Workflows & Use Cases

Step-by-step workflow patterns for common automotive research tasks using the MarketCheck MCP Server — vehicle valuation, market research, dealer analysis, EV trends, and UK market analysis.

This page provides ready-to-use workflow patterns that combine multiple MCP tools for common automotive research and analysis tasks. Each workflow shows the tools in order with example parameters.

Vehicle Valuation

The most common workflow — getting a comprehensive valuation for a specific vehicle.

# 1. Confirm vehicle specs and MSRP
decode_vin_neovin(vin="1HGCV1F34JA123456")

# 2. Get ML-predicted market price with comparables
predict_price_with_comparables(vin="1HGCV1F34JA123456", miles=35000, zip="90210")

# 3. Review price history across dealers
get_car_history(vin="1HGCV1F34JA123456")

This gives you the vehicle's factory specs, current estimated market value with comparable listings, and how the price has changed over time.

Market Research

Research a market segment to understand inventory, pricing, and supply dynamics.

# 1. Discover available filter values
search_active_cars(facets="make,model,powertrain_type", state="CA", rows=1)

# 2. Targeted search with validated values
search_active_cars(make="Toyota", powertrain_type="BEV", state="CA", rows=10)

# 3. Get market statistics (price, mileage, days on market)
search_active_cars(make="Toyota", model="RAV4", stats="price,dom", state="CA", rows=1)

Always start with a facets query. This prevents empty results from mismatched filter values and shows you exactly what the market looks like.

Dealer Analysis

Evaluate a dealer's inventory, sales performance, and turnover patterns.

# 1. Current inventory
search_active_cars(dealer_id="12345", rows=50, include_dealer_object=true)

# 2. Days-on-market statistics
search_past_90_days(dealer_id="12345", stats="dom", rows=1)

# 3. Recent sales
search_past_90_days(dealer_id="12345", sold=true, rows=20, sort_by="last_seen", sort_order="desc")

Competitive Pricing Analysis

Compare a vehicle's price against the broader market.

# 1. Decode the vehicle
decode_vin_neovin(vin="5YJSA1E21KF123456")

# 2. Get predicted price and comparables
predict_price_with_comparables(vin="5YJSA1E21KF123456", miles=28000, zip="94105")

# 3. Search for similar active listings in the area
search_active_cars(
  make="Tesla",
  model="Model S",
  year_range="2019-2020",
  state="CA",
  price_range="30000-60000",
  rows=20,
  sort_by="price",
  sort_order="asc"
)

EV Market Trends

Analyze the electric vehicle market across multiple dimensions.

The get_sold_summary tool is Experimental and available to Enterprise subscribers only.

# 1. Sold EV summary — top models by volume
get_sold_summary(
  fuel_type_category="EV",
  ranking_dimensions="make,model",
  ranking_measure="sold_count",
  ranking_order="desc",
  top_n=10
)

# 2. Active EV inventory breakdown by make
search_active_cars(powertrain_type="BEV", facets="make|0|50", rows=1)

# 3. EV pricing in California
search_active_cars(powertrain_type="BEV", state="CA", stats="price", rows=1)

Sold Vehicle Trends

Long-term sales analysis using up to 5 years of historical data.

The get_sold_summary tool is Experimental and available to Enterprise subscribers only.

# 1. Top sellers for a full year
get_sold_summary(
  date_from="2024-01-01",
  date_to="2024-12-31",
  ranking_dimensions="make,model",
  ranking_measure="sold_count",
  top_n=10
)

# 2. Which vehicles are selling above MSRP?
get_sold_summary(
  inventory_type="New",
  price_over_msrp_percentage=">0",
  ranking_dimensions="make,model,body_type",
  ranking_measure="price_over_msrp_percentage",
  ranking_order="desc"
)

# 3. Fastest-moving inventory by body type
get_sold_summary(
  body_type="SUV",
  ranking_measure="average_days_on_market",
  ranking_order="asc",
  top_n=20
)

Dealership Group Performance

Compare performance across dealership groups.

The get_sold_summary tool is Experimental and available to Enterprise subscribers only.

# 1. Top dealership groups by volume
get_sold_summary(
  date_from="2024-01-01",
  date_to="2024-12-31",
  ranking_dimensions="dealership_group_name",
  ranking_measure="sold_count",
  ranking_order="desc",
  top_n=20
)

# 2. Specific group breakdown by city
get_sold_summary(
  dealership_group_name="AutoNation Inc.",
  date_from="2024-01-01",
  date_to="2024-12-31",
  ranking_dimensions="make,model",
  ranking_measure="sold_count",
  summary_by="city_state"
)

UK Market Research

Research the UK automotive market with UK-specific filters.

# 1. Discover available makes and fuel types in the UK
search_uk_active_cars(facets="make,fuel_type,body_type", rows=1)

# 2. ULEZ-compliant electric vehicles in London
search_uk_active_cars(fuel_type="Electric", ulez_compliant="true", city="London", rows=10)

# 3. Recent BMW sales in England
search_uk_recent_cars(country="england", make="BMW", sold=true, rows=20)

Wholesale / Auction Analysis

Research auction inventory and wholesale pricing.

# 1. Search auction listings
search_active_cars(seller_type="auction", state="CA", rows=20)

# 2. Compare to retail pricing
search_active_cars(
  seller_type="dealer",
  make="Toyota",
  model="Camry",
  state="CA",
  stats="price",
  rows=1
)

Tips for Effective Workflows

Start broad, then narrow — Begin with facets to understand what data exists before applying specific filters
Use rows=1 with stats or facets — When you only need aggregate data, minimize the listing count
Combine tools sequentially — VIN decode → price predict → history gives a complete vehicle picture
Watch token usage — Keep include_dealer_object, include_build_object, and fetch_all_photos off unless specifically needed
Use powertrain_type over fuel_type — It has clean, normalized values (BEV, HEV, PHEV, etc.)