
Agent Analytics
@Agent-Analytics
关于 Agent Analytics
Analytics your AI agent can actually use. Your agent tracks what's working across multiple projects, runs A/B experiments, analyzes funnels, and reports back to you. Works with Claude Code, Cursor, Windsurf, Codex, and any agent that speaks HTTP or MCP. Open source, API-first, no
基本信息
配置
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"agent-analytics": {
"url": "https://mcp.agentanalytics.sh/mcp"
}
}
}工具
未检测到工具
工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。
概览
What is Agent Analytics?
Agent Analytics is an open-source, API-first analytics tool designed for AI agents. It enables agents to track performance across multiple projects, run A/B experiments, analyze funnels, and report results directly to the user. It works with Claude Code, Cursor, Windsurf, Codex, and any agent that communicates via HTTP or MCP, and requires no dashboard.
How to use Agent Analytics?
—
Key features of Agent Analytics
- Tracks what’s working across multiple projects
- Runs A/B experiments
- Analyzes user funnels
- Reports results back to your agent
- Open source and API-first
- No dashboard required
Use cases of Agent Analytics
- AI agents monitoring performance across different projects
- Automating A/B tests for agent-driven workflows
- Analyzing funnel behavior from agent interactions
- Receiving automated analytics reports without a UI
FAQ from Agent Analytics
Which agents are compatible with Agent Analytics?
Claude Code, Cursor, Windsurf, Codex, and any agent that speaks HTTP or MCP.
Is Agent Analytics open source?
Yes, it is open source.
Does Agent Analytics require a dashboard?
No, it is designed to be dashboard-free and agent-friendly.
What can my agent do with Agent Analytics?
Your agent can track performance, run A/B experiments, analyze funnels, and report back to you.
How does my agent communicate with Agent Analytics?
It communicates via HTTP or the MCP (Model Context Protocol).
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