AI Skill Hub 强烈推荐:Sentry错误监控MCP服务 是一款优质的MCP工具。AI 综合评分 8.2 分,在同类工具中表现稳健。如果你正在寻找可靠的MCP工具解决方案,这是一个值得深入了解的选择。
为大型语言模型提供Sentry错误监控平台的集成接口。支持查询错误日志、分析应用崩溃、获取性能指标等功能。适合DevOps工程师、应用开发者和AI系统集成者使用,助力智能化错误诊断与故障排查。
Sentry错误监控MCP服务 是一款遵循 MCP(Model Context Protocol)标准协议的 AI 工具扩展。通过 MCP 协议,它可以让 Claude、Cursor 等主流 AI 客户端直接访问和操作外部工具、数据源和服务,实现 AI 能力的无缝扩展。无论是文件操作、数据库查询还是 API 调用,都可以通过自然语言在 AI 对话中直接触发,极大提升生产效率。
为大型语言模型提供Sentry错误监控平台的集成接口。支持查询错误日志、分析应用崩溃、获取性能指标等功能。适合DevOps工程师、应用开发者和AI系统集成者使用,助力智能化错误诊断与故障排查。
Sentry错误监控MCP服务 是一款遵循 MCP(Model Context Protocol)标准协议的 AI 工具扩展。通过 MCP 协议,它可以让 Claude、Cursor 等主流 AI 客户端直接访问和操作外部工具、数据源和服务,实现 AI 能力的无缝扩展。无论是文件操作、数据库查询还是 API 调用,都可以通过自然语言在 AI 对话中直接触发,极大提升生产效率。
# 方式一:通过 Claude Code CLI 一键安装
claude skill install https://github.com/getsentry/sentry-mcp
# 方式二:手动配置 claude_desktop_config.json
{
"mcpServers": {
"sentry----mcp--": {
"command": "npx",
"args": ["-y", "sentry-mcp"]
}
}
}
# 配置文件位置
# macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
# Windows: %APPDATA%/Claude/claude_desktop_config.json
# 安装后在 Claude 对话中直接使用 # 示例: 用户: 请帮我用 Sentry错误监控MCP服务 执行以下任务... Claude: [自动调用 Sentry错误监控MCP服务 MCP 工具处理请求] # 查看可用工具列表 # 在 Claude 中输入:"列出所有可用的 MCP 工具"
// claude_desktop_config.json 配置示例
{
"mcpServers": {
"sentry____mcp__": {
"command": "npx",
"args": ["-y", "sentry-mcp"],
"env": {
// "API_KEY": "your-api-key-here"
}
}
}
}
// 保存后重启 Claude Desktop 生效
Sentry's MCP service is primarily designed for human-in-the-loop coding agents. Our tool selection and priorities are focused on developer workflows and debugging use cases, rather than providing a general-purpose MCP server for all Sentry functionality.
This remote MCP server acts as middleware to the upstream Sentry API, optimized for coding assistants like Cursor, Claude Code, and similar development tools. It's based on Cloudflare's work towards remote MCPs.
EMBEDDED_AGENT_PROVIDER= # Required: 'openai' or 'anthropic' OPENAI_API_KEY= # Required if using OpenAI ANTHROPIC_API_KEY= # Required if using Anthropic
pnpm -w run cli --access-token=TOKEN "query" ```
Note: The CLI defaults to http://localhost:5173. Override with --mcp-host or set MCP_URL environment variable.
Comprehensive testing playbooks: - Stdio testing: See docs/testing-stdio.md for complete guide on building, running, and testing the stdio implementation (IDEs, MCP Inspector) - Remote testing: See docs/testing-remote.md for complete guide on testing the remote server (OAuth, web UI, CLI client)
You'll find everything you need to know by visiting the deployed service in production:
<https://mcp.sentry.dev>
If you're looking to contribute, learn how it works, or to run this for self-hosted Sentry, continue below.
SENTRY_HOST= # For self-hosted deployments MCP_DISABLE_SKILLS= # Disable specific skills (comma-separated, e.g. 'seer')
**Important:** Always set `EMBEDDED_AGENT_PROVIDER` to explicitly specify your LLM provider. Auto-detection based on API keys alone is deprecated and will be removed in a future release. See [docs/embedded-agents.md](docs/embedded-agents.md) for detailed configuration options.
#### Example MCP Configuration
json { "mcpServers": { "sentry": { "command": "npx", "args": ["@sentry/mcp-server"], "env": { "SENTRY_ACCESS_TOKEN": "your-token", "EMBEDDED_AGENT_PROVIDER": "openai", "OPENAI_API_KEY": "sk-..." } } } }
If you leave the host variable unset, the CLI automatically targets the Sentry
SaaS service. Only set the override when you operate self-hosted Sentry.
For self-hosted instances that don't support Seer:
json { "mcpServers": { "sentry": { "command": "npx", "args": ["@sentry/mcp-server"], "env": { "SENTRY_ACCESS_TOKEN": "your-token", "SENTRY_HOST": "sentry.example.com", "MCP_DISABLE_SKILLS": "seer" } } } } ```
OPENAI_API_KEY= # Also required for AI-powered search tools in production
Note: The root `.env` file provides defaults for all packages. Individual packages can have their own `.env` files to override these defaults during development.
Once that's done you can run them using:
shell pnpm eval
**Manual testing** (preferred for testing MCP changes):
shell
Install as a Claude Code plugin for automatic subagent delegation:
claude plugin marketplace add getsentry/sentry-mcp
claude plugin install sentry-mcp@sentry-mcp
This provides a sentry-mcp subagent that Claude automatically delegates to when you ask about Sentry errors, issues, traces, or performance.
For forward-looking tool variants and features:
claude plugin install sentry-mcp@sentry-mcp-experimental
While this repository is focused on acting as an MCP service, we also support a stdio transport. This is still a work in progress, but is the easiest way to adapt run the MCP against a self-hosted Sentry install.
Note: The AI-powered search tools (search_events, search_issues, etc.) require an LLM provider (OpenAI or Anthropic). These tools use natural language processing to translate queries into Sentry's query syntax. Without a configured provider, these specific tools will be unavailable, but all other tools will function normally.
To utilize the stdio transport, you'll need to create an User Auth Token in Sentry with the necessary scopes. As of writing this is:
org:read
project:read
project:write
team:read
team:write
event:write
Launch the transport:
npx @sentry/mcp-server@latest --access-token=sentry-user-token
Need to connect to a self-hosted deployment? Add <code>--host</code> (hostname only, e.g. <code>--host=sentry.example.com</code>) when you run the command. For isolated internal deployments that only expose plain HTTP, also add <code>--insecure-http</code>.
Some features (like Seer) may not be available on self-hosted instances. You can disable specific skills to prevent unsupported tools from being exposed:
npx @sentry/mcp-server@latest --access-token=TOKEN --host=sentry.example.com --disable-skills=seer
For self-hosted instances without TLS:
npx @sentry/mcp-server@latest --access-token=TOKEN --host=sentry.internal:9000 --insecure-http
```shell SENTRY_ACCESS_TOKEN= # Required: Your Sentry auth token
优质MCP工具,为LLM提供生产级错误监控能力。代码成熟度高,TypeScript编写,与Sentry深度集成,实用价值突出。
该工具使用 NOASSERTION 协议,商用场景请仔细阅读协议条款,必要时咨询法律意见。
AI Skill Hub 为第三方内容聚合平台,本页面信息基于公开数据整理,不对工具功能和质量作任何法律背书。
建议在沙箱或测试环境中充分验证后,再部署至生产环境,并做好必要的安全评估。
📄 NOASSERTION — 请查阅原始协议条款了解具体使用限制。
总体来看,Sentry错误监控MCP服务 是一款质量优秀的MCP工具,在同类工具中具备一定竞争力。AI Skill Hub 将持续追踪其更新动态,建议收藏备用,结合自身场景选择合适时机引入使用。
| 原始名称 | sentry-mcp |
| 原始描述 | 开源MCP工具:An MCP server for interacting with Sentry via LLMs.。⭐697 · TypeScript |
| Topics | 错误监控MCP服务器Sentry集成生产工具LLM应用 |
| GitHub | https://github.com/getsentry/sentry-mcp |
| License | NOASSERTION |
| 语言 | TypeScript |
收录时间:2026-05-21 · 更新时间:2026-05-22 · License:NOASSERTION · AI Skill Hub 不对第三方内容的准确性作法律背书。
选择 Agent 类型,复制安装指令后粘贴到对应客户端