Question 1

What exactly is an MCP Server?

Accepted Answer

MCP (Model Context Protocol) Server acts as a bridge, allowing AI models to access and interact with external data sources and tools. It standardizes how applications provide context to LLMs.

Question 2

How does Clarity MCP work?

Accepted Answer

Clarity MCP uses HAR (HTTP Archive) files to capture browser network requests, extracts API endpoints, and then uses AI to generate tools that AI agents can use to interact with those APIs.

Question 3

What are the benefits of using MCP Servers?

Accepted Answer

MCP Servers enable AI agents to access real-time information, automate tasks, personalize recommendations, and integrate with various digital services, improving efficiency and accuracy.

Question 4

What is a HAR file and how do I create one?

Accepted Answer

A HAR (HTTP Archive) file captures all network requests your browser makes while interacting with a website. You can create one using your browser's developer tools (usually accessed by pressing F12).

Question 5

How do I install and run Clarity MCP?

Accepted Answer

You can install Clarity MCP using npm (`npm install -g @lekt9/clarity-mcp`). After setting your API key, you can run the server with the `clarity-mcp` command.

Question 6

What is UBOS, and how does it relate to MCP Servers?

Accepted Answer

UBOS is a full-stack AI Agent Development Platform that helps you orchestrate AI Agents, connect them with your enterprise data, and build custom AI Agents. MCP Servers can be integrated into the UBOS platform to enhance AI agent capabilities.

Question 7

What kind of information can be found in HAR files and what are the security considerations?

Accepted Answer

HAR files can contain sensitive information like cookies, authentication tokens, and personal data. Handle them securely and avoid sharing them publicly.

Question 8

Can I use Clarity MCP with AI models other than Claude?

Accepted Answer

While the documentation specifically mentions Claude, the underlying principles of MCPs and the OpenAPI compliance of Clarity MCP suggest it can be adapted for use with other AI models that support the MCP protocol.

Question 9

Are MCPs just APIs with a different name?

Accepted Answer

MCPs can be considered APIs packaged in a way that's optimized for AI consumption. They provide a standardized way for AI agents to interact with external services.

Question 10

What are the limitations of Clarity MCP?

Accepted Answer

The server requires a valid API key, and tool execution depends on the availability of the Clarity backend. It also does not cache tool definitions or results.

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