Skip to main content
Glama
Flippa MCP
by sind00

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.

npm version npm downloads GitHub stars License Sponsor

npx flippa-mcp-server

Works on Mac, Windows, and Linux.

Flippa MCP Server

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-server

Or install globally:

npm install -g flippa-mcp-server

Claude Desktop Configuration

Add to your Claude Desktop config file:

{
  "mcpServers": {
    "flippa": {
      "command": "npx",
      "args": ["flippa-mcp-server"]
    }
  }
}

Platform

Path

macOS

~/Library/Application Support/Claude/claude_desktop_config.json

Windows

%APPDATA%\Claude\claude_desktop_config.json

Linux

~/.config/claude/claude_desktop_config.json

TIP

No API key required! The Flippa listings API is public. All 5 tools work without any authentication or Flippa account.


Tools

Tool

Description

flippa_search_listings

Search and browse listings with filters for type, status, sale method, and sorting

flippa_get_listing

Get complete details for any listing by ID

flippa_analyze_listing

Compute valuation metrics: revenue multiples, ROI, risk factors, and buy/pass verdict

flippa_comparable_sales

Find comparable listings and get aggregate pricing stats

flippa_market_overview

Get market-wide statistics across property types

Parameter

Type

Required

Default

Description

property_type

string

No

—

website, saas, ecommerce_store, fba, ios_app, android_app, ai_apps_and_tools, youtube, newsletter, service, other

status

string

No

open

open, closed, ended

sale_method

string

No

—

auction, classified

sort_alias

string

No

—

lowest_price, highest_price, most_active, most_recent, ending_soonest, most_profitable, most_relevant

page_number

number

No

1

Page number for pagination

page_size

number

No

30

Results per page (1–100)

response_format

string

No

markdown

markdown or json

Parameter

Type

Required

Default

Description

listing_id

string

Yes

—

The Flippa listing ID (e.g., "12299903")

response_format

string

No

markdown

markdown or json

Returns complete listing data: pricing, revenue, profit, traffic, seller info, verification status, description, images, and more.

Parameter

Type

Required

Default

Description

listing_id

string

Yes

—

The Flippa listing ID to analyze

response_format

string

No

markdown

markdown or json

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

listing_id

string

No

—

Find comparables for this listing (uses its type and revenue range)

property_type

string

No

—

Filter by type. Overrides listing's type if both provided.

page_size

number

No

10

Number of comparables (1–20)

response_format

string

No

markdown

markdown or json

Returns comparable listings with aggregate stats: average price, median price, average revenue multiple, and price range.

Parameter

Type

Required

Default

Description

property_type

string

No

—

Focus on one type, or omit for full market view

response_format

string

No

markdown

markdown or json

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

FLIPPA_BASE_URL

No

https://flippa.com/v3

Override the Flippa API base URL

FLIPPA_API_TOKEN

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

website

Content sites, blogs, media properties

saas

Software as a Service businesses

ecommerce_store

Online stores and shops

fba

Amazon FBA businesses

ios_app

iOS applications

android_app

Android applications

ai_apps_and_tools

AI-powered applications and tools

youtube

YouTube channels

newsletter

Email newsletters

service

Service businesses and agencies

other

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 server

Project 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_overview

Support This Project

If Flippa MCP helps you find great deals, consider sponsoring to keep development going:

Sponsor on GitHub


License

MIT License. See LICENSE for details.


Flippa has the listings. <-- MCP --> LLMs have the brains.

Available Tools

5 tools
flippa_analyze_listingAnalyze Flippa ListingA
Read-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 ListingsA
Read-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 DetailsA
Read-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 OverviewA
Read-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 ListingsA
Read-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

    A4.2/5.0

    Scored across 5 tools

    Disambiguation5/5

    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.

    Naming Consistency5/5

    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.

    Tool Count5/5

    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.

    Completeness4/5

    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.

    Maintenance

    ActivityNo data
    ResponsivenessOutdated data

    Related MCP Connectors

    Related MCP Servers

    • A
      license
      Not graded
      quality
      D
      maintenance
      Connects AI assistants to the TrustMRR API to browse, filter, and analyze startup listings by revenue, MRR, and growth metrics. It enables detailed retrieval of startup financials and pricing for comprehensive deal analysis.
      17 npm
      14
      MIT
    • A
      license
      Not graded
      quality
      D
      maintenance
      Enables AI assistants to perform real-time business intelligence tasks including competitive analysis, website scoring, review analysis, and market research.
      MIT
    • A
      license
      Not graded
      quality
      C
      maintenance
      GovAuctions.app is a free public site for searching government surplus auctions. This MCP server exposes its data: live listings from GSA and other public sellers across the US, UK, CA and AU, sold-price comps from 170,000+ closed auctions, and a 0-100 Flip Score resale signal.
      10 npm
      MIT
    • A
      license
      Not graded
      quality
      F
      maintenance
      Provides real-time website audits, lead scoring, tech-stack detection, and local-business search for AI agents doing sales outreach and competitor research.
      MIT