MCP.Market

Khwan MCP server

by khwan.ai·ai.khwan/khwan-mcp·v0.3.12

Durable AI memory: recall distilled facts in a later session or subagent, and remember new ones.

C60/100grade C
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Safety scan
C60/100

full report

Adoption
Growing

0 stars48 downloads/wk

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Public scan report

scanner v0.1.10 · 2026-10-31 · same rubric, same numbers if you re-run it

1 high
  • Code scan6 source files scanned25/25
  • Live reliabilityremote unreachable: TypeError: fetch failed0/20
  • –Tool poisoningtools not inspected (endpoint requires auth); not countedn/a
  • Auth qualitystatic API keys via environment variables6/15
  • Maintenancelast push 65 days ago12/15
  • Maintainer identityendpoint served from the registry-verified namespace domain8/10

Findings (1)

  • highRemote endpoint did not respondreliability.unreachable

    TypeError: fetch failed

Overall 60/100. Components that don't apply are left out of the denominator. Any critical finding is an F.RubricAppeal a findingJSON

How Khwan compares

Against every graded MCP server, from our own scans and uptime checks. Updated after each scan run.

Safety score
60/100
higher than 15% of 48,255 servers
Downloads a week
48
more than 40% of 12,191 servers with a package

Install Khwan in Claude Code, Cursor or VS Code

claude mcp add --transport http khwan-mcp https://mcp.khwan.ai/mcp/{core}/{user}
Add to Cursor

What the publisher says

From the Khwan repository's README, as published. We do not edit it. Read it on GitHub

khwan-mcp

Durable memory that survives the session. An MCP server that plugs Khwan — a pure AI-memory layer — into Claude Code, Claude Desktop, or any MCP client.

Khwan never runs your model. The client is the model. Its job is to persist and distil what matters into a brain you can recall in a later session or seed a subagent with — a compact, bounded set of facts instead of a replayed transcript. One account can hold many isolated cores (brains), and — on paid plans — an isolated sub-brain per end-user.

Nothing on the read or write path costs you an inference call: khwanrecall and khwanremember make none. Khwan does run one model of its own, on a schedule — a nightly pass that distils stored turns into standing lessons. A real production run was 8 brains and 245 stored turns distilled into 11 lessons, for $0.0094. That pass is Khwan's cost, not yours, and it is the whole difference from memory layers that compress, graph, or consolidate on every turn.

<!-- The MCP Registry verifies ownership of a PyPI package by finding this name in the package README, which is what PyPI shows as the description. It must match name in server.json, and it only reaches PyPI on the next release — so do not rename one without re-releasing. --> <!-- mcp-name: ai.khwan/khwan-mcp -->

How it saves tokens (and where it doesn't)

Be honest about the mechanism — an MCP adds to a host's context, it cannot replace the transcript the host already sends. So:

growing history (cache reads ≈ 0.1×), so re-injecting memory every turn only adds. Don't do that here.

  • Within one hot session, it does not save tokens. Claude Code caches its

ends. Khwan persists distilled facts so the next run recalls them cheaply — no cold-replay of an old transcript, and facts that already scrolled out of context are retrievable again.

  • Across sessions and subagents, it does. A cache dies in minutes; a session

The token-smart pattern: seed once, remember durable facts (below), rather than running the full loop on every turn of a caching host. The full prepare → record loop still shines in a custom agent on a non-caching host, where replacing history with distilled memory bounds per-turn cost directly.

Install

pip install khwan-mcp          # or: uvx khwan-mcp

Connect to Claude Code

claude mcp add khwan --scope project \
  -e KHWAN_CORE=default \
  -- khwan-mcp

--scope project writes .mcp.json into the repo, so the setting travels with the project. Note what is not in that command: the key.

Keeping the key out of the repo

claude mcp add -e KHWANAPIKEY=… writes the literal value into .mcp.json — a file whose whole point is being committed. Two ways to avoid that, and the second is the one that works everywhere:

Shell environment. Leave KHWANAPIKEY out of the config entirely and export it in the shell that launches claude. The server inherits it.

export KHWAN_API_KEY=kwk_live_xxx

A launcher (works in the desktop app too). A desktop app is started from a dock or menu, not a login shell, so it inherits none of your shell exports and the approach above silently yields no key. Read it from a file instead:

mkdir -p ~/.khwan && chmod 700 ~/.khwan
printf 'KHWAN_API_KEY=kwk_live_xxx\n' > ~/.khwan/env && chmod 600 ~/.khwan/env

cat > ~/.khwan/khwan-mcp <<'SH'
#!/bin/sh
set -a
[ -f "$HOME/.khwan/env" ] && . "$HOME/.khwan/env"
set +a
exec khwan-mcp "$@"
SH
chmod 700 ~/.khwan/khwan-mcp

Then point the config at the launcher and keep only non-secret settings inline:

claude mcp add khwan --scope project \
  -e KHWAN_CORE=acme -e KHWAN_USER=Web \
  -- ~/.khwan/khwan-mcp

.mcp.json is now safe to commit, and every new repo costs two lines instead of a pasted key. Anyone else on the team writes their own ~/.khwan/env.

Shortened. The full README is on GitHub.

Nothing above is checked by us. What we check is on the safety report.

Khwan: common questions

Is Khwan MCP server safe?
With care: it is graded C, so read the findings first (60/100). Read the Khwan safety report
How do I install Khwan?
It runs remotely at mcp.khwan.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 Khwan need an API key?
Yes. The registry entry asks for KHWAN_API_KEY.
Is Khwan maintained?
The last commit was 69 days ago (2026-08-27). The latest release is v0.3.12.
What can I use instead of Khwan?
Servers from other publishers that do the same job: Deja Vu MCP server and Knowl MCP server.
How does Khwan compare with other MCP servers?
safety score 60/100 (higher than 15% of 48,255 servers); downloads a week 48 (more than 40% of 12,191 servers with a package). Full comparison.

Alternatives to Khwan

Same job from other publishers: the closest match first, then the best rated.

  • Deja Vu
    deja-vu: local memory over the session histories of forty-three coding agents.
    A
  • Knowl
    Persistent memory for AI agents, for code, research and everyday life. Stale facts retire.
    A