Flippa MCP
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| FLIPPA_BASE_URL | No | Override the Flippa API base URL | https://flippa.com/v3 |
| FLIPPA_API_TOKEN | No | Bearer token for future authenticated endpoints (watchlist, bidding) |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": true
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| flippa_search_listingsA | Search and browse listings on the Flippa marketplace. Args:
Returns: Paginated list of Flippa listings with price, revenue, profit, bid count, and verification status. Includes pagination metadata with has_more flag. Examples:
|
| flippa_get_listingA | Get full details for a specific Flippa listing by ID. Args:
Returns: Complete listing details including price, revenue, profit, traffic stats, seller info, verification status, description, and more. Examples:
|
| flippa_analyze_listingA | 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:
Returns: Computed analysis including:
Examples:
|
| flippa_comparable_salesA | 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:
Returns: Target listing (if listing_id provided), list of comparable listings, average price, median price, average revenue multiple, and price range. Examples:
|
| flippa_market_overviewA | 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:
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:
|
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
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.