LoreDocs v0.1.16

Your AI project's knowledge base. Organized, searchable, version-tracked.

LoreDocs gives Claude persistent access to your project documentation -- specs, guides, architecture decisions, reference docs -- so it never loses context between sessions. Works with Claude Code, Cursor, OpenAI Codex, and Hermes Agent.

Available on the Anthropic Marketplace. Install directly from Claude, or via PyPI: uvx loredocs

Quick Start

Prerequisites: uv (fast Python package manager).

# Install uv (one time)
curl -LsSf https://astral.sh/uv/install.sh | sh

# Clone and install
cd /path/to/loredocs
uv sync

For detailed installation instructions, see INSTALL.md.

Using LoreDocs

Claude Code (Terminal)

claude --plugin-dir /path/to/loredocs

Or inside an existing session:

/plugin add /path/to/loredocs

Once loaded, Claude has access to all 46 LoreDocs MCP tools automatically. Ask Claude to "create a vault for this project" or "find the architecture doc" and it uses the tools on its own.

Cowork (Desktop App)

1. Click + next to the prompt box
2. Select Plugins > Add plugin
3. Browse to the loredocs source folder

Shared Database Access: Cowork runs in a sandboxed VM. To access docs saved from Claude Code, ask Claude:

"Mount my ~/.loredocs folder"

How It Works

LoreDocs organizes knowledge into vaults -- named containers for related documents. Each vault can hold specs, guides, decisions, checklists, or any text you want Claude to remember.

~/.loredocs/loredocs.db          <-- SQLite database (metadata, search index)
~/.loredocs/vaults/<vault-id>/   <-- Document files on disk

Key concepts:

• Vaults group related docs by project or topic
• Documents are text files with metadata (tags, categories, priority, notes)
• Version history tracks every change to every document
• Full-text search via SQLite FTS5 finds anything instantly
• Injection loads vault content into Claude's context on demand

Your Data is Always Available

LoreDocs works through MCP tools when they are available and falls back to bundled scripts automatically when they are not. Your vault documents are safe regardless of MCP status -- the same add, search, and retrieve operations work either way. You do not need to configure anything; the plugin skill handles the switch silently.

Verify Installation

After installing, verify LoreDocs is working by asking Claude:

"Run vault_list and show me the results."

If you see a list of vaults (or an empty list if this is your first time), LoreDocs is connected. If you get an error about missing tools, re-run uv sync and reload the plugin.

Recommended CLAUDE.md Setup

For the best experience, add the following snippet to your ~/.claude/CLAUDE.md (global) or your project's CLAUDE.md. This tells Claude how to use LoreDocs consistently across sessions.

## LoreDocs (persistent project knowledge)

At session start:
1. Call `vault_list` to see available knowledge vaults.
2. Call `vault_inject_summary` for any vaults relevant to the current project.
3. Use this context to understand project architecture, decisions, and reference docs.

During the session:
- If you create significant documentation, add it to LoreDocs with `vault_add_doc`.
- Tag documents for easy cross-vault discovery with `vault_tag_doc`.

At session end:
- If new docs were created or updated, ensure they are stored in LoreDocs for future sessions.

For Cowork users: Cowork does not run hooks automatically. Add instructions to call vault_list and vault_inject_summary at session start in your project CLAUDE.md.

Canonical Project Knowledge

In multi-agent environments, different tools and agents often create improvised mirrors of shared skill or configuration content -- playbooks, style guides, shared reference docs. Those mirrors drift. One agent updates the source; the other keeps reading the stale copy. Two agents in the same project end up operating from divergent knowledge with no visible signal that anything is wrong.

LoreDocs prevents this by making the vault the single canonical source that every agent reads. Instead of each agent loading a local file copy, every agent calls vault_inject_by_tag at session start and gets the same vault-managed version.

Recommended pattern

Store shared content (playbooks, team guidelines, shared specs) as vault documents rather than as local files that agents copy or mirror.

Agents load the content at session start:

vault_inject_by_tag: team-playbook

All agents -- regardless of surface (Claude Code, Cowork, CLI, or any future AI tool) -- call the same vault and receive the same current version. Updating the content requires editing the vault document once; all agents pick up the change on their next session start.

Local files (.claude/skills/, .agents/, or any surface-specific config) become pointers or bootstrap stubs only -- not the authoritative content. The vault is the source of truth.

Example: sharing a playbook across an agent team

# Session start for any agent on the team:
# 1. Inject the shared playbook by tag
vault_inject_by_tag("team-playbook")

# 2. Inject any project-specific reference docs
vault_inject_by_tag("project-architecture")

# Working context is now current -- no local file copies needed.

To store the shared content in the vault (one time, or on each update):

# Store (or update) the shared playbook:
vault_update_doc(vault="team-knowledge", doc_id="playbook-id", content=open("PLAYBOOK.md").read())

# Or add it fresh (path= reads directly from disk -- no need to load into context):
vault_add_doc(vault="team-knowledge", name="Team Playbook", path="/absolute/path/to/PLAYBOOK.md", tags=["team-playbook"])

Any agent that calls vault_inject_by_tag("team-playbook") reads the same document. No copies, no mirrors, no drift.

Plans: Free vs Pro

LoreDocs is local-first and free to use. Pro ($9/mo) removes the storage limits and unlocks semantic (meaning-based) retrieval. Everything runs on your machine on either plan -- Pro does not add any cloud component.

Free tier limits are enforced before writes; Pro removes them. Check your current tier and usage anytime with vault_tier_status. Activate a Pro license with vault_set_tier.

The Pro semantic features use a local embedding model (BGE-small-en-v1.5) and the LanceDB index -- still no data leaves your machine.

Features

• Vault organization: Group docs by project with linked project metadata
• Document versioning: Full history with rollback to any prior version
• Tagging and categorization: Tag docs for cross-vault discovery
• Priority levels: Mark docs as critical, high, normal, or low priority
• Full-text search: Fast keyword search across all vaults and documents
• Context injection: Load specific docs, tags, or vault summaries into Claude's context
• Bulk operations: Import directories, bulk-tag, export manifests
• Document linking: Connect related docs across vaults
• Embedding-based document relationships (Pro): vault_find_related returns both keyword co-occurrence and embedding-based auto-links for Pro users. Uses BGE-small-en-v1.5, cosine >= 0.75, same-vault scoped. Embedding links are archived if you downgrade from Pro to Free.
• Cross-product session linking (Pro): Automatically links vault documents to the most relevant LoreConvo sessions, and vice versa. Three tools: vault_link_session, vault_get_session_links, vault_get_linked_sessions. Requires both LoreDocs Pro and LoreConvo Pro.
• Tier management: Free/Pro tiers with configurable limits
• Local-first: SQLite database, no cloud dependency, zero API costs

MCP Tools

LoreDocs provides 46 MCP tools by default (47 with LOREDOCS_ENABLE_CAP_TOOLS=1) organized by function:

Vault Management (8 tools)

Document Operations (10 tools)

Search and Discovery (5 tools)

Organization (5 tools)

Context Injection (9 tools)

Import/Export (3 tools)

Document Links (2 tools)

Administration (3 tools)

Cross-product Session Links (3 tools, Pro)

Portable Project Workspace

LoreDocs and LoreConvo together form a portable project workspace for all of Claude -- session memory AND structured knowledge, entirely on your machine.

• LoreConvo remembers what you discussed, decided, and left open (episodic + semantic memory)
• LoreDocs stores the reference docs, specs, and guides Claude needs (durable knowledge)

Where cloud AI workspaces tie you to one ecosystem, LoreConvo + LoreDocs works across Claude Code, Cursor, OpenAI Codex, Hermes Agent, and Cowork. Both store data locally in SQLite. Neither sends anything to an external server.

Requirements

• Python 3.10+
• macOS or Linux
• uv package manager
• mcp and pydantic (auto-installed by uv sync)

Data and Privacy

LoreDocs is local-first. All data lives in ~/.loredocs/ on your machine.

• Data collected: Document names, content, tags, categories, and vault names you provide when storing documents. No telemetry, usage analytics, or identifiers are collected automatically.
• Storage: SQLite database at ~/.loredocs/loredocs.db; document files in ~/.loredocs/vaults/. No cloud storage. Override the root directory with the LOREDOCS_ROOT environment variable.
• Third-party sharing: None. Data never leaves your machine.
• Retention: Data is retained until you delete it via vault_remove_doc, vault_delete, or remove the database files manually. No automatic expiry.
• Contact: info@labyrinthanalyticsconsulting.com

Full privacy policy: https://labyrinthanalyticsconsulting.com/privacy

Troubleshooting

MCP tools not showing up in Claude Code? Make sure you ran uv sync first. The virtual environment must exist with dependencies installed.

"No module named 'mcp'" error? The .mcp.json points to the virtual environment's Python. If you moved the folder, re-run uv sync.

Cowork can't see docs saved in Code? Ask Claude to "mount my ~/.loredocs folder" so Cowork can access the shared database.

Fallback Script (Direct DB Access)

If the MCP server is unreachable (e.g., in scheduled tasks or automation scripts), scripts/query_loredocs.py provides the same core operations directly against the SQLite database.

# List all vaults
python scripts/query_loredocs.py --list

# Show vault details and document manifest
python scripts/query_loredocs.py --info "My Project Docs"

# Search documents across all vaults
python scripts/query_loredocs.py --search "architecture"

# Add a document to a vault
python scripts/query_loredocs.py --add-doc \
    --vault "My Project Docs" \
    --name "Architecture Overview" \
    --file docs/architecture.md \
    --tags '["architecture", "design"]'

# Add a document from stdin
echo "# Quick Note" | python scripts/query_loredocs.py --add-doc \
    --vault "My Project Docs" \
    --name "Quick Note" \
    --stdin

The script auto-discovers the database at ~/.loredocs/loredocs.db (or pass --db-path explicitly). It writes the same schema as the MCP tools, including FTS indexing and on-disk file storage.

What's New

v0.1.16 (2026-07-26)

Installs and updates now work the way you would expect

LoreDocs used to run from a Python virtual environment created in the source tree, or from uvx loredocs@latest. Neither pinned what actually ran: @latest resolves against a cache that can be stale, so a server could keep running an old version indefinitely, and the venv's interpreter is a symlink to a system Python that breaks if that Python is upgraded or removed.

The plugin now ships a configuration pinned to an exact version, and the server runs through uvx with its own managed Python. Installing or updating the plugin is what changes your version, and nothing else does. There is no virtual environment to create, break, or repair.

Leftover packages from an older pip install are harmless and can be ignored.

Fixed: semantic search and index rebuild were broken for Pro users

vault_search with semantic=true and vault_rebuild_index both failed outright for anyone on Pro, returning an internal error instead of results. This affected every Pro user of those two tools and had been present since v0.1.4. Both work now.

If you are on Pro and semantic search has never returned anything useful, this is why. Run vault_rebuild_index once after upgrading (see below) and it will start working.

Fixed: diagnostics no longer hide the reason for a failure

get_server_info and the loredocs-compat-check command reported that something was wrong without saying what: the underlying error text was being discarded. It is now included in the output. A missing packaging dependency was also causing the compatibility check to disable itself silently; that dependency is now declared, so the check runs and reports a real version.

One install, every tier: semantic search now works out of the box

Semantic search used to be a separate install step. It needed the [pro] extra, which pulled in PyTorch: a large download, a second environment to keep up to date, and a common source of "why isn't semantic search working?"

Semantic search now ships in the standard install. The same embedding model as before (BAAI/bge-small-en-v1.5) runs on ONNX Runtime instead of PyTorch, which is roughly a third of the download size. There is one install path and one environment for everyone. Pro is now purely a license flag: nothing extra to install to unlock it.

pip install loredocs[pro] still works and is now equivalent to a plain install, so existing scripts do not break.

Recommended one-time step: run vault_rebuild_index after upgrading. The new runtime produces very slightly different vectors than the old one, so an index built before this release will gradually drift out of step with documents added afterwards. Rebuilding brings everything back onto the same footing. Keyword search is unaffected and needs nothing.

The first semantic search after upgrading downloads the model (about 90MB) and may take a minute. After that it is cached.

Updated: MCP SDK

The bundled MCP SDK moves to 1.28.1, which carries fixes for three advisories in the versions LoreDocs previously pinned (CVE-2026-52870, CVE-2026-52869, CVE-2026-59950). None of them could affect LoreDocs: all three concern network transports and a multi-client task feature that LoreDocs does not use, since it runs over stdio as a single-client local server. The update means a security scan of your install comes back clean.

See the full changelog for the complete release history.

License

Business Source License 1.1 (BSL 1.1) - Labyrinth Analytics Consulting

Free for personal/non-commercial use (up to 3 vaults). Commercial use requires a paid license. Converts to Apache 2.0 on 2030-03-31. See LICENSE for details.