agents, for code, research and everyday life. Stale facts retire.not reviewedEstablishedA