CardVault MCP Server
v3.7Connect your AI agent to the largest free sports card database via the Model Context Protocol. Search 3,000+ cards, compare players, calculate grading ROI, and evaluate sealed product expected value.
Quick Start
1. Add to your MCP client config:
{
"mcpServers": {
"cardvault": {
"url": "https://cardvault-two.vercel.app/api/mcp",
"transport": "http"
}
}
}2. Or use curl to test:
curl -X POST https://cardvault-two.vercel.app/api/mcp \
-H "Content-Type: application/json" \
-d '{"method":"tools/list","id":1,"jsonrpc":"2.0"}'3. Discovery endpoint:
GET https://cardvault-two.vercel.app/.well-known/mcp.json
Available Tools
search_cardsSearch cards by player name, set, year, or sport
Example request
{
"method": "tools/call",
"params": {
"name": "search_cards",
"arguments": {
"query": "Trout",
"sport": "baseball",
"limit": 3
}
},
"id": 1,
"jsonrpc": "2.0"
}get_card_priceGet estimated raw and graded values for a card
Example request
{
"method": "tools/call",
"params": {
"name": "get_card_price",
"arguments": {
"player": "Mike Trout",
"year": 2011
}
},
"id": 2,
"jsonrpc": "2.0"
}grading_roiCalculate grading ROI for PSA, CGC, or SGC
Example request
{
"method": "tools/call",
"params": {
"name": "grading_roi",
"arguments": {
"raw_value": 150,
"company": "psa",
"expected_grade": 9
}
},
"id": 3,
"jsonrpc": "2.0"
}sealed_product_evCalculate expected value of sealed card products
Example request
{
"method": "tools/call",
"params": {
"name": "sealed_product_ev",
"arguments": {
"product_name": "Prizm Basketball"
}
},
"id": 4,
"jsonrpc": "2.0"
}list_setsList card sets with counts and completion costs
Example request
{
"method": "tools/call",
"params": {
"name": "list_sets",
"arguments": {
"sport": "baseball",
"year": 2024
}
},
"id": 5,
"jsonrpc": "2.0"
}player_lookupGet all cards for a player with portfolio value
Example request
{
"method": "tools/call",
"params": {
"name": "player_lookup",
"arguments": {
"player": "Shohei Ohtani"
}
},
"id": 6,
"jsonrpc": "2.0"
}compare_playersCompare two players side-by-side with investment analysis
Example request
{
"method": "tools/call",
"params": {
"name": "compare_players",
"arguments": {
"player_a": "Mike Trout",
"player_b": "Shohei Ohtani"
}
},
"id": 7,
"jsonrpc": "2.0"
}Protocol Details
| Protocol | Model Context Protocol (MCP) |
| Version | 2024-11-05 |
| Transport | HTTP (Streamable HTTP) |
| Format | JSON-RPC 2.0 |
| Endpoint | POST /api/mcp |
| Discovery | GET /.well-known/mcp.json |
| Auth | None (free, public) |
Use Cases
AI Price Lookup
Ask your AI assistant "What is a 1986 Fleer Michael Jordan worth?" and get instant pricing data.
Portfolio Analysis
Have your agent compare two players' card portfolios to inform investment decisions.
Grading Decisions
Calculate whether a card is worth sending to PSA, CGC, or SGC before spending money.
Sealed Product Analysis
Evaluate the expected value of hobby boxes and blasters before buying.
Collection Building
Search for rookie cards, filter by sport and year, and find the best cards to collect.
Market Research
List sets, compare completion costs, and find undervalued collections.