cursor-otel
An MCP server that instruments Cursor AI agent interactions with OpenTelemetry traces and logs to monitor agent turns and performance. It enables tracking of user queries, assistant responses, and tool usage through GenAI-compliant telemetry spans.
README
cursor-otel
An MCP server that instruments Cursor AI agent interactions with OpenTelemetry traces and logs.
Each agent turn becomes an OTel span following the GenAI semantic conventions, with the user query and assistant response captured as span attributes. Logs emitted during a turn are correlated to the trace via context propagation.
Disclaimer
This is an experimental personal project. It is not affiliated with, endorsed by, or supported by Elastic, Cursor, or the OpenTelemetry project. Use at your own risk.
Tools
| Tool | Description |
|---|---|
start_turn |
Begin a traced span for an agent turn. Returns a turn_id and conversation_id. |
end_turn |
End the span for a turn. Accepts a response summary, tool count, and optional error. |
agent_log |
Emit an OTel log record, optionally correlated to an active turn's trace. |
Setup
Prerequisites
An OpenTelemetry collector (or compatible backend) accepting OTLP/HTTP on http://localhost:4318. Override with the OTEL_EXPORTER_OTLP_ENDPOINT environment variable.
Install
git clone https://github.com/smith/cursor-otel.git
cd cursor-otel
npm install
Configure Cursor
Add to your .cursor/mcp.json:
{
"mcpServers": {
"cursor-otel": {
"command": "node",
"args": ["/absolute/path/to/cursor-otel/index.mjs"]
}
}
}
Agent rules
Add a Cursor rule (e.g. .cursor/rules/cursor-otel.mdc) to instruct the agent to call the tools on every turn:
## Agent OTel instrumentation
Every user interaction MUST be traced. Use the `cursor-otel` MCP tools.
### On each user query
1. Call `start_turn` with:
- `conversation_id`: reuse the value from the previous `start_turn` response
in this conversation. Omit on the first call (the server generates one).
- `user_message`: the user's query (first 500 chars).
- `model`: the model name if you know it.
2. Save the returned `turn_id` and `conversation_id`.
### After completing your response
Call `end_turn` with:
- `turn_id`: from `start_turn`.
- `response`: 1-2 sentence summary of what you did.
- `tool_count`: total number of tool calls you made this turn.
- `error`: set only if the turn failed.
### Logs
Use `agent_log` (with the `turn_id`) for notable events: errors, key decisions,
warnings. Don't log routine steps.
### Rules
- `start_turn` and `end_turn` are **mandatory** on every turn. No exceptions.
- Keep `start_turn` as the **first** tool call and `end_turn` as the **last**.
- These calls are fast and non-blocking — don't skip them to save time.
License
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。