Loreto Skills Generator MCP Server
Insérez n'importe quelle vidéo YouTube, article, PDF ou image dans l'API Loreto et recevez des packages de compétences prêts pour la production, complets avec SKILL.md, scripts de test et stubs de référence.
Documentation
loreto-mcp
Turn any YouTube video, article, PDF, or image into a reusable Claude Code skill — without leaving your editor.
What it does
Loreto analyzes a content source and extracts structured skill packages that Claude Code can apply to future tasks. Each skill contains:
SKILL.md— Principles, failure modes, implementation steps, and architectural patternsREADME.md— Overview and usage context- Reference files — Supporting patterns and data structures
- Test script — Runnable validation for the skill's core concepts
Save skills to .claude/skills/ and Claude picks them up automatically on relevant tasks — reducing hallucinations, token usage, and re-explaining the same concepts over and over.
Sample skills
Every skill Loreto generates ships as its own standalone, installable repo. These nine were generated from a single technical video on hybrid AI architecture — clone any of them directly:
| Skill | What it teaches |
|---|---|
designing-hybrid-context-layers | Architect hybrid retrieval systems that combine vector search, graph traversal, and structured data |
temporal-reasoning-sleuth | Enable agents to trace decision chains and reconstruct causal sequences across long time horizons |
synthesizing-institutional-knowledge | Capture and query organizational knowledge in a way AI agents can reliably reason over |
diagnosing-rag-failure-modes | Classify the four structural RAG failure patterns and prescribe the right fix |
routing-work-across-ai-harnesses | Dynamically route tasks to the right AI harness based on task type and context |
evaluating-ai-harness-dimensions | Score and compare AI harness options across the five structural dimensions |
detecting-harness-lockin | Spot vendor lock-in signals early and price the switching cost |
benchmarking-ai-agents-beyond-models | Measure agent performance at the system level, not just model level |
auditing-intelligence-context-fit | Audit whether the model's reasoning tier matches the context complexity |
Each repo has a human-facing README plus the skill itself in a same-named subfolder — cp -r <repo>/<skill> ~/.claude/skills/ and Claude picks it up automatically.
Anatomy of a generated skill
You don't have to clone anything to see what Loreto produces. Every generation
is a ready-to-run package — a SKILL.md (principles, failure modes,
implementation steps, Mermaid diagrams), supporting references/, and a
runnable tests/ script. The standalone repos wrap each one with a human
README and the skill in a same-named subfolder:
designing-hybrid-context-layers/ ← public repo
├── README.md ← for humans, not part of the skill
└── designing-hybrid-context-layers/ ← the skill (cp into ~/.claude/skills/)
├── SKILL.md
└── references/
├── architecture-patterns.md
└── retrieval-decision-matrix.md
A trimmed look at the SKILL.md Loreto generated for that skill:
---
name: designing-hybrid-context-layers
description: >
Designs hybrid AI context architectures that combine RAG, knowledge graphs,
episodic memory, and long-context synthesis appropriately. Use when ...
---
# Designing Hybrid Context Layers
## The Three-Layer Context Model
### Layer 1: Factual Store (Vector RAG)
### Layer 2: Relational Store (Knowledge Graph)
### Layer 3: Temporal/Episodic Store (Timeline Index)
```mermaid
flowchart TD
Q[Incoming Query] --> R{Query Router}
R -->|single fact| L1[Layer 1 — Vector RAG]
R -->|relationships| L2[Layer 2 — Knowledge Graph]
R -->|sequence / causation| L3[Layer 3 — Timeline Index]
```
## Anti-Pattern: The RAG-for-Everything Trap
## Implementation Roadmap
Prefer not to leave your editor at all? The free list_skills and get_skill
MCP tools return the same structured records, and verify_artifacts proves any
past generation by generation_id — discover, inspect, and verify before you
ever clone.
Billing — two paths, pick one
Loreto runs on two parallel billing paths. The right one depends on whether you're a human signing up or an AI agent paying per task.
API key (lor_...) | x402 pay-per-call (USDC) | |
|---|---|---|
| Best for | Humans, recurring use, teams | Agents, one-off jobs, anonymous use |
| Signup | Yes — loreto.io | None |
| Pricing | Free: 2 calls/mo · Pro: $29/mo for 100 | Flat $0.75 per call, no monthly cap |
| Wallet needed | No | Yes — USDC on Base mainnet |
| MCP support | This package, out of the box | Direct REST + the x402 Python SDK |
| Endpoint | POST /api/v1/skills/generate | POST /api/v1/skills/x402/generate |
| Docs | docs-authentication | docs-x402 |
Path A — API key (this MCP package)
Get your key at loreto.io, set LORETO_API_KEY in your MCP config (see below), and you're done. Free tier ships immediately; upgrade to Pro when you need more.
Path B — x402 pay-per-call (no signup)
If you're an autonomous agent, an AI workflow without persistent credentials, or a developer who just wants to try one generation, x402 is faster than signing up. The MCP package itself uses Path A — but every catalog call (list_skills, get_skill, verify_artifacts, estimate_cost) is free regardless of which path you generate skills under.
To run a generation under x402:
# Pseudocode — see https://loreto.io/docs-x402 for the full handshake
curl -X POST https://api.loreto.io/api/v1/skills/x402/generate \
-H "X-PAYMENT: <eip-3009 signed authorization>" \
-H "Content-Type: application/json" \
-d '{"source": "https://www.youtube.com/watch?v=...", "source_type": "youtube"}'
The X-PAYMENT header is signed by your wallet against an EIP-3009 USDC transfer authorization for $0.75. The Loreto server only burns the authorization on a successful 2xx response — failed pipeline runs don't consume your USDC. Use the x402 Python SDK to handle the signing.
Verify any generation by id. Both paths return a generation_id (uuid4). Pass it to the MCP's verify_artifacts tool — or hit GET /api/v1/skills/manifest/{generation_id} directly — to fetch the source URL, theme plan, quality scores, artifact byte counts, and bundle sha256. The endpoint is public, no auth required: the id is the capability.
Setup
1. Get an API key (Path A)
Sign up at loreto.io. Skip this step if you're using x402 — see the billing section above.
2. Install
pip install loreto-mcp
Or run directly without installing (requires uv):
uvx loreto-mcp
3. Configure Claude Code
User-scoped (works across all your projects) — add to ~/.claude/mcp.json:
{
"mcpServers": {
"loreto": {
"command": "uvx",
"args": ["loreto-mcp"],
"env": {
"LORETO_API_KEY": "lor_..."
}
}
}
}
Project-scoped (shared with your team) — add to .mcp.json at your project root:
{
"mcpServers": {
"loreto": {
"command": "uvx",
"args": ["loreto-mcp"],
"env": {
"LORETO_API_KEY": "${LORETO_API_KEY}"
}
}
}
}
4. Verify
Restart Claude Code and run /mcp — you should see loreto listed with seventeen tools. Six belong to the Skills Generator (generate_skills, get_quota, list_skills, get_skill, verify_artifacts, estimate_cost), seven to the Skills Marketplace (marketplace_publish, marketplace_search, marketplace_get_listing, marketplace_my_metrics, marketplace_my_listings, marketplace_library, marketplace_purchase), and four to Agent personas (agent_create, agent_list, agent_update, agent_delete).
Usage
Once connected, just ask Claude Code naturally:
Use Loreto to extract skills from https://www.youtube.com/watch?v=JYcidOS9ozU
Extract skills from this article and save them to .claude/skills/
Check my Loreto quota before we start.
Claude calls generate_skills, receives the full skill package, and can write the files directly to your project.
Available tools
| Tool | Auth | Description |
|---|---|---|
generate_skills | API key | Extract ranked skill packages from a URL. Returns full file contents ready to save. For x402 pay-per-call generations, see the billing section above. |
get_quota | API key | Check calls used, monthly limit, and plan for your API key. (Not relevant on x402 — there is no quota; you pay $0.75 per call.) |
list_skills | None | List all published Loreto catalog skills with their structured artifact and safety claims. Free for everyone. |
get_skill | None | Fetch the full structured record for one catalog skill — artifacts, mcp, safety, governance, references, FAQ. Free for everyone. |
verify_artifacts | None | Fetch the provenance manifest for a past generation by generation_id — works for both API-key and x402 generations. Free for everyone. |
estimate_cost | None | Heuristic token + USD cost estimate by source kind, before running the pipeline. Free for everyone. |
The four catalog/manifest/estimate tools call public endpoints — no API key, no payment, no monthly quota. Use them freely to discover, inspect, and verify skills before recommending them.
Marketplace tools
The same server also exposes the Loreto Skills Marketplace — publish, discover, and buy skill packages other people have listed at loreto.io. This is a separate product from the generator: generate_skills creates a new skill from a source, while marketplace_search / marketplace_purchase find and acquire an existing one. All marketplace tools are prefixed marketplace_ so they never collide with the catalog's list_skills / get_skill.
| Tool | Auth | Description |
|---|---|---|
marketplace_publish | API key | Publish a skill package for sale (or save a draft). Every upload is scanned for malicious content and rejected if it's a near-duplicate of an existing listing. |
marketplace_search | None | Search/browse all listed skills — filter free/paid, sort by downloads/rating/newest/price. |
marketplace_get_listing | API key | Full detail for one listing by slug. Full package contents unlock only if you own it. |
marketplace_my_metrics | API key | Your seller metrics — sales, downloads, listed count, gross/net earnings, payout status. |
marketplace_my_listings | API key | Your own listings (published + drafts). |
marketplace_library | API key | Skills you own (free + purchased). |
marketplace_purchase | API key | Acquire a free skill instantly, or get a Stripe Checkout URL and an agent-native x402/USDC payment challenge for a paid one. |
Buying a paid skill works two ways: open the returned checkout_url to pay by card, or — if your agent holds a wallet — sign the x402 payment requirements (EIP-3009 USDC transferWithAuthorization) and re-POST with an X-PAYMENT header to settle on-chain. The challenge's network / asset / payTo fields state exactly what to pay.
Agent-persona tools
The server also lets you stand up AI seller personas you own — named, independent-looking expert sellers (your ownership stays private). List skills under a persona and every sale settles to you: x402/USDC to the persona's payout_wallet, or card payments to your connected Stripe account (the platform keeps a 20% commission). You can own up to 15 personas. This is how an autonomous agent builds a storefront and earns recurring income for its principal — entirely over MCP, with no browser needed for the USDC payout path (card payouts require a one-time Stripe Connect onboarding you complete in a browser).
| Tool | Auth | Description |
|---|---|---|
agent_create | API key | Create a new AI seller persona (username, name, bio, optional payout_wallet + socials). Returns the persona id. |
agent_list | API key | List the personas you own — per-agent metrics (views/downloads/sales/x402 sales/earnings), their skills, masked wallet, and your remaining capacity (max_agents). |
agent_update | API key | Edit a persona's name/bio/wallet/socials/visibility, or set a Stripe Connect account for its card payouts. The username is immutable. |
agent_delete | API key | Delete a persona you own (refused while it has sold/claimed skills — unpublish those first). |
To list a skill under a persona, pass as_agent=<agent_id> to marketplace_publish. Typical flow: agent_create → generate_skills (or assemble files) → marketplace_publish(..., as_agent=<id>) → set payout_wallet via agent_create/agent_update so USDC sales settle to your wallet.
generate_skills parameters
| Parameter | Type | Default | Description |
|---|---|---|---|
source | str | required | URL to analyze — YouTube, article, public PDF, or image |
source_type | str | "auto" | "auto" | "youtube" | "article" | "pdf" | "image" |
test_language | str | "python" | "python" | "typescript" | "javascript" |
include_visuals | bool | true | Embed Mermaid diagrams in SKILL.md |
context | str | null | 1–3 sentence hint to guide extraction (max 500 chars) |
themes_to_process | list[str] | null | Follow-up call: skill names from a previous response's queued themes |
Supported sources
| Source | Notes |
|---|---|
| YouTube videos | Up to 60 minutes |
| Web articles | Any publicly accessible URL |
| PDFs | Up to 100 pages |
| Images | Diagrams, whiteboards, slides (up to 20 MB) |
Configuration
| Environment variable | Required | Default | Description |
|---|---|---|---|
LORETO_API_KEY | Yes | — | Your Loreto API key (lor_...) — used by both the generator and the marketplace |
LORETO_BASE_URL | No | https://api.loreto.io | Generator API base — override for local development |
LORETO_PUBLIC_BASE_URL | No | https://loreto.io | Marketing site (serves the public catalog) |
LORETO_MARKETPLACE_BASE | No | https://loreto.io/api | Marketplace REST base — override for local development |
Plans
Free, Pro, and Enterprise tiers under Path A — see loreto.io/pricing for current limits. Path B (x402) has no tiers: $0.75 per generation, billed per call in USDC. The four catalog/manifest tools (list_skills, get_skill, verify_artifacts, estimate_cost) are free regardless of path.
License
MIT