aibuiltwithdeveloper-tools
Scores a website’s AI technology adoption using BuiltWith data through an MCP server.
Quick Install
Automated & IDE SetupCopy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.
One-click editor setup isn’t available for this listing yet — we don’t have a confirmed install command, and we’d rather show nothing than point your editor at the wrong package or host. Follow the project’s own setup instructions, linked above.
Manual Client & Custom JSON ConfigExpand JSON ▾
No confirmed setup config for this listing yet. We only publish a config block when the install details come from the project itself — its README, its docs, or a verified owner. We haven’t found those for AI Stack Score, and we’d rather show nothing than a guess you’d paste into your client. Follow the project’s own setup instructions for the current steps.
Overview
Use cases
Score a website’s AI technology adoption
Evaluate BuiltWith-based AI adoption data
Bring website AI scores into an agent workflow
Key features
Score website AI technology adoption
Use BuiltWith data for scoring
Expose website scoring through MCP
Capabilities & Tool Schemas
Inspect callable tools, capabilities, and parameters exposed to AI agents by AI Stack Score.
Extracted Tool Capabilities
Score website AI technology adoption
Use BuiltWith data for scoring
Expose website scoring through MCP
How AI Stack Score works
What AI Stack Score MCP server does
The AI Stack Score MCP server evaluates a website’s adoption of AI technology. Its scoring is based on BuiltWith data, which is the only named data source in the available project information. The result is intended to represent how much AI technology a website has adopted.
This makes the server relevant for agents that need to inspect a website from an AI-technology perspective rather than perform general web research. The available description does not define the score’s scale, its individual factors, or the format of the returned result.
How it works
An AI agent uses the MCP connection to request a score for a website. AI Stack Score then relies on BuiltWith data to assess the site’s AI technology adoption. The supplied material does not document whether the input must be a URL, domain, or another identifier, so clients should verify the expected request format before implementation.
No information is available about authentication, BuiltWith API access, caching, rate limits, or whether scores are calculated on demand. Those details may affect how an agent should handle repeated requests and errors.
Tools and capabilities
The documented capability is website AI-adoption scoring. The source material does not list formal MCP tool names, parameters, or return schemas. Based on the description, an agent can use the AI Stack Score MCP server to:
- Request an AI-technology adoption score for a website.
- Base that assessment on BuiltWith data.
- Bring the score into an MCP-compatible agent workflow.
Do not assume that the server provides broader BuiltWith lookups, technology inventories, historical comparisons, or recommendations; none of those capabilities are described.
Setup and configuration
Installation and configuration instructions are not available in the provided material. There are no documented environment variables, command examples, transport settings, dependency requirements, or authentication steps. The repository field points to aistackscore.com, but it does not establish a specific installation method or client configuration.
Before deploying the AI Stack Score MCP server, confirm how the MCP endpoint is started, how a website is supplied, and whether a BuiltWith credential is required. These requirements cannot be inferred from the short description alone.
Limitations and notes
The available information is limited to the server’s purpose and data source. It does not state the scoring methodology, supported website types, data freshness, error behavior, licensing, or supported MCP clients. It also does not confirm compatibility with any specific editor or desktop application.
Treat the AI Stack Score MCP server as a focused scoring capability, not as a documented general-purpose BuiltWith interface. Validate the output and integration details against the project’s own documentation before using it in production workflows.
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Frequently Asked Questions about AI Stack Score
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<a href="https://allmcps.com/mcp/ai-stack-score"><img src="https://allmcps.com/api/badge/ai-stack-score?style=directory" alt="AI Stack Score on AllMCPs" /></a>Technical Specs & Signals
CategoryDeveloper Tools
9/9 checks healthy over the last 61d
36Quality signal: Fair · 36/100How this signal is calculated ▾
Server availability25/25
Verified ownership0/20
Documentation & tools10/30
Adoption & activity1/15
Community engagement0/10
A guidance signal from public completeness & health data — not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.
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