Flippa MCP
The Flippa MCP server provides AI-powered tools to search, analyze, and evaluate online business listings on the Flippa marketplace — no API key or account required.
Search Listings (
flippa_search_listings): Browse the marketplace with filters for property type (SaaS, website, ecommerce, FBA, apps, YouTube, newsletters, etc.), listing status, sale method (auction or classified), and sorting options (most profitable, highest price, ending soonest, etc.).Get Listing Details (
flippa_get_listing): Retrieve complete information for a specific listing by ID, including pricing, revenue, profit, traffic stats, seller info, verification status, and full description.Analyze a Listing (
flippa_analyze_listing): Perform a valuation analysis — computes revenue/profit multiples, ROI estimates, and price-per-visitor metrics; delivers a verdict (underpriced, fair, overpriced, or insufficient data); and flags risk factors like unverified revenue, low traffic, no bids, or missing data.Find Comparable Sales (
flippa_comparable_sales): Discover similar listings for benchmarking, with aggregate stats like average price, median price, average revenue multiple, and price range.Market Overview (
flippa_market_overview): Get a broad market snapshot with aggregate statistics across all or specific property types, including total listing counts, price/revenue/profit stats (min, max, avg, median), average revenue multiples, and verified revenue percentages.
Results can be returned in human-readable markdown or structured JSON, and the server runs cross-platform via Claude Desktop integration.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Flippa MCP find me profitable SaaS businesses for sale under $50,000"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Flippa.com Listings MCP
Search, analyze, and evaluate online businesses on Flippa — powered by AI.
No API key required. No account needed. Just plug into Claude and go.
npx flippa-mcp-serverWorks on Mac, Windows, and Linux.
Why Flippa MCP · Tools · Getting Started · Examples
Why Flippa MCP
Flippa is the world's largest marketplace for buying and selling online businesses — websites, SaaS products, ecommerce stores, apps, newsletters, and more. Thousands of listings, each with revenue claims, traffic stats, and asking prices that may or may not make sense.
Evaluating a listing manually means checking revenue multiples, comparing prices across similar businesses, assessing risk factors, and doing math you'll probably get wrong at 2am. Multiply that by the dozens of listings you need to review to find a good deal.
Flippa MCP gives Claude full marketplace intelligence. Five specialized tools that search listings, pull detailed financials, compute valuation metrics, find comparable sales, and generate market overviews. Zero configuration. No API key. No Flippa account. Just install and ask Claude to find you a good deal.
Related MCP server: BizIntel MCP Server
Who This Is For
Entrepreneurs evaluating businesses to buy on Flippa
Investors doing due diligence on online business acquisitions
Sellers researching pricing and market conditions before listing
Anyone who wants AI-powered marketplace intelligence without the spreadsheet grind
Getting Started
Install
npx flippa-mcp-serverOr install globally:
npm install -g flippa-mcp-serverClaude Desktop Configuration
Add to your Claude Desktop config file:
{
"mcpServers": {
"flippa": {
"command": "npx",
"args": ["flippa-mcp-server"]
}
}
}Platform | Path |
macOS |
|
Windows |
|
Linux |
|
No API key required! The Flippa listings API is public. All 5 tools work without any authentication or Flippa account.
Tools
Tool | Description |
| Search and browse listings with filters for type, status, sale method, and sorting |
| Get complete details for any listing by ID |
| Compute valuation metrics: revenue multiples, ROI, risk factors, and buy/pass verdict |
| Find comparable listings and get aggregate pricing stats |
| Get market-wide statistics across property types |
Parameter | Type | Required | Default | Description |
| string | No | — |
|
| string | No |
|
|
| string | No | — |
|
| string | No | — |
|
| number | No |
| Page number for pagination |
| number | No |
| Results per page (1–100) |
| string | No |
|
|
Parameter | Type | Required | Default | Description |
| string | Yes | — | The Flippa listing ID (e.g., |
| string | No |
|
|
Returns complete listing data: pricing, revenue, profit, traffic, seller info, verification status, description, images, and more.
Parameter | Type | Required | Default | Description |
| string | Yes | — | The Flippa listing ID to analyze |
| string | No |
|
|
Returns computed metrics:
Revenue multiple, profit multiple, annual revenue
Price per visitor, revenue per visitor
Estimated ROI in months
Verdict: underpriced, fair, overpriced, or insufficient_data
Risk factors (unverified revenue, low traffic, no bids, etc.)
Parameter | Type | Required | Default | Description |
| string | No | — | Find comparables for this listing (uses its type and revenue range) |
| string | No | — | Filter by type. Overrides listing's type if both provided. |
| number | No |
| Number of comparables (1–20) |
| string | No |
|
|
Returns comparable listings with aggregate stats: average price, median price, average revenue multiple, and price range.
Parameter | Type | Required | Default | Description |
| string | No | — | Focus on one type, or omit for full market view |
| string | No |
|
|
Returns market-wide stats: total listings, breakdown by type, price/revenue/profit statistics (min, max, avg, median), average revenue multiple, and verified revenue percentage.
Examples
Search for profitable SaaS businesses
"Find me SaaS listings on Flippa sorted by most profitable"
Uses flippa_search_listings with property_type: "saas" and sort_alias: "most_profitable".
Analyze a specific listing
"Analyze Flippa listing 12299903 — is it fairly priced?"
Uses flippa_analyze_listing to compute revenue multiples, ROI, and risk factors, then delivers a verdict.
Compare with the market
"Find comparable listings for this SaaS business and tell me if the asking price is reasonable"
Uses flippa_comparable_sales to find similar listings by type and revenue range, then compares pricing.
Get a market snapshot
"Give me an overview of the current Flippa marketplace for ecommerce stores"
Uses flippa_market_overview to aggregate stats across all ecommerce listings.
Deep dive evaluation
"Search for the top 5 most profitable websites on Flippa, then analyze each one and tell me which is the best deal"
Chains flippa_search_listings → flippa_analyze_listing across multiple listings to find the best opportunity.
How Analysis Works
The flippa_analyze_listing tool fetches a listing and computes valuation metrics:
Metric | Formula |
Revenue Multiple | Asking Price / Annual Revenue |
Profit Multiple | Asking Price / Annual Profit |
ROI Estimate | Asking Price / Monthly Profit (payback in months) |
Price per Visitor | Asking Price / Monthly Uniques |
Verdict Logic
Revenue Multiple | Verdict |
< 2x | Underpriced — below typical range, investigate why |
2x – 4x | Fair — within standard online business valuation range |
> 4x | Overpriced — above typical range, ensure premium is justified |
No revenue data | Insufficient Data — cannot determine valuation |
Risk Factors Detected
The tool automatically flags these concerns:
No reported revenue or profit
Traffic data unavailable or very low (< 1,000 uniques/mo)
Revenue not verified by Flippa
Traffic not verified by Flippa
Seller is not a Super Seller
No bids on the listing
No images provided
Very short listing description (< 100 chars)
Confidential listing with limited data
Configuration
Variable | Required | Default | Description |
| No |
| Override the Flippa API base URL |
| No | — | Bearer token for future authenticated endpoints (watchlist, bidding) |
With environment variables
{
"mcpServers": {
"flippa": {
"command": "npx",
"args": ["flippa-mcp-server"],
"env": {
"FLIPPA_API_TOKEN": "your-token-here"
}
}
}
}Supported Property Types
Type | Description |
| Content sites, blogs, media properties |
| Software as a Service businesses |
| Online stores and shops |
| Amazon FBA businesses |
| iOS applications |
| Android applications |
| AI-powered applications and tools |
| YouTube channels |
| Email newsletters |
| Service businesses and agencies |
| Other business types |
Development
git clone https://github.com/sind00/flippa-mcp.git
cd flippa-mcp
npm install
npm run dev # Watch mode with tsx
npm run build # Compile TypeScript
npm start # Run compiled serverProject Structure
src/
index.ts # Server entry point
types.ts # TypeScript interfaces
constants.ts # Configuration constants
schemas/
listing.ts # Zod validation schemas
services/
flippa-client.ts # HTTP client (retry, rate limiting)
formatter.ts # Response formatting (markdown/json)
tools/
search.ts # flippa_search_listings
details.ts # flippa_get_listing
analyze.ts # flippa_analyze_listing
compare.ts # flippa_comparable_sales
market.ts # flippa_market_overviewSupport This Project
If Flippa MCP helps you find great deals, consider sponsoring to keep development going:
License
MIT License. See LICENSE for details.
Flippa has the listings. <-- MCP --> LLMs have the brains.
Available Tools
5 toolsflippa_analyze_listingAnalyze Flippa ListingARead-only
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" }
Inputs: listing_id (required), response_format.
flippa_comparable_salesFind Comparable Flippa ListingsARead-only
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 }
Inputs: listing_id, property_type, page_size, response_format.
flippa_get_listingGet Flippa Listing DetailsARead-onlyIdempotent
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" }
Inputs: listing_id (required), response_format.
flippa_market_overviewFlippa Market OverviewARead-only
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" }
Inputs: property_type, response_format.
flippa_search_listingsSearch Flippa ListingsARead-onlyIdempotent
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" }
Inputs: property_type, status, sale_method, sort_alias, +3 more.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
TDQS
Scored across 5 tools
Each tool has a clearly distinct purpose with no overlap: analyze_listing focuses on valuation metrics and risk assessment, comparable_sales finds similar listings for comparison, get_listing retrieves detailed listing data, market_overview provides aggregate statistics, and search_listings enables browsing and filtering. The descriptions clearly differentiate their functions, eliminating any potential for confusion.
All tools follow a perfect 'flippa_verb_noun' pattern (e.g., flippa_analyze_listing, flippa_comparable_sales). This consistent naming convention makes the tool set predictable and easy to understand, with no deviations in style or structure across all five tools.
With 5 tools, this server is well-scoped for analyzing and browsing Flippa marketplace data. Each tool serves a unique and essential function—from individual listing analysis to market-wide insights—without being overly sparse or bloated, making the count ideal for the domain.
The tool set covers core workflows for Flippa analysis: retrieving listings (get_listing, search_listings), evaluating them (analyze_listing, comparable_sales), and understanding market context (market_overview). A minor gap is the lack of tools for interacting with listings (e.g., bidding or saving), but this is reasonable for a read-only analysis server focused on data retrieval and assessment.
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