Flippa MCP

Search and browse listings on the Flippa marketplace.

Args:

• property_type: Filter by type (website, saas, ecommerce_store, fba, ios_app, android_app, ai_apps_and_tools, youtube, newsletter, service, other)

• status: Filter by status (open, closed, ended). Default: "open"

• sale_method: Filter by sale method (auction, classified)

• sort_alias: Sort by (lowest_price, highest_price, most_active, most_recent, ending_soonest, most_profitable, most_relevant)

• page_number: Page number (default 1)

• page_size: Results per page, 1-100 (default 30)

• response_format: "markdown" (default) or "json"

Returns: Paginated list of Flippa listings with price, revenue, profit, bid count, and verification status. Includes pagination metadata with has_more flag.

Examples:

• Search all open SaaS listings: { "property_type": "saas" }

• Most profitable websites: { "property_type": "website", "sort_alias": "most_profitable" }

• Ending soon auctions: { "sale_method": "auction", "sort_alias": "ending_soonest" }

Get full details for a specific Flippa listing by ID.

Args:

• listing_id: The Flippa listing ID (e.g., "12299903"). Required.

• response_format: "markdown" (default) or "json"

Returns: Complete listing details including price, revenue, profit, traffic stats, seller info, verification status, description, and more.

Examples:

• Get listing details: { "listing_id": "12299903" }

• Get as JSON: { "listing_id": "12299903", "response_format": "json" }

Analyze a Flippa listing's valuation, compute financial metrics, and assess risk.

This is a computed tool that fetches listing data and calculates valuation metrics including revenue multiples, profit multiples, ROI estimates, and risk factors.

Args:

• listing_id: The Flippa listing ID to analyze (e.g., "12299903"). Required.

• response_format: "markdown" (default) or "json"

Returns: Computed analysis including:

• Financial metrics: revenue/profit multiples, annual revenue, price per visitor, ROI estimate

• Verdict: "underpriced" (<2x revenue), "fair" (2-4x), "overpriced" (>4x), or "insufficient_data"

• Risk factors: unverified revenue/traffic, low traffic, no bids, missing images, etc.

Examples:

• Analyze a listing: { "listing_id": "12299903" }

• Get analysis as JSON: { "listing_id": "12299903", "response_format": "json" }

Find comparable listings on Flippa for valuation comparison.

If a listing_id is provided, fetches that listing first and uses its property_type and revenue range (0.5x-2x) to find similar listings. You can also search by property_type directly.

Args:

• listing_id: Find comparables for this listing. Optional.

• property_type: Filter by type. Overrides the target listing's type if both provided. Optional.

• page_size: Number of comparables to return, 1-20 (default 10)

• response_format: "markdown" (default) or "json"

Returns: Target listing (if listing_id provided), list of comparable listings, average price, median price, average revenue multiple, and price range.

Examples:

• Comps for a listing: { "listing_id": "12299903" }

• SaaS comparables: { "property_type": "saas", "page_size": 15 }

Get aggregate market statistics from the Flippa marketplace.

Queries listings across property types to build a market snapshot including total counts, price/revenue/profit statistics, and verification rates.

Args:

• property_type: Focus on a specific type (website, saas, ecommerce_store, etc.). If omitted, aggregates across all major types. Optional.

• response_format: "markdown" (default) or "json"

Returns: Market overview with total listings, breakdown by property type (count, avg price, avg revenue), price/revenue/profit statistics (min, max, avg, median), average revenue multiple, and verified revenue percentage.

Examples:

• Full market overview: {}

• SaaS market overview: { "property_type": "saas" }