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Logfire-MCP 分析追踪器

一种模型上下文协议服务器,使大型语言模型能够从 Logfire 检索和分析 OpenTelemetry 的痕迹和指标,支持异常跟踪以及针对遥测数据的自定义 SQL 查询。

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README

Logfire MCP Server

This repository contains a Model Context Protocol (MCP) server with tools that can access the OpenTelemetry traces and metrics you've sent to Logfire.

This MCP server enables LLMs to retrieve your application's telemetry data, analyze distributed traces, and make use of the results of arbitrary SQL queries executed using the Logfire APIs.

Available Tools

  • find_exceptions - Get exception counts from traces grouped by file

    • Required arguments:
      • age (int): Number of minutes to look back (e.g., 30 for last 30 minutes, max 7 days)
  • find_exceptions_in_file - Get detailed trace information about exceptions in a specific file

    • Required arguments:
      • filepath (string): Path to the file to analyze
      • age (int): Number of minutes to look back (max 7 days)
  • arbitrary_query - Run custom SQL queries on your OpenTelemetry traces and metrics

    • Required arguments:
      • query (string): SQL query to execute
      • age (int): Number of minutes to look back (max 7 days)
  • get_logfire_records_schema - Get the OpenTelemetry schema to help with custom queries

    • No required arguments

Setup

Install uv

The first thing to do is make sure uv is installed, as uv is used to run the MCP server.

For installation instructions, see the uv installation docs.

If you already have an older version of uv installed, you might need to update it with uv self update.

Obtain a Logfire read token

In order to make requests to the Logfire APIs, the Logfire MCP server requires a "read token".

You can create one under the "Read Tokens" section of your project settings in Logfire: https://logfire.pydantic.dev/-/redirect/latest-project/settings/read-tokens

[!IMPORTANT] Logfire read tokens are project-specific, so you need to create one for the specific project you want to expose to the Logfire MCP server.

Manually run the server

Once you have uv installed and have a Logfire read token, you can manually run the MCP server using uvx (which is provided by uv).

You can specify your read token using the LOGFIRE_READ_TOKEN environment variable:

LOGFIRE_READ_TOKEN=YOUR_READ_TOKEN uvx logfire-mcp

or using the --read-token flag:

uvx logfire-mcp --read-token=YOUR_READ_TOKEN

[!NOTE]
If you are using Cursor, Claude Desktop, Cline, or other MCP clients that manage your MCP servers for you, you do NOT need to manually run the server yourself. The next section will show you how to configure these clients to make use of the Logfire MCP server.

Configuration with well-known MCP clients

Configure for Cursor

Create a .cursor/mcp.json file in your project root:

{
  "mcpServers": {
    "logfire": {
      "command": "uvx",
      "args": ["logfire-mcp", "--read-token=YOUR-TOKEN"]
    }
  }
}

The Cursor doesn't accept the env field, so you need to use the --read-token flag instead.

Configure for Claude Desktop

Add to your Claude settings:

{
  "command": ["uvx"],
  "args": ["logfire-mcp"],
  "type": "stdio",
  "env": {
    "LOGFIRE_READ_TOKEN": "YOUR_TOKEN"
  }
}

Configure for Cline

Add to your Cline settings in cline_mcp_settings.json:

{
  "mcpServers": {
    "logfire": {
      "command": "uvx",
      "args": ["logfire-mcp"],
      "env": {
        "LOGFIRE_READ_TOKEN": "YOUR_TOKEN"
      },
      "disabled": false,
      "autoApprove": []
    }
  }
}

Customization - Base URL

By default, the server connects to the Logfire API at https://logfire-api.pydantic.dev. You can override this by:

  1. Using the --base-url argument:
uvx logfire-mcp --base-url=https://your-logfire-instance.com
  1. Setting the environment variable:
LOGFIRE_BASE_URL=https://your-logfire-instance.com uvx logfire-mcp

Example Interactions

  1. Find all exceptions in traces from the last hour:
{
  "name": "find_exceptions",
  "arguments": {
    "age": 60
  }
}

Response:

[
  {
    "filepath": "app/api.py",
    "count": 12
  },
  {
    "filepath": "app/models.py",
    "count": 5
  }
]
  1. Get details about exceptions from traces in a specific file:
{
  "name": "find_exceptions_in_file",
  "arguments": {
    "filepath": "app/api.py",
    "age": 1440
  }
}

Response:

[
  {
    "created_at": "2024-03-20T10:30:00Z",
    "message": "Failed to process request",
    "exception_type": "ValueError",
    "exception_message": "Invalid input format",
    "function_name": "process_request",
    "line_number": "42",
    "attributes": {
      "service.name": "api-service",
      "code.filepath": "app/api.py"
    },
    "trace_id": "1234567890abcdef"
  }
]
  1. Run a custom query on traces:
{
  "name": "arbitrary_query",
  "arguments": {
    "query": "SELECT trace_id, message, created_at, attributes->>'service.name' as service FROM records WHERE severity_text = 'ERROR' ORDER BY created_at DESC LIMIT 10",
    "age": 1440
  }
}

Examples of Questions for Claude

  1. "What exceptions occurred in traces from the last hour across all services?"
  2. "Show me the recent errors in the file 'app/api.py' with their trace context"
  3. "How many errors were there in the last 24 hours per service?"
  4. "What are the most common exception types in my traces, grouped by service name?"
  5. "Get me the OpenTelemetry schema for traces and metrics"
  6. "Find all errors from yesterday and show their trace contexts"

Getting Started

  1. First, obtain a Logfire read token from: https://logfire.pydantic.dev/-/redirect/latest-project/settings/read-tokens

  2. Run the MCP server:

    uvx logfire-mcp --read-token=YOUR_TOKEN
    
  3. Configure your preferred client (Cursor, Claude Desktop, or Cline) using the configuration examples above

  4. Start using the MCP server to analyze your OpenTelemetry traces and metrics!

Contributing

We welcome contributions to help improve the Logfire MCP server. Whether you want to add new trace analysis tools, enhance metrics querying functionality, or improve documentation, your input is valuable.

For examples of other MCP servers and implementation patterns, see the Model Context Protocol servers repository.

License

Logfire MCP is licensed under the MIT License. This means you are free to use, modify, and distribute the software, subject to the terms and conditions of the MIT License.

help

运行方式说明

cloud

托管运行

托管运行通常表示这个 MCP Server 由服务方环境承载,用户一般按页面提供的连接方式或授权流程接入,不需要在本地长期启动一个 MCP 进程

  1. 打开服务方连接页
  2. 完成授权或复制端点
  3. 在 MCP 客户端中连接
terminal

本地运行 / 其它方式

本地运行通常需要用户在自己的电脑或服务器上安装依赖,把 server_config 复制到 MCP 客户端,并按 env_schema 补齐环境变量、密钥或其它配置

  1. 复制 server_config
  2. 安装所需依赖
  3. 补齐环境变量后重启客户端