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@webeyez/mcp-server
Advanced tools
Model Context Protocol (MCP) server for Webeyez. Access Webeyez session replays, JavaScript errors, conversion funnels, and performance diagnostics directly from any MCP-compatible AI client.
Expose Webeyez session replays, JavaScript errors, conversion funnels, rage clicks, and performance diagnostics directly to your AI agents and assistants (Claude, Cursor, Windsurf, ChatGPT, etc.) using the Model Context Protocol (MCP).
Webeyez is a real-time user experience monitoring, conversion optimization, and error diagnostics platform. It helps online businesses identify and resolve conversion leaks, user friction, client-side bugs, and performance anomalies.
The Webeyez MCP Server bridges your local AI tools directly to the Webeyez diagnostics engine. It is implemented as a secure proxy client, meaning the server runs safely on Webeyez infrastructure to protect your data and proprietary logic, while the local NPM package serves as a lightweight, secure gateway.
Use this MCP server when you want your AI developer agent or assistant to:
You do not need to install the server globally. The package can be run directly using npx:
npx -y @webeyez/mcp-server
The Webeyez MCP server supports both standard local stdio connection (using our NPM package as a secure proxy) and direct web-based SSE connections.
Add the server to your claude_desktop_config.json configuration file:
~/Library/Application Support/Claude/claude_desktop_config.json%APPDATA%\Claude\claude_desktop_config.json{
"mcpServers": {
"webeyez": {
"command": "npx",
"args": [
"-y",
"@webeyez/mcp-server"
],
"env": {
"WEBEYEZ_API_KEY": "your_webeyez_api_token_here"
}
}
}
}
Configure your editor to run the MCP proxy as a shell command:
command.npx -y @webeyez/mcp-server
WEBEYEZ_API_KEYWeb-based clients and custom applications can connect directly to the Webeyez SSE endpoint without any local installation:
https://api.app.webeyez.com/mcpx-api-key header or as a token URL query parameter.The following tools are exposed by the server for AI agents to query:
start_webeyez_query: Starts a long-running natural language query against the Webeyez diagnostics engine. Use this to ask questions about your session data, checkout friction, JS errors, or conversion drop-offs.check_webeyez_status: Polls the status and retrieves the final text answer/response of a query started with start_webeyez_query.get_organizations_list: Lists all Webeyez organizations you have access to (along with their organizationIds).get_organization_domains: Lists all registered domains for a specific organization.logout_webeyez: Safely clears connection state and credentials.get_js_errors: Returns client-side JavaScript console errors, occurrences, and stack traces.get_failed_api_calls: Lists failed HTTP/network requests (AJAX/Fetch returning 4xx or 5xx).get_session_examples: Retrieves recorded user session replay links matching specific filters.get_funnel_summary: Retrieves conversion rates and drop-off summaries for configured funnels.get_checkout_dropoffs: Returns checkout funnel friction details.get_revenue_loss_estimate: Returns estimated revenue impact caused by conversion drop-offs or errors.list_accounts / list_sites: Helper tools to retrieve accessible accounts and sites.WEBEYEZ_API_KEY (Required): Your personal API Key or Personal Access Token (PAT).WEBEYEZ_MCP_URL (Optional): Overrides the default hosted Webeyez MCP gateway endpoint (default: https://api.app.webeyez.com/mcp).The Webeyez MCP server uses a secure hybrid model:
ISC License.
FAQs
Model Context Protocol (MCP) server for Webeyez. Access Webeyez session replays, JavaScript errors, conversion funnels, and performance diagnostics directly from any MCP-compatible AI client.
The npm package @webeyez/mcp-server receives a total of 81 weekly downloads. As such, @webeyez/mcp-server popularity was classified as not popular.
We found that @webeyez/mcp-server demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 2 open source maintainers collaborating on the project.

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