Agent Tool IntelligenceAI Visibility for MCP Tools

Agent Tool Intelligence is a free, open-source platform designed to assess the AI visibility of Model Context Protocol (MCP) tools. Simply paste a GitHub link to get a rating from F to B+ in just 5 seconds, helping developers understand how discoverable their tools are by AI agents. Based on an analysis of nearly 40,000 MCP servers, it offers transparent methodology, README badges, and monthly ecosystem reports, all without registration or cost.

free

MCP toolsAI agentstool evaluationopen sourceMIT licenseGitHubvisibility scoredeveloper toolsecosystem reportAI development

IndexedJuly 8, 2026

UpdatedJuly 11, 2026

3.0 (0 Number of reviews)

If you're a developer building tools for the Model Context Protocol (MCP), you've probably hit a wall: your code is solid, but nobody's using it. It's like AI agents can't even find your creation. This is precisely the problem Agent Tool Intelligence aims to solve. It's a free, open-source platform that doesn't require any sign-up, and it can give your tool a clear visibility score in about five seconds.

Understanding MCP Tools and the Need for Visibility

The Model Context Protocol (MCP) is becoming a standard for how AI agents interact with external tools. More and more developers are spinning up MCP servers to extend AI capabilities, which is great for the ecosystem. The flip side? It's growing so fast that quality tools often get lost in the noise. The Agent Tool Intelligence team dug through 39,762 MCP servers and found a striking statistic: 54% of these tools had robust code but zero users. They were practically invisible to AI agents. This tool steps in to tell you exactly where your creation stands in this crowded landscape.

How Agent Tool Intelligence Works

Using the platform couldn't be simpler. Head to the website, paste your MCP server's GitHub URL into the input box, and hit 'score'. In roughly five seconds, you'll get a letter grade, ranging from F (the lowest) to B+ (the highest). No registration, no fees, no hidden costs. Beyond the grade, you'll also receive a badge you can embed directly into your project's README, plus a link to a monthly ecosystem report. The entire scoring methodology is completely open, built on a set of reproducible metrics like documentation completeness, naming conventions, and response speed.

Imagine an indie developer who spent weeks crafting a neat file system MCP tool. After running it through Agent Tool Intelligence, they get a C. The report highlights missing usage instructions and parameter examples in their README. A quick fix, and suddenly the score jumps to B-, and GitHub stars start trickling in. This small example underscores a crucial point: sometimes, visibility trumps raw functionality.

Open Source, Transparent, and Developer-Focused

Agent Tool Intelligence itself is open source, licensed under the MIT protocol. This means you can peek under the hood at its scoring logic, or even deploy and improve it yourself. The project doesn't just offer individual tool scores; it also publishes monthly ecosystem reports. These reports give you a bird's-eye view of the broader MCP landscape and its trends. For developers serious about their tools, this kind of insight is invaluable.

Typical Use Case: Any developer building MCP tools can quickly check their visibility score after launching a new tool or iterating on an existing one. The feedback helps optimize documentation and configuration. Meanwhile, the ecosystem reports can guide development direction by highlighting popular or emerging functional areas.

Strengths and Limitations

Fast and Free: Get a score by just pasting a URL, no registration needed, perfect for rapid iteration.
Data-Driven: Scores are based on real data from nearly 40,000 MCP servers, offering practical insights.
Open Source & Transparent: The community can review and improve the scoring methodology, avoiding black-box operations.
Ecosystem View: Monthly reports provide a macro perspective, aiding strategic development.

Of course, no tool is perfect. Currently, the highest score is B+, which might not offer enough differentiation for truly top-tier tools. Also, it's exclusively for MCP protocol tools; if you're using other interfaces like direct APIs, it won't apply. And since it relies on public GitHub repository data, private repos are out of luck.

Practical Advice for Developers

If you're developing an MCP tool, consider running it through Agent Tool Intelligence before launch. Treat the score as a 'visibility health check.' Pay attention to the suggested improvements, whether it's your README structure, code examples, or response times. Subscribing to the monthly ecosystem report can also keep you informed about growing functional areas. And don't forget to add that score badge to your README – it's a visibility signal in itself.

Ultimately, in an increasingly crowded AI agent ecosystem, a tool that helps good work stand out is a win for both developers and the community. Agent Tool Intelligence makes a solid start with its simple, free, and open approach.

Pros & Cons

Pros

Provides a quick visibility score in 5 seconds
Scores are data-driven, based on nearly 40,000 MCP servers
Completely free to use with no registration required
Open-source and transparent scoring methodology, allowing community audit
Offers README badges and valuable monthly ecosystem reports

Cons

Maximum score is B+, lacking differentiation for top-tier tools
Only applicable to MCP protocol tools, not other API interfaces
Requires a public GitHub repository; private repos cannot be evaluated
Scoring metrics may not cover all aspects of tool quality (e.g., code maintainability)

Frequently Asked Questions

Is Agent Tool Intelligence free to use?

Yes, it's completely free. You don't need to register, provide an email, or enter any payment information to use the service.

How do I get a score for my MCP tool?

Simply visit the website, paste the public GitHub repository URL of your MCP server into the input field on the homepage, and click the 'score' button. You'll receive a grade from F to B+ within approximately 5 seconds.

Why does the scoring range only go up to B+?

The current scoring system, based on an analysis of 39,762 MCP servers, covers basic to good visibility. Future iterations may expand to include higher-tier grades as the ecosystem evolves and more data becomes available.

Is Agent Tool Intelligence an open-source project?

Absolutely. The project is licensed under the MIT protocol, meaning its code is fully open source. Community contributions and improvements are highly encouraged.

Can I evaluate a private GitHub repository?

Currently, Agent Tool Intelligence only supports public GitHub repositories. The scoring process requires access to the repository's content, which is not possible with private repositories.

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