The first MCP server for the LitecoinVM ecosystem — 433K+ trading card products, on-chain Merkle proofs, and Monte Carlo simulation on LiteForge.
Project description
The first Model Context Protocol server for the LitecoinVM ecosystem.
Plug any AI agent into 433K+ real trading card prices across 13 games — every price backed by on-chain Merkle proofs, not blind trust.
Why This Exists
AI agents are making decisions with market data — but how do they know the data is real?
Regular APIs require trust. You call an endpoint, you get a number, and you hope it's accurate. There's no way to verify it. For AI agents managing portfolios, executing trades, or assessing collateral, this is a problem.
This MCP server solves it. Every actively-priced product in the oracle is committed to a Merkle root on-chain daily. Any agent can request a Merkle proof for any card and independently verify the price against the LitecoinVM blockchain — no trust required.
What Makes This Different
| Feature | Regular Price API | LitVM TCG Oracle |
|---|---|---|
| Data source | Opaque server | 13.5M+ verified market observations |
| Verification | Trust the server | Merkle proof → on-chain verification |
| Simulation | None | Monte Carlo with calibrated parameters |
| Coverage | Limited | 433K products, 276K actively priced |
| For AI agents | Manual integration | MCP — works in Claude, GPT, Cursor |
| Blockchain | None | LitecoinVM (LiteForge, Chain 4441) |
Data Coverage
The oracle indexes the full TCGPlayer catalog and tracks live market prices:
| Metric | Count | Description |
|---|---|---|
| Total catalog | 433,671 | All products across 13 games and 85 categories |
| Actively priced | 276,788 | Products with a current market_price > 0 |
| Price observations | 13.5M+ | Daily snapshots collected over months |
| Merkle-provable | 276,788 | Only actively-priced products are committed on-chain |
| Zero-price entries | ~157K | Tokens, promos, bundles, foreign-market-only — searchable but not provable |
Transparency note: Not every product in the catalog has a market price. ~157K entries are catalog metadata with no trading activity (token cards, unopened case listings, foreign-language promos, etc.). These are returned by
search_cardsbut will return a404fromget_merkle_proofbecause zero-price products are not committed to the Merkle tree. This is by design — you wouldn't commit unverifiable data on-chain.
Quick Start
Install
pip install litvm-tcg-oracle
For live on-chain contract reads (optional):
pip install litvm-tcg-oracle[chain]
Claude Desktop
Add to ~/.claude/claude_desktop_config.json:
{
"mcpServers": {
"litvm-tcg-oracle": {
"command": "litvm-tcg-oracle"
}
}
}
Cursor / VS Code
Add to your MCP settings:
{
"litvm-tcg-oracle": {
"command": "litvm-tcg-oracle"
}
}
Then ask your AI: "Search for Charizard Base Set and simulate the price over 90 days"
Tools
1. search_cards — Full-Text Search
Search the full 433K product catalog using FTS5 full-text search.
→ search_cards(query="black lotus", game="Magic", limit=5)
Covers 13 games: Pokémon, Magic: The Gathering, Yu-Gi-Oh!, One Piece, Disney Lorcana, Flesh & Blood, Dragon Ball Super, Digimon, Star Wars, Union Arena, MetaZoo, Cardfight Vanguard, My Hero Academia.
Returns product IDs needed for get_price and get_merkle_proof.
2. get_price — Price + History
Get current market price and daily price history for any card.
→ get_price(card_name="Charizard Base Set Holo", days=90)
Returns market price, low (buy-it-now) price, and a daily price array. This history is what powers the Monte Carlo calibration — the same data the simulation engine uses to calculate drift and volatility.
3. get_merkle_proof — On-Chain Verification
This is the key differentiator. Get a cryptographic proof that a card's price was committed to the LitecoinVM blockchain.
→ get_merkle_proof(product_id=84198)
Returns a bytes32[] proof array (19 hashes for the current tree) that can be submitted to the MerklePriceOracle contract on LiteForge to verify the price without trusting any server.
Verification flow:
- Call
get_merkle_proof(product_id)→ receive proof + leaf data - Submit to
MerklePriceOracle.verifyPrice()on LiteForge (Chain 4441) - Contract checks the leaf against the committed Merkle root
- Returns
trueif and only if the price matches exactly
Leaf encoding (matches Solidity):
keccak256(bytes.concat(keccak256(abi.encode(
productId, categoryId, name, marketPrice, lowPrice
))))
Standard: OpenZeppelin MerkleProof (double-hash, sorted pairs)
Only the 276K actively-priced products are in the Merkle tree. Zero-price catalog entries return a
404— this is correct behavior.
4. oracle_status — Live On-Chain Status
Reads directly from the LiteForge blockchain via Caldera RPC — not cached data.
→ oracle_status()
Returns:
- MerklePriceOracle: Merkle root, total products, freshness, total root updates
- TCGPriceOracleV2: Total TWAP updates, last update timestamp, 660+ confirmed updates
- Database: Card count, price rows, latest data date
5. simulate_price — Monte Carlo Simulation
Stochastic price simulations calibrated from real market data.
→ simulate_price(card_name="Charizard Base Set", days=90, model="merton")
How the Simulation Works
This is not placeholder math. Every simulation parameter is calibrated from real price observations stored in the oracle database.
Calibration Pipeline:
Card name → FTS5 search → product_id → price_history (up to 365 days)
→ weekly resampling (ISO week buckets)
→ log-returns between weekly closing prices
→ annualized drift (μ) and volatility (σ)
→ jump detection via 2σ threshold on time-scaled returns
→ 10,000 vectorized numpy simulation paths
→ percentile forecast bands + VaR/CVaR risk metrics
Why weekly resampling? Daily TCG prices have irregular gaps (weekends, holidays, no sales). Weekly resampling produces stable drift estimates by collapsing daily observations into ISO-week buckets and computing log-returns between weekly closing prices. This eliminates the √Δt scaling problem that plagues irregularly-spaced data.
Models:
Geometric Brownian Motion (GBM)
dS = μ·S·dt + σ·S·dW
Standard log-normal diffusion — the foundation of Black-Scholes option pricing. Assumes continuous price movements with no sudden jumps.
Merton Jump-Diffusion (default)
dS = (μ − λk)·S·dt + σ·S·dW + J·S·dN
Extends GBM by adding Poisson-distributed price jumps to capture sudden market events — buyouts, influencer videos, ban lists, set reprints, tournament results.
| Symbol | Meaning | Calibration |
|---|---|---|
μ |
Drift (annualized return) | Weekly log-return mean × 52 |
σ |
Volatility | Weekly log-return stdev × √52 |
λ |
Jump intensity (jumps/year) | Count of returns > 2σ, annualized |
μⱼ |
Jump mean | Average of detected jump returns |
σⱼ |
Jump volatility | Stdev of detected jump returns |
k |
Drift compensator | E[eᴶ] - 1 (ensures fair pricing) |
dW |
Brownian motion | Standard Wiener process |
dN |
Jump arrival | Poisson(λ·dt) |
Risk Metrics:
- VaR 95%: "There is a 5% chance the price drops below $X over N days"
- CVaR 95% (Expected Shortfall): "If that tail event occurs, the average loss lands at $Y"
Transparency:
param_source: "calibrated_from_market_data"— real parameters from this card's historyparam_source: "default_tcg_priors"— insufficient data (<5 points), using conservative priors (3% drift, 40% vol)- Standard errors reported for μ, σ, λ to quantify parameter uncertainty
- Mean-reversion detection via lag-1 autocorrelation
References:
- Merton, R.C. (1976). Option pricing when underlying stock returns are discontinuous. Journal of Financial Economics, 3(1-2), 125-144.
- Black, F. & Scholes, M. (1973). The Pricing of Options and Corporate Liabilities. Journal of Political Economy, 81(3), 637-654.
6. get_market_snapshot — Market Overview
Top cards by value for any game.
→ get_market_snapshot(game="Pokemon", limit=25)
Architecture
┌──────────────────┐ MCP (stdio) ┌──────────────────────┐
│ │ ◄─────────────────────► │ │
│ AI Agent │ │ litvm-tcg-oracle │
│ (Claude, GPT, │ │ MCP Server │
│ Cursor, etc.) │ │ (pip install) │
│ │ │ │
└──────────────────┘ └──────┬───────┬───────┘
│ │
HTTPS │ │ RPC
│ │
▼ ▼
┌──────────────────┐ ┌─────────────┐
│ Oracle REST API │ │ LiteForge │
│ (Mac Mini) │ │ Chain 4441 │
│ │ │ │
│ 433K products │ │ Merkle + │
│ 13.5M prices │ │ V2 Oracle │
│ FTS5 search │ │ contracts │
└──────────────────┘ └─────────────┘
Off-chain layer (REST API): Search, prices, market data, simulation calibration
On-chain layer (LiteForge RPC): Merkle root verification, oracle contract status, TWAP feeds
The Mac Mini runs the daily pipeline (scrape → price update → Merkle root → on-chain push) and serves the REST API. The MCP server is a thin client that any developer can pip install and connect to Claude, GPT, or Cursor.
Configuration
| Variable | Default | Description |
|---|---|---|
LITVM_ORACLE_URL |
https://oracle.the-undesirables.com |
Override the API base URL |
Local Development
export LITVM_ORACLE_URL=http://localhost:8402
litvm-tcg-oracle
On-Chain Contracts
| Contract | Purpose |
|---|---|
| MerklePriceOracle | Daily Merkle root for 276K products |
| TCGPriceOracleV2 | Hourly TWAP for top 50 blue-chip cards |
Both contracts are deployed on LiteForge Testnet (Chain ID 4441) via the Caldera RPC. Run oracle_status() to get live contract addresses and on-chain state, or browse the Block Explorer.
License
- Use freely for development, research, and non-competing production use
- Cannot operate a competing price oracle service on LitecoinVM
- Converts to MIT on June 1, 2030
© 2026 The Undesirables LLC
Links
- Website: the-undesirables.com
- Oracle API: oracle.the-undesirables.com
- LitecoinVM: litvm.com
- Block Explorer: liteforge.explorer.caldera.xyz
- X: @undesirables_ai
Built by The Undesirables LLC — the first and only oracle on LitecoinVM.
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