LoreDocs
Resumen
Descripción del creador (original en inglés)
Local-first knowledge vaults for project docs and specs. Tagged, versioned, full-text searchable.
Los tres pilares de PopNx MCP
Estos tres nunca se combinan en una sola puntuación: las opiniones, las mediciones y la popularidad son cosas distintas.
- Opinión de usuariosiAún no hay reseñasLas reseñas se abrirán junto con las cuentas en una etapa posterior
- Nuestras revisiones básicasi1 de 1 superadasRevisado con información pública; el código aún no se ha escaneado
- UsoiMuy nuevo↓ 216/sem · ★ –
Qué puedes hacer con él
Todavía no escribimos un resumen sencillo para este. Abajo están los datos que leímos del registro.
- Conexión: Se ejecuta en tu computadora
- Transporte: stdio
- Categoría: Búsqueda y memoria de IA
- Debes completar: LOREDOCS_PRO
Instalación
Elige la app de IA que usas y copia la configuración.
Antes de instalar
- Revisiones básicas: 1 de 1 superadas
- Se ejecuta en tu computadora con los permisos de tu usuario (archivos, red, apps).
- Debes completar tú:
LOREDOCS_PRO
Los valores marcados como secretos son llaves de tu cuenta. Nunca los compartas ni los pegues en un chat.
Necesitas
- PyPIuv de Python instalado (para el comando uvx)
¿Qué app usas?
Elige tu app arriba. La recordamos, así que la próxima vez el botón dirá “Instalar en …”.
Abre Claude Desktop → Settings → Developer → Edit Config y pega esto en claude_desktop_config.json
{
"mcpServers": {
"loredocs": {
"command": "uvx",
"args": [
"loredocs"
],
"env": {
"LOREDOCS_PRO": "your-value"
}
}
}
}Ejecuta esto en tu terminal
claude mcp add loredocs --env LOREDOCS_PRO=your-value -- uvx loredocsCompleta los valores vacíos antes de ejecutarlo.
O copia la configuración tú
Pégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"loredocs": {
"command": "uvx",
"args": [
"loredocs"
],
"env": {
"LOREDOCS_PRO": "your-value"
}
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
O copia la configuración tú
Pégalo en .vscode/mcp.json de tu proyecto
{
"servers": {
"loredocs": {
"type": "stdio",
"command": "uvx",
"args": [
"loredocs"
],
"env": {
"LOREDOCS_PRO": "your-value"
}
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Este se ejecuta en tu computadora, y ChatGPT solo puede conectarse a servidores en internet. Elige otra app.
Tu elección se guarda en una cookie en este dispositivo; no necesitas cuenta.
Valores que debes completar
- Pro license key. Leave unset for the free tier.
Esta configuración se genera a partir de la ficha del creador en el registro. Si el README dice otra cosa, sigue el README.
Qué puede hacer
Se ejecuta en tu computadora; la lista de herramientas aparece en tu app de IA después de instalarlo.
Revisiones básicasi
Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 10 nov 2026
- ✓ Superada
El creador coincide con el repo
El nombre en el registro se verificó con la cuenta de GitHub labyrinth-analytics, dueña del repo
- … Aún sin revisar
Sigue en mantenimiento
Todavía no hemos leído este repo en GitHub
- … Aún sin revisar
Tiene licencia
Todavía no hemos leído este repo en GitHub
- – No aplica
El endpoint responde
Este se ejecuta en tu computadora; no hay endpoint en internet
- – No aplica
Inicio de sesión con OAuth
Se ejecuta en tu computadora y usa ajustes locales en su lugar
- … Aún sin revisar
Sin instrucciones ocultas en las descripciones de herramientas
Se ejecuta en tu computadora; solo podemos leer listas de herramientas de endpoints en internet
Comparado con otros en Búsqueda y memoria de IAi
- Más estrellas que el 0% de los otros 5843 servidores de esta categoría
- Publicado en el registro más recientemente que el 91% de los otros 5843 servidores de esta categoría
- Revisiones básicas iguales o mejores que el 100% de los otros 5843 servidores de esta categoría
Comparado con todos los servidores activos de esta categoría en el registro. Las estrellas solo cuentan cuando quien lo publica es dueño del repo.
Preguntas frecuentes
¿Es seguro LoreDocs?
Superó 1 de 1 revisiones básicas aplicables. No hemos leído el código. Antes de agregar una clave o un token, revisa qué acceso pide el servidor y usa una clave que tenga solo los permisos que necesitas.
¿Qué claves o códigos necesita?
Debes completar: LOREDOCS_PRO
¿Se ejecuta en mi computadora o en la nube?
Se ejecuta en tu computadora. Tu app de IA lo inicia cuando hace falta, y los datos no pasan por los servidores del creador (a menos que el propio servidor llame a un servicio en línea).
¿Sigue en mantenimiento?
El repo de GitHub cambió por última vez –, y la última versión (0.1.33) llegó al registro hace 3 días.
¿Qué apps pueden usarlo?
Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas Python (uv) en tu computadora.
¿Qué puedo usar en su lugar?
En la misma categoría: Context7, Codebase Memory, Exa
Alternativas
Servidores de la misma categoría hechos por otros creadores, ordenados por estrellas.
Cómo leer una tarjeta:↓ Descargas por semanai★ Estrellas de GitHubiTres pilares: reseñas · revisiones · usoiActualizado = fecha en que se publicó la última versión en el registroi
Codebase Memory
Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.
Exa
Connect AI agents to Exa for web search, content fetching, and multi-step research.
README del creador
Abrir el README
Copiado tal cual del repo del creador. PopNx MCP no lo ha revisado ni lo respalda. Se quitaron HTML, imágenes y scripts. Los enlaces llevan fuera de este sitio.
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
loredocssource 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
loredocsversion you pin from PyPI viauvx. 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-v1.5embedding 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_listand 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_listto see available knowledge vaults. - Call
vault_inject_summaryfor 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) |
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_relatedreturns 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
Solo se muestra el principio; lee el resto en el repo