Keymem
Associative key-graph memory for LLM agents — recall by association, not vector similarity.
Connector by donggyun112 · GitHub account verified by the MCP Registry
Chalk Labs
Need help deploying Keymem?
Chalk Labs sets up agents like this inside real teams: connected to your tools, tested on your data, with a human in the loop where it matters.
Install
Works with Claude Code, Codex, VS Code, Cursor, Windsurf, Claude Desktop. Read the repository before you give any tool access to your data.
npx agentmarket install connector/donggyun112-keymem
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
Get the weekly diff
The weekly diff: one email a week with new agent tools, notable updates and grade changes, plus security alerts for tools you follow. Double opt-in, one-click unsubscribe.
About
Reviews
Write a reviewNo reviews yet. Installed it? Reviews come from verified installers only. How reviews work
Permissions
What this server can do and what it asks for, from its tool list, install config and code. Checked Oct 25, 2026.
- Tools
- 5 read · 2 write · 0 delete · 3 not yet classified
- Secrets
- None asked for
- Install scripts
- None found
- Runs as
- Node.js package
Tools by what they do 10
Read from the source code; the running server may list different tools.
Read 5 · Look things up without changing anything.
browse_keysdismissread_keyread_memoryrecall
Write 2 · Create, change, send or run things.
confirm_memorycorrect
Not yet classified 3 · We could not tell from the name and description.
forgetrememberremember_batch
Network hosts it talks to 3
github.com· found in codeglama.ai· found in codehuggingface.co· found in code
Files it touches
/Users/dongkseo/project/super-memory/.worktrees/direct-hydrate-shadow/bench/assoc-fixture.json/Users/dongkseo/project/super-memory/.worktrees/direct-hydrate-shadow/bench/fixture.json- Your home directory (~)
- Any path the agent passes to its tools
Tools (10)
Read from the source code; the running server may differ. Descriptions are the server’s own words; hidden characters are shown as [U+…].
browse_keysBrowse the vocabulary of one namespace when recall has no hit or you need an entry point. Returns active key clusters with hubs first, then by linked-memory count. This is index metadata only; continue with read_key(key_id, query, namespace) and read_memory(memory_id, via_key_id, namespace).
confirm_memoryConfirm that a memory is still current using explicit present evidence. Never call this merely because read_memory returned the content. Use only after a current user assertion, an authoritative current source, or direct observation. Refreshes validity but does not change content or key links. An exact normalized restatement passed as recall's `context` is already auto-confirmed there (check memories[0].auto_confirmed) — this tool is for evidence recall can't see: read_memory results, authoritative sources, or direct observation.
correctUpdate outdated information. Use when user corrects you or info changes (e.g. moved cities, changed job). Old version is preserved but weakened — never lost. Omit keys to keep the same search terms. Omit decay_profile and ttl_seconds to preserve the predecessor's policies; provide either to replace that policy. related_to links the updated memory to other memory IDs.
dismissTell keymem a recalled memory was surfaced by the WRONG key — the fact may be fine, it just should not have come up for this query. Pass the memory_id and the key_id it arrived under (recall returns both). Weakens that one key->memory link so the pairing ranks lower next time, and cancels any pending alias learning for it. The memory itself, its other keys, and its content are untouched, and the link is floored rather than severed, so nothing becomes unreachable. Use correct() when the fact changed and forget() when it is simply wrong.
forgetPermanently delete a memory. Only use for completely wrong information. For outdated info, use correct() instead — it preserves history.
read_keyList the memories stored under one key (concept), ranked. Returns the canonical key, its aliases, and hub metadata plus ranked memory IDs, metadata, and validity — never memory content. Pass a focused query for the missing fact and the active namespace when known: handles are then ranked by content relevance, which is essential for hubs. Each memory's score is content_relevance × link_weight × depth_factor × freshness_factor when query is passed (link_weight × depth_factor × freshness_factor otherwise); content_relevance is normalized lexical relevance or reranker relevance, never body-vector …
read_memoryRead the full content and validity of one stored memory (selected via read_key). Returns the memory and all connected key clusters so exploration can continue Key → Memory → Key. Pass via_key_id from the selected key: the read records access and only that traversed edge is Hebbian-reinforced. Reading does not change content depth or confirm that the content is current.
recallSearch long-term memory for what is already known about the user, project, or topic — call this before your first reply and whenever the topic shifts. Always pass the active namespace when known. Returns {status, query, namespace, keys, memories}: ranked key clusters plus one passive Top-1 memory selected under the top key. The memory includes validity, matched_key, and connected_keys, each with a relevance score (cosine of that key to your query/context, sorted high→low). Before answering, check whether the Top-1 memory supplies every fact the question needs. If a fact is missing, follow an u…
rememberMANDATORY END-OF-TURN GATE: before replying, save every durable fact newly revealed this turn (names, preferences, decisions, corrections, project facts, goals). A durable fact left unsaved is a bug; save silently in the same turn. Save nothing only after consciously confirming that nothing durable appeared. Before writing, recall() the topic in the same namespace and reuse returned canonical concepts or aliases. Use 3-6 diverse ATOMIC concept keys of 1-2 words each, never memory-specific phrases (use 'Nexora' and 'portfolio', not 'Nexora portfolio'); 3+-word keys are flagged in hints.phrase_k…
remember_batchMANDATORY END-OF-TURN GATE: when a turn reveals multiple durable facts, save them silently before replying. A durable fact left unsaved is a bug. Recall each topic first, reuse canonical concept-level keys (ATOMIC, 1-2 words each — never phrases), and register cross-lingual forms together. Each item: {content, keys, key_types?, namespace?, ttl_seconds?, decay_profile?, related_to?}; decay_profile defaults to standard. Returns saved IDs and is more efficient than multiple remember() calls.
Signals
- Stars
- 3
- Forks
- 0
- Open issues
- 0
- Last commit
- Oct 22, 2026 (8 days ago)
- Last release
- Oct 22, 2026 (8 days ago)
From GitHub (fetched Oct 24, 2026).
Details
- Registry name
io.github.donggyun112/keymem- Version
- 0.17.0
- Auth
- No auth
- Packages
- npm keymem
- License
- MIT
- Repository
- github.com/donggyun112/keymem
- First seen
- Oct 24, 2026
- Last checked
- Oct 25, 2026
More from donggyun112
Done for you
Rather not set it up yourself?
Chalk Labs scopes, builds and runs agents for your team: the task audit, the eval harness, the integrations and the weekly ops report. Fixed scope, priced before we start.
See how we build AI agents →Read the case studies
Chalk Labs is a two-founder AI and growth studio. We build AI agents, CRMs and MVPs for Web3 and AI companies, and have shipped 50+ product and token launches.
- launches shipped
- 50+
- launches shipped
- media placements
- 500+
- media placements
- founders on every account
- 2
- founders on every account
Press we've placed: Forbes · CoinDesk · Decrypt · Cointelegraph · The Block
Rahil Jain, Co-founder, Chalk Labs. Ex-Goldman Sachs engineer. You talk to the person who builds it.
Get Keymem running in your business
Tell us what you want to automate. A founder replies within one working day with a plan, not a pitch deck.
Cite this page
Keymem MCP server. Agent Mart. https://agentmart.dev/connectors/donggyun112-keymem (last updated 2026-10-25)