Agenten stärken
Die eigene URL des Herausgebers. Kein PlugMCP-Endpunkt.
Host a copy with our keys and logs.
https://ai-know.me/mcpDie Claude-Schaltfläche oben öffnet Claude mit ausgefülltem Namen und ausgefüllter URL. Sie bestätigen dort noch.
claude mcp add --transport http me.ai-know-memory https://ai-know.me/mcpRun in a terminal.
{ "mcpServers": { "me.ai-know-memory": { "command": "npx", "args": [ "-y", "mcp-remote", "https://ai-know.me/mcp" ] } }}claude_desktop_config.json
Remote-URL oder ein Befehl auf Ihrem Rechner? Worin sich die beiden Installationen unterscheiden
Auf PlugMCP ausführen
A new server you create. It is not this listing's official endpoint. Use the publisher install when you want their URL and their credentials.
StartenVom Herausgeber
Chinese-first, brain-inspired long-term memory as an MCP server. Give any MCP client — Claude Desktop / Claude Code / Cursor / Cline / Cherry Studio / Coze — the ability to remember and understand your user across sessions.
Chinese-first brain-inspired memory MCP — hybrid recall, 7-layer user profile, workspace assembly.
MCP-USAGE.mdv0.4.0 · 9 tools / 2 resources / 1 prompt · stdio + Streamable HTTP · MCP protocol 2025-11-25
This repo is a thin bridge: it translates MCP tool calls into REST calls to the Zhiji backend (hosted at ai-know.me). The bridge stores nothing; all memory lives in the Zhiji service you connect to.
Mem0 / Zep / LangMem expose add / search / delete over a vector store. 知己 exposes brain-inspired primitives:
bge-large-zh semantic + time-decay + access-reinforcement + dedup ranking.All Chinese-optimized (trigram tokenizer + bge-large-zh); English is supported too. Memory is stored in the Zhiji backend you connect to — self-host it, or use the hosted ai-know.me service; either way it's your Zhiji instance, not a generic memory-SaaS middleman.
9 tools, grouped by role. Every user-scoped tool takes userEmail (or falls back to MB_USER_EMAIL); only the notable extra params are listed.
2 resources — zhiji://schema/dimensions (authoritative 7-layer / 37-dim profile schema) · zhiji://server/status (live service status).
1 prompt — personal-context: weaves profile + memories + facts into a ready-to-prepend system prompt for a given query.
Experimental capabilities (sleep consolidation / dream replay / emergence) are not exposed until their groundedness passes ablation.
zhiji_status → verify connectivity
zhiji_memory_ingest → feed a conversation (or zhiji_ingest_file for audio/docs)
zhiji_workspace_assemble → in a *new* session, recall + understand the user
zhiji_feedback → thumbs up/down, closing the self-evolution loop
You need an agent Key (mb- prefix). Get one at https://ai-know.me/memory?tab=api (register + create a Key bound to your account).
Point any Streamable-HTTP MCP client at the hosted endpoint — you don't need this repo at all:
claude mcp add zhiji-memory --transport http \
--url https://ai-know.me/mcp \
--header "Authorization: Bearer mb-yourKey"
Or in a URL-style client config (Cursor / Cherry Studio / LobeChat):
{
"mcpServers": {
"zhiji-memory": {
"url": "https://ai-know.me/mcp",
"headers": { "Authorization": "Bearer mb-yourKey" }
}
}
}
Use this repo when you want the bridge as a local stdio process (e.g. a desktop client launches it for you), talking to the hosted Zhiji backend:
npm install # only @modelcontextprotocol/sdk + zod
Then in your client config:
{
"mcpServers": {
"zhiji-memory": {
"command": "node",
"args": ["/absolute/path/to/zhiji-mcp/zhiji-mcp-server.mjs"],
"env": {
"MB_BASE_URL": "https://ai-know.me",
"MB_API_KEY": "mb-yourKey"
}
}
}
}
# visual debugger — should list 9 tools / 2 resources / 1 prompt
npx @modelcontextprotocol/inspector node zhiji-mcp-server.mjs
Full client matrix (LangChain, OpenAI Agents SDK, Coze…) is in MCP-USAGE.md.
MCP client ──stdio / HTTP(JSON-RPC)──► zhiji-mcp-*.mjs ──REST──► Zhiji backend (ai-know.me)
The MCP layer stores nothing; it translates MCP tool calls into REST calls to the Zhiji backend. Shared core zhiji-mcp-core.mjs backs both entry points:
userEmail. The bridge treats userEmail as a namespace, not a credential.Bearer mb-… get 401; the backend binds each Key to its userEmail and rejects cross-user access.MCP-USAGE.md §8.MCP-USAGE.md — full guide (install, all clients, per-tool reference, troubleshooting, FAQ)MIT © 2026 知己 AI (ai-know.me)
知己 AI · MCP integration — Chinese-first brain-inspired memory. The bridge is open; the memory intelligence lives in the Zhiji backend.
Chinese-first brain-inspired memory MCP — hybrid recall, 7-layer user profile, workspace assembly.
{ "mcpServers": { "me.ai-know-memory": { "url": "https://ai-know.me/mcp", "headers": {} } }}Tools
Noch keine Tool-Liste. Remote-Server erhalten eine nach dem ersten Health-Check.
FAQ
Kopieren Sie auf dieser Seite die http-Konfiguration für Cursor, Claude Desktop, Claude Code oder VS Code. Sie nutzt die Installation des Herausgebers, keinen PlugMCP-Proxy.
In diesem Eintrag ist keine erforderliche Umgebungsvariable aufgeführt.
Memory wird über HTTP erreicht.
Zuletzt geprüft: 2026-11-10. Chinese-first brain-inspired memory MCP — hybrid recall, 7-layer user profile, workspace assembly.