Agenten stärken
Der eigene Befehl des Herausgebers. Kein PlugMCP-Endpunkt.
Host a copy with our keys and logs.
uvx lore-sdk==1.4.2Claude Code hat keinen Installationslink für einen lokalen Befehl. Kopieren Sie den Befehl unten und führen Sie ihn in einem Terminal aus.
claude mcp add io.github.agentkitai-lore -- uvx lore-sdk==1.4.2In einem Terminal ausführen.
{ "mcpServers": { "io.github.agentkitai-lore": { "command": "uvx", "args": [ "lore-sdk==1.4.2" ] } }}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.
StartenYour AI agents remember everything. Automatically.
Lore is a cross-agent memory system that stores, connects, and retrieves knowledge across any AI agent — without code changes. Install a hook, and relevant memories appear in every prompt. No agent cooperation needed.
User: "What API rate limits should I use?"
── Lore hook fires (20ms) ──────────────────────────────
🧠 Relevant memories from Lore:
- [0.82] Stripe API returns 429 after 100 req/min — use exponential backoff
- [0.71] Our internal API rate limit is 500 req/min per API key
────────────────────────────────────────────────────────
Agent sees memories + prompt → responds with full context
remember · recall · forget · list_memories · stats
Store and retrieve memories across any AI agent via MCP tools, REST API, or Python/TypeScript SDK. Semantic search with tier-based TTL, temporal decay, and automatic PII redaction.
graph_query · entity_map · related · extract_facts · list_facts · conflicts
Entities and relationships auto-extracted from memories. Hop-by-hop graph traversal surfaces connected knowledge that pure vector search misses. Atomic fact extraction with automatic conflict detection.
supersede · list_at_time · facts_at_time · timeline · provenance · supersession_chain · consolidate_memories
History without deletion. Memories and facts are corrected by superseding them, never deleting — every change appends to an auditable trail. Lore tracks two independent time axes (bi-temporal): valid-time (when a fact was true in the world) and system-time (when Lore learned it), so you can ask "what was canonical — or true about X — as of date Y?". list_at_time / facts_at_time answer as-of queries, timeline walks chronologically adjacent events, and provenance / supersession_chain expose the full correction lineage for a memory or fact.
Web UI at /ui/
Interactive D3 force-directed graph of your knowledge base. Entity detail panels, topic clusters, search, and filtering. Runs in the browser — no install required.
Auto-snapshot + auto-inject — zero agent cooperation
The Session Accumulator automatically captures conversation context and injects relevant session history into every prompt. Deterministic (no LLM needed). Works via hooks — the agent never knows Lore exists.
recent_activity
Session-aware summary of what happened recently across all projects. Gives agents continuity between conversations without manual context-passing.
topics · topic_detail
Auto-generated concept hubs that cluster related memories, entities, and facts around recurring themes. See everything Lore knows about a topic in one view.
export · snapshot · snapshot_list · save_snapshot
Full data export in JSON and Markdown formats. Obsidian-compatible output for browsing your knowledge graph in a PKM tool. Snapshots for backup and migration.
review_digest · review_connection · lore review list --sort risk
Review discovered knowledge graph connections with computed risk scores. Batch approve/reject with notes, full audit trail of decisions. Sort by risk, confidence, or age.
lore bootstrap
Single command that validates Python version, Postgres, pgvector, Docker, runs migrations, and verifies server health. Use --fix to auto-remediate missing dependencies.
lore setup claude-code · lore setup openclaw · lore setup cursor · lore setup codex
One-command hook installation for all major AI coding agents. Auto-retrieval injected into every prompt — no code changes needed. Includes --validate, --test-connection, and --dry-run flags.
lore slo create · lore slo status · GET /v1/slo/status
Define SLO targets for retrieval latency (p50/p95/p99) and hit rate. Background checker evaluates every 60s and fires webhook or email alerts on breach. Time-series API for charting.
lore profiles list · GET /v1/profiles · ?profile=coding
Named retrieval profiles stored in Postgres. Presets for coding (recency-biased), incident response (graph-heavy), and research (long-term). Select per-request or set as API key default.
lore policy create · lore restore-drill · GET /v1/policies/compliance
Declarative lifecycle policies with per-tier retention windows, cron-based snapshot schedules, and restore drills with timing metrics. Compliance dashboard across all policies.
lore workspace create · lore workspace switch · lore audit
Workspace isolation within orgs. Scoped API keys, member management with RBAC roles, and a full audit log of every action (memory.create, key.revoke, etc.).
lore plugin create · lore plugin list · lore plugin reload
Extend Lore with plugins discovered via Python entry_points. Five lifecycle hooks (on_remember, on_recall, on_enrich, on_extract, on_score), hot-reload, scaffold CLI, and test harness.
suggest · lore suggest --context "..." · GET /v1/recommendations
Surface relevant memories before explicit queries. Multi-signal scoring (context similarity, entity overlap, temporal patterns, access patterns) with human-readable explanations and a feedback loop.
GET /v1/analytics/retrieval · Prometheus metrics
Track hit rate, score distribution, memory utilization, and latency. Know whether memories are actually helping your agents.
git clone https://github.com/agentkitai/lore.git
cd lore
docker compose up -d
Starts Postgres with pgvector and the Lore server on http://localhost:8765.
pip install "lore-sdk[server,solo]"
lore serve # starts on port 8765
curl http://localhost:8765/v1/memories
One line — no install — drops Lore into any MCP client (Claude Code, Cursor, VS Code, Codex, Claude Desktop):
// Claude Code: .mcp.json · Claude Desktop: claude_desktop_config.json
{
"mcpServers": {
"lore": { "command": "uvx", "args": ["--from", "lore-sdk[mcp]", "lore-memory"] }
}
}
Already installed (pip install lore-sdk[mcp])? Use "command": "lore-memory" (or lore mcp). Per-client guides are in Multi-Agent Setup below; lore integrate --platform <client> writes the config for you.
Option A: Auto-retrieval hook (recommended)
lore setup claude-code
This installs a UserPromptSubmit hook that auto-injects relevant memories into every prompt.
Option B: MCP tools
Add to ~/.claude/settings.json:
{
"mcpServers": {
"lore": {
"command": "lore",
"args": ["mcp"],
"env": {
"LORE_API_URL": "http://localhost:8765",
"LORE_API_KEY": "your-api-key"
}
}
}
}
lore setup openclaw
Installs a message:preprocessed hook for auto-retrieval. Memories appear in context before every agent response.
lore setup cursor
Installs a beforeSubmitPrompt hook. Also add MCP config to .cursorrules:
{
"mcpServers": {
"lore": {
"command": "lore",
"args": ["mcp"],
"env": {
"LORE_API_URL": "http://localhost:8765",
"LORE_API_KEY": "your-api-key"
}
}
}
}
lore setup codex
Installs a beforePlan hook. Add MCP config:
{
"mcpServers": {
"lore": {
"command": "lore",
"args": ["mcp"],
"env": {
"LORE_API_URL": "http://localhost:8765",
"LORE_API_KEY": "your-api-key"
}
}
}
}
Auto-retrieval works with any system that can make an HTTP call before sending a prompt:
curl -s "http://localhost:8765/v1/retrieve?query=your+prompt&limit=5&min_score=0.3&format=markdown" \
-H "Authorization: Bearer $LORE_API_KEY"
# Memory operations
lore remember "API rate limit is 100 req/min" --tags api,limits
lore recall "rate limits" --limit 5
lore forget <memory-id>
lore memories --tier long_term
lore stats
# Knowledge graph
lore graph "authentication" --depth 2
lore entities --limit 50
lore facts "extract facts from this text"
lore conflicts
# Session & context
lore recent --hours 24
lore on-this-day
# Export & backup
lore export --format json > backup.json
lore import backup.json
lore snapshot-save --title "before refactor"
# Server & setup
lore bootstrap # validate prerequisites
lore serve # start HTTP server
lore mcp # start MCP server
lore ui # start web UI
lore setup claude-code # install hooks
lore setup claude-code --validate --test-connection
# SLO management
lore slo create --name "P99 < 50ms" --metric p99_latency --threshold 50 --operator lt
lore slo status
lore slo alerts
# Retrieval profiles
lore profiles list
lore profiles create --name fast-coding --semantic-weight 1.0 --recency-bias 7
# Retention policies
lore policy create --name prod --snapshot-schedule "0 2 * * *" --max-snapshots 30
lore policy compliance
lore restore-drill --latest
# Workspaces
lore workspace create dev-team
lore workspace switch dev-team
lore audit --since 24h
# Plugins
lore plugin create my-tagger
lore plugin list
lore plugin reload my-tagger
# Recommendations
lore suggest --context "setting up docker"
# Review (with risk scoring)
lore review list --sort risk
lore review approve <id> --note "Verified"
lore review batch approve --ids id1,id2
# API keys
lore keys create --name "my-agent"
lore keys list
lore keys revoke <key-id>
# Memory CRUD
GET /v1/retrieve # Auto-retrieval (for hooks)
POST /v1/memories # Create memory
POST /v1/memories/search # Semantic search
GET /v1/memories # List memories
GET /v1/memories/{id} # Get memory
PATCH /v1/memories/{id} # Update memory
DELETE /v1/memories/{id} # Delete memory
# Knowledge graph
GET /v1/graph # Knowledge graph
GET /v1/graph/topics # Topic list
GET /v1/graph/topics/{name} # Topic detail
GET /v1/graph/entity/{id} # Entity detail
# Bi-temporal & supersession (history without deletion)
POST /v1/memories/{id}/supersede # Mark superseded (by=null un-supersedes)
GET /v1/memories/at_time # Memories canonical as of ?at=<ts>
GET /v1/memories/{id}/supersession-chain # Memory correction audit trail
GET /v1/memories/{id}/provenance # Full lineage (sources + chain)
POST /v1/memories/consolidate # Merge N memories + supersede sources
GET /v1/facts/at_time # Facts about an entity valid at ?at=<ts>
POST /v1/facts/{id}/supersede # Supersede-not-delete a fact edge
GET /v1/facts/{id}/supersession-chain # Fact correction trail
GET /v1/timeline # Chronologically adjacent events
# Ingestion
POST /v1/conversations # Extract memories from conversation
POST /v1/ingest # Ingest external content
# Review + risk scoring
GET /v1/review # Pending reviews (sortable by risk)
POST /v1/review/{id} # Approve/reject with notes
POST /v1/review/bulk # Batch approve/reject
GET /v1/review/history # Decision audit trail
# Export & snapshots
POST /v1/export # Export all data
POST /v1/import # Import data
POST /v1/export/snapshots # Create snapshot
GET /v1/export/snapshots # List snapshots
# SLO dashboard
GET /v1/slo # List SLO definitions
POST /v1/slo # Create SLO
GET /v1/slo/status # Current pass/fail per SLO
GET /v1/slo/alerts # Alert history
GET /v1/slo/timeseries # Time-series for charts
# Retrieval profiles
GET /v1/profiles # List profiles
POST /v1/profiles # Create profile
GET /v1/retrieve?profile=coding # Retrieve with profile
# Retention policies
GET /v1/policies # List policies
POST /v1/policies # Create policy
GET /v1/policies/compliance # Compliance summary
POST /v1/policies/{id}/drill # Execute restore drill
# Workspaces + RBAC
POST /v1/workspaces # Create workspace
GET /v1/workspaces # List workspaces
POST /v1/workspaces/{id}/members # Add member
GET /v1/audit # Query audit log
# Plugins
GET /v1/plugins # List plugins
POST /v1/plugins/{name}/enable # Enable plugin
POST /v1/plugins/{name}/reload # Hot-reload plugin
# Recommendations
POST /v1/recommendations # Get proactive suggestions
POST /v1/recommendations/{id}/feedback # Thumbs up/down
PATCH /v1/recommendations/config # Adjust aggressiveness
# Setup validation
POST /v1/setup/validate # Test connectivity
# Analytics & monitoring
GET /v1/recent # Recent activity
GET /v1/analytics/retrieval # Retrieval analytics
GET /metrics # Prometheus metrics
# API keys
POST /v1/keys # Create API key
GET /v1/keys # List API keys
DELETE /v1/keys/{id} # Revoke API key
┌──────────────────────────────────────────────────────────────┐
│ Agent Runtimes │
│ Claude Code · OpenClaw · Cursor · Codex · Any HTTP client │
└──────────┬──────────────────────────────────┬────────────────┘
│ hooks (auto-retrieval) │ MCP tools
▼ ▼
┌──────────────────────────────────────────────────────────────┐
│ Lore Server (:8765) │
│ │
│ REST API · MCP Server · Web UI (/ui/) · Plugin SDK │
│ │
│ ┌─────────────┐ ┌──────────────┐ ┌─────────────────────┐ │
│ │ Embedder │ │ Knowledge │ │ LLM Pipeline │ │
│ │ (ONNX) │ │ Graph │ │ (optional) │ │
│ │ pgvector │ │ + Review │ │ classify · enrich │ │
│ │ + Profiles │ │ + Risk │ │ extract · recommend │ │
│ └─────────────┘ └──────────────┘ └─────────────────────┘ │
│ │
│ ┌─────────────┐ ┌──────────────┐ ┌─────────────────────┐ │
│ │ SLO │ │ Retention │ │ Workspaces │ │
│ │ Checker │ │ Scheduler │ │ + RBAC │ │
│ │ + Alerting │ │ + Drills │ │ + Audit Log │ │
│ └─────────────┘ └──────────────┘ └─────────────────────┘ │
└──────────────────────────┬───────────────────────────────────┘
│
┌────────────▼────────────┐
│ PostgreSQL + pgvector │
│ memories · entities │
│ relationships · facts │
│ slo · profiles · audit │
│ workspaces · policies │
└─────────────────────────┘
git clone https://github.com/agentkitai/lore.git
cd lore
pip install -e ".[dev,server,mcp,enrichment]"
docker compose up -d db # Postgres + pgvector
pytest
MIT
Cross-agent memory over MCP: hybrid recall, knowledge graph, private/shared visibility, redaction.
{ "mcpServers": { "io.github.agentkitai-lore": { "command": "uvx", "args": [ "lore-sdk==1.4.2" ] } }}Tools
Noch keine Tool-Liste. Remote-Server erhalten eine nach dem ersten Health-Check.
FAQ
Kopieren Sie auf dieser Seite die stdio-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.
Lore läuft lokal über stdio.
Zuletzt geprüft: 2026-11-09. Cross-agent memory over MCP: hybrid recall, knowledge graph, private/shared visibility, redaction.