lore-knowledge-mcp 0.5.0

Unified knowledge management MCP server with document intelligence and research workflows

Lore

The operational knowledge layer for engineers and their AI agents.

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The Problem

Your agents are capable. But every session, they start from zero — no knowledge of your infrastructure, no memory of what broke last month, no idea why you made that architecture call.

You re-explain. They re-discover. Context vanishes when the session ends.

Lore fixes that.

Without Lore:                    With Lore:
─────────────────                ──────────────────────────────────
Agent session starts             Agent queries Lore on startup
"How does our infra work?"       Gets: topology, gotchas, runbooks,
You re-explain everything        recent incidents, verified decisions
Session ends, context lost       Knowledge persists across all sessions
                                 Next agent starts informed

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What Lore Does

Knowledge Base

Structured operational knowledge your agents query in real time.

# Capture a hard-won gotcha
kb_add(topic="proxmox", title="LXC resolv.conf inherits from host — breaks without Tailscale",
       content="...", author="david", source_type="human")

# Agent queries before touching anything
kb_search(query="proxmox lxc dns")  # returns the gotcha instantly

Investigations

Structured debugging with a traceable paper trail from symptom to resolution.

investigation_add(topic="anki-media", title="Media not loading after container restart",
                  content="Hypothesis: mount collision between container volumes...")

investigation_log_experiment(title="Mount collision test", hypothesis="...",
                              results={"collision": True}, conclusion="Confirmed. Remove duplicate mount.")

Six months later, a different engineer hits the same issue. The trail is there.

Journal

Permanent record of milestones, architecture decisions, and buying decisions.

journal_append(entry_type="milestone",
               content="Migrated monitoring stack to ops bastion. Rationale: centralized visibility.",
               tags=["monitoring", "migration"])

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Attribution

In a multi-agent system, provenance matters. Every Lore entry carries author, source_type, and verified.

kb_search("proxmox lxc networking")

Results:
  [1] "LXC resolv.conf inherits from host — Tailscale breaks containers"
      author: david | source_type: human | verified: true

  [2] "LXC container DNS fix after Tailscale install"
      author: engineer-agent | source_type: agent | verified: null

  [3] "LXC DNS configuration reference"
      author: research-agent | source_type: agent | verified: false

Agents know: result 1 is production-safe. Result 2, spot-check first. Result 3, review before acting.

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Quick Start

Solo (SQLite — no server needed)

pip install lore-mcp
export DB_BACKEND=sqlite KNOWLEDGE_DATA_DIR=~/.lore
lore-mcp

Add to Claude Code (~/.claude.json or project .mcp.json):

{
  "mcpServers": {
    "lore": {
      "command": "lore-mcp",
      "env": {
        "DB_BACKEND": "sqlite",
        "KNOWLEDGE_DATA_DIR": "/home/yourname/.lore"
      }
    }
  }
}

Team (PostgreSQL)

pip install lore-mcp
export DB_BACKEND=local DB_HOST=localhost DB_PORT=5432 \
       DB_NAME=lore DB_USER=lore_user DB_PASSWORD=yourpassword
lore-mcp --host 0.0.0.0 --port 5555

All agents on your team point at http://your-server:5555/mcp. One shared knowledge layer.

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Tool Reference

Knowledge Base

Tool	What it does
kb_add	Add an entry. Accepts author, source_type for attribution.
kb_search	Semantic search with optional topic filter.
kb_get	Fetch full entry by ID.
kb_list	List entries, filter by topic.
kb_update	Update content, tags, or set verified flag.
kb_delete	Delete entry (requires confirm=true).

Investigations

Tool	What it does
investigation_add	Open or add to an investigation (topic, title, content, tags).
investigation_list	List investigations, filter by topic.
investigation_get	Fetch full investigation by ID.
investigation_log_experiment	Log a structured experiment with hypothesis, methodology, results, conclusion.
investigation_list_experiments	List all logged experiments.

Journal

Tool	What it does
journal_append	Add a milestone, decision, or reflection.
journal_list	List recent entries (default 20).
journal_get	Fetch entry by ID.
snapshot_config	Snapshot a config object to the journal.

Document Ingestion

Tool	What it does
kb_ingest_doc	Ingest a markdown file into the KB.
kb_ingest_dir	Batch-ingest a directory, with change detection.
kb_sync_status	Check what's changed since last sync.

MCP Index

Tool	What it does
mcp_index_scan	Scan all configured MCP servers and index their tools.
mcp_index_search	Search indexed tools by description.
mcp_index_get_server	Get all tools for a specific MCP server.
mcp_index_rebuild	Force a full rescan.

Search

Tool	What it does
multi_search	Search across KB, investigations, journal, and transcripts at once.
search_local	Search local files by content.
search_transcripts	Search Whisper transcript segments.
deduplicate_results	Deduplicate a result set by similarity.
cluster_results	Cluster results by topic.

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Backends

Backend	Use case	Setup
SQLite	Solo / local dev / single machine	No server, one env var
PostgreSQL	Team / shared / production	Self-hosted DB
Supabase	Cloud PostgreSQL	Managed, zero-ops

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How It's Different

Tool	Built for	What it remembers	Agent-native
OB1 / personal memory	One person	Your thoughts and captures	No
Mem0 / Zep	App developers	User preferences, conversations	Partially
Confluence / Notion	Human teams	Documentation (human-browsed)	No
Lore	Engineering teams + AI agents	How your systems work	Yes

Lore is not a second brain. It's the operational intelligence layer your agents need to work in your environment — not just any environment.