LoreDocs

Name: LoreDocs
Author: labyrinth-analytics

by labyrinth-analyticsversion 0.1.32i★ –iRuns on your computer

Registry nameio.github.labyrinth-analytics/loredocs

Install

Overview

Description from the maker (original English)

Local-first knowledge vaults for project docs and specs. Tagged, versioned, full-text searchable.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: stdio
Category: Search & AI memory
You need to fill in: LOREDOCS_PRO

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
You fill in yourself: LOREDOCS_PRO

Values marked secret are keys to your account. Never share them or paste them into a chat.

You need

PyPIPython’s uv installed (for the uvx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "loredocs": {
      "command": "uvx",
      "args": [
        "loredocs"
      ],
      "env": {
        "LOREDOCS_PRO": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add loredocs --env LOREDOCS_PRO=your-value -- uvx loredocs

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "loredocs": {
      "command": "uvx",
      "args": [
        "loredocs"
      ],
      "env": {
        "LOREDOCS_PRO": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "loredocs": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "loredocs"
      ],
      "env": {
        "LOREDOCS_PRO": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

Values you fill in

LOREDOCS_PRO secret env
Pro license key. Leave unset for the free tier.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 6, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account labyrinth-analytics, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Search & AI memoryi

More stars than 0% of the other 7246 servers in this category
Published to the registry more recently than 81% of the other 7246 servers in this category
Basic checks equal to or better than 100% of the other 7246 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is LoreDocs safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

You need to fill in: LOREDOCS_PRO

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.1.32) reached the registry 8 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.

What can I use instead?

In the same category: Context7, Codebase Memory, Exa

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Context7

by upstash

Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.

Computer or cloud★ 64,224MITUpdated today

Install

Codebase Memory

by DeusData

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

Runs on your computer★ 48,148MITUpdated 20 days ago

Install

Exa

by exa-labs

Connect AI agents to Exa for web search, content fetching, and multi-step research.

Runs in the cloud★ 5,213MITUpdated last month

Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

LoreDocs v0.1.32

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, Cowork, Cursor, OpenAI Codex, and Hermes Agent.

Install directly from Claude Code's plugin marketplace, or via PyPI: uvx loredocs

Quick Start

Prerequisites: uv (fast Python package manager).

# Install uv: https://docs.astral.sh/uv/getting-started/installation/

Clone and install

cd /path/to/loredocs uv sync

For detailed installation instructions, see INSTALL.md.

Using the Claude Agent SDK directly? git clone the public repo and point the SDK's local-directory plugin loader at it -- the repo root is a self-contained plugin directory (.claude-plugin/plugin.json + .mcp.json). No separate SDK-installable bundle exists or is needed.

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 49 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)

Click + next to the prompt box
Select Plugins > Add plugin
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"

Hermes Agent

For Hermes Agent users, add LoreDocs as an MCP server under mcp_servers: in ~/.hermes/config.yaml (see INSTALL.md for the full entry), then restart Hermes.

All 49 LoreDocs MCP tools are then available in your Hermes sessions.

Hermes Disclosures

When using LoreDocs with Hermes Agent:

Installation: First run downloads the loredocs version you pin from PyPI via uvx. There is no automatic self-update.
Data Storage: All vault data is stored locally at ~/.loredocs/ in SQLite format. No data is sent to cloud services or external servers.
Pro License Validation: Pro tier activation uses offline Ed25519 cryptography to validate your license key. No network request is made during validation.
Telemetry: LoreDocs does not collect or transmit telemetry or usage data.
Network calls: Pro semantic search downloads the BAAI/bge-small-en-v1.5 embedding model from Hugging Face once, on first use. The optional Notion import calls the Notion API with a token you provide. LoreDocs makes no other network calls.

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/ / <-- 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:

Call vault_list to see available knowledge vaults.
Call vault_inject_summary for any vaults relevant to the current project.
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	Pro ($9/mo)
Vaults	3	Unlimited
Documents per vault	50	Unlimited
Storage	500 MB	Unlimited
Version history per document	5 versions	Unlimited
Full-text search (FTS5)	Yes	Yes
Core MCP tools (create, search, version, tag, inject, import/export)	Yes	Yes
Local-first, no cloud, no telemetry	Yes	Yes
Semantic search (`vault_search semantic=true`, `vault_rebuild_index`)	--	Yes
Embedding-based document relationships (`vault_find_related`)	Keyword co-occurrence only	Keyword + embedding auto-links
Cross-product session linking (`vault_link_session` + 2 more)	--	Yes (also requires LoreConvo Pro)

Upgrade to Pro -- $9/month

After checkout, your license key is emailed automatically to the address you used at checkout, usually within a few minutes. Questions: info@labyrinthanalyticsconsulting.com.

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 49 MCP tools by default (50 with the notion extra installed; 51 with LOREDOCS_ENABLE_CAP_TOOLS=1 and the notion extra) organized by function:

Vault Management (8 tools)

Tool	What it does
`vault_create`	Create a new vault with name and description
`vault_list`	List all vaults with doc counts and sizes
`vault_info`	Get detailed vault information
`vault_archive`	Archive a vault (preserves data, hides from listing)
`vault_delete`	Permanently delete a vault and all its documents
`vault_link_project`	Link a vault to a project directory
`vault_open_workspace`	Open or create the vault scoped to a directory path
`loredocs_onboard`	Set up workspace with starter vaults on first install

Document Operations (10 tools)

Tool	What it does
`vault_add_doc`	Add a new document to a vault (inline content or from file path)
`vault_update_doc`	Update document content (creates version history)
`vault_remove_doc`	Remove a document from a vault
`vault_get_doc`	Retrieve a document with full content
`vault_list_docs`	List documents in a vault with filtering and sorting
`vault_copy_doc`	Copy a document to another vault
`vault_move_doc`	Move a document to another vault
`vault_doc_history`	View version history of a document
`vault_doc_restore`	Restore a document to a previous version

Search and Discovery (6 tools)

Tool	What it does
`vault_search`	Full-text search across all vaults
`vault_search_by_tag`	Find documents by tag across all vaults

| vault_find_related | Discover documents related to a given doc (Pro

Only the beginning is shown; read the rest in the repo

LoreDocs

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

Values you fill in

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Search & AI memoryi

Common questions

Alternatives

Context7

Codebase Memory

Exa

README from the maker

LoreDocs v0.1.32

Quick Start

Clone and install

Using LoreDocs

Claude Code (Terminal)

Cowork (Desktop App)

Hermes Agent

Hermes Disclosures

How It Works

Your Data is Always Available

Verify Installation

Recommended CLAUDE.md Setup

Canonical Project Knowledge

Recommended pattern

Example: sharing a playbook across an agent team

1. Inject the shared playbook by tag

2. Inject any project-specific reference docs

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

Or add it fresh (path= reads directly from disk -- no need to load into context):

Plans: Free vs Pro

Features

MCP Tools

Vault Management (8 tools)

Document Operations (10 tools)

Search and Discovery (6 tools)