原型 · 预览版:收录官方注册中心里的全部服务器,每 30 分钟同步一次。评价和账户功能将在后续阶段推出。
PopNx MCP为使用 AI 的人准备的 MCP 服务器 · 用大白话讲清楚

LogBrew

作者:LogBrewCo版本 0.4.0i★ –i在云端运行
注册名称co.logbrew/mcp

安装

概览

作者提供的说明(英文原文)

Read LogBrew errors, slow traces, logs, and product analytics, and triage issues with consent.

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

  • 连接方式: 在云端运行
  • 传输方式: Streamable HTTP
  • 分类: 营销与社交媒体

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

你需要

你用的是哪个应用?

在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。

适用于网页版、桌面版和手机版 Claude:

  1. 打开 Settings → Connectors
  2. 点击 Add custom connector
  3. 粘贴下面的地址,然后点击 Add
  4. 如果要求登录,请登录作者的服务
SettingsConnectors1+ Add2https://…3
https://mcp.logbrew.co/mcp

在终端中运行这条命令

claude mcp add --transport http logbrew https://mcp.logbrew.co/mcp

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "logbrew": {
      "url": "https://mcp.logbrew.co/mcp"
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "logbrew": {
      "type": "http",
      "url": "https://mcp.logbrew.co/mcp"
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

ChatGPT 只能连接互联网上的服务器:

  1. 打开网页版 ChatGPT → Settings → Connectors (Apps)
  2. 点击 Create 或 Add(部分套餐需要先在 Advanced 中开启 Developer mode)
  3. 粘贴下面的地址,起个名字,然后保存
  4. 如果要求登录,请登录作者的服务
SettingsConnectors1+ Create2https://…3
https://mcp.logbrew.co/mcp

菜单名称可能因套餐和版本不同而略有差异。

你的选择通过 Cookie 保存在这台设备上,无需账户。

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。

它能做什么

我们还没有读取这个服务器的工具列表;我们会轮流检查各个端点。

基础检查i

我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月6日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过域名 logbrew.co 验证(注册中心会核实域名所有权)

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    端点有响应

    尚未检查;我们会轮流检查各个端点

  • … 尚未检查

    使用 OAuth 登录

    尚未检查;我们会轮流检查各个端点

  • … 尚未检查

    工具描述中没有隐藏指令

    尚未检查;我们会在检查端点时读取工具列表

与“营销与社交媒体”中的其他服务器比较i

  • 星标数多于此分类中其他 2961 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 2961 个服务器的 83% 更新
  • 基础检查结果等于或优于此分类中其他 2961 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。

常见问题

LogBrew 安全吗?

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。

它需要哪些密钥或代码?

注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。

它在我的电脑上运行还是在云端?

它在作者的云端运行。通过互联网连接,无需安装,但你发送的内容会经过作者的服务器。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(0.4.0)于7天前进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。它通过 URL 连接,所以接受远程 MCP 服务器的应用也可以使用,例如开启开发者模式的 ChatGPT。

有什么可以替代它?

同一分类中有:MCP YouTube Transcript, Google Analytics MCP, BibiGPT YouTube Video Summarizer

替代选择

同一分类中其他作者的服务器,按星标数排序。

如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

MCP YouTube Transcript

作者:jkawamoto

An MCP server retrieving transcripts of YouTube videos

在你的电脑上运行★ 495MIT9天前更新
安装

Google Analytics MCP

作者:surendranb

GA4 MCP server for AI agents: schema discovery, server-side aggregation, analysis-ready defaults.

在你的电脑上运行★ 244MIT9天前更新
安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

LogBrew MCP

The hosted LogBrew MCP server lets an AI agent read telemetry from your LogBrew projects and, if you allow it, triage issues and set up projects. You do not install it. Add its URL to your MCP client:

https://mcp.logbrew.co/mcp
  • Transport: Streamable HTTP. The server accepts MCP protocol versions 2026-07-28, 2025-11-25 and 2025-06-18.
  • Authorization: OAuth. Your client opens the LogBrew authorization page, you sign in, and you select the projects that the agent can read. The read scope lets the agent read. Operations that change data need the separate write scope, which you can decline when you approve the connection.
  • Changes: Without the write scope, the agent cannot change anything. With it, the agent can resolve, reopen, archive, prioritize and assign issues, and create projects and project keys, acting as you and within your permissions. Archiving an issue and revoking a key take a second, confirming call. The agent cannot change billing, members or account settings. A call on a project that you did not approve returns permission_denied.
  • Connection lifetime: An access token is valid for 1 hour, and the client refreshes it while you use the connection. A connection ends after 30 days without use, or 90 days after you approved it. Revoke a connection in the LogBrew dashboard under Settings > MCP connections, or with logbrew mcp revoke.

What an agent can do

The server has 2 tools. search is annotated read-only. execute is annotated as able to change data, because the catalog has write operations:

ToolWhat it does
searchFinds operations and returns the contract of one operation: its input and output schemas, permission, cost, safety and stability.
executeRuns one operation that search found and returns structured data, or an error with a stable code and a next action.

The operations read issues (investigation, lists, activity, owners and ownership rules), logs, traces, spans, metrics, product actions, releases, signal volume and product analytics. With the write scope, operations also resolve, reopen, archive, prioritize, assign and unassign issues, create projects, create and revoke project keys, send a test event, and load and remove sample data. The operation reference lists every operation in the shipped catalog and its limits.

Supported clients

Any MCP client that completes LogBrew authorization can connect. The client can publish a client ID metadata document or register dynamically.

Connect an AI agent with MCP shows the setup for many clients. For example, in Claude Code:

claude mcp add --transport http logbrew https://mcp.logbrew.co/mcp

claude mcp login logbrew

Operation reference

This reference describes the operation catalog shipped in catalog/operations.json, which the hosted server at https://mcp.logbrew.co/mcp loads. Most operations read. A connection with the write scope can also triage issues, create projects and project keys, send a test event, and load or remove sample data (see Changes). The catalog has no operations for billing, organization members, account settings, or deleting a project.

The server exposes two tools. search finds versioned operations and returns their input and output schemas. execute runs a selected operation. Every operation works only on the projects the signed-in user approved, and on projects created through the same connection. Discovery does not grant permission or establish that data is available for a particular account.

Each operation's info.permission names the delegated scope it needs: read, or write for an operation that changes data. A write operation also has safety: write, a title, and hints with the MCP tool annotation names readOnlyHint, destructiveHint, and idempotentHint. When the catalog holds a write operation, the execute tool declares readOnlyHint: false, and destructiveHint: true if any operation may delete or overwrite data. The authorization server checks the scope again on every call.

Use the returned schema for required fields, valid versions, filters, limits and pagination. Do not substitute CLI flags for JSON fields. Omit an optional field rather than sending null. Preserve the selected project and filters when following a cursor. Related evidence may be missing, unavailable or truncated; none of those states means zero events.

Investigations
OperationWhat it reads
issues.investigate.v16The issues.investigate.v15 result, where correlations.related_issues lists other issues from the same project, environment and release, one per issue, oldest first, up to 20. An issue is listed when it is unresolved and its first in-app frame has the same module, function and file, or when it occurred on the same trace within 5 minutes. Each item has basis (first_in_app_frame, same_trace), occurrence_count, first_seen_at and last_seen_at in that environment and release.
issues.investigate.v17The issues.investigate.v16 result plus two fields. source_locator.frame_links links each in-app frame whose captured path proves its repository file to that file and line at the deployed commit (frame_index, repository_relative_file, line, url). suspect_commits names the deploy where the issue first appeared or regressed (deployment_id, head_revision), the previous deploy of another release (base_revision), and up to 10 ranked commits in that range that changed a file in the issue's in-app frames (rank, sha, url, title, author_name, committed_at, files). The frame nearest the crash ranks first, then more matched files, then the newest commit. status and evidence.missing_fields say what is missing, such as repository contents access (suspect_commits.authorization) or a deploy without a commit SHA (suspect_commits.deployment.commit_sha). Suspect commits are read from GitHub.
issues.investigate.v15The issues.investigate.v14 result, with an archived issue reading archived instead of ignored in subject.status, the lifecycle's persisted and effective status, and each status change.
issues.investigate.v14One issue and its selected occurrence, reproduction, lifecycle, grouping and correction evidence. Each breadcrumb has data with method, url (no query or fragment) and status_code for an HTTP call, from and to for a route change, and logger for a log record; a field the breadcrumb does not have is null.
issues.investigate.v13The issues.investigate.v14 result without typed breadcrumb data.
logs.investigate.v1One log, its captured context and bounded related evidence.
traces.investigate.v3One trace, its failure evidence and cross-signal links.
spans.investigate.v1One exact span and its diagnostic evidence.
actions.investigate.v1One recorded product action and its related evidence. This does not perform the action.
metrics.investigate.v2A metric's meaning, captured description and linked evidence.
releases.investigate.v5One release, deployment comparisons and captured release markers.
Ownership and activity
OperationWhat it reads
issues.owners.v2The issues.owners.v1 result with teams: each owner has type user or team, and a team owner has team_id, slug and name. Ownership rules name a team as #slug; a CODEOWNERS @org/slug names the team with that slug.
issues.owners.v1Suggested owners of one issue, best first: matching ownership rules, then matching CODEOWNERS lines, then people who recently changed or were assigned the issue. Each owner names the rule, its line and what it matched. inputs counts the frame paths, modules, route template, tags and rules that were checked.
issues.activity.v1One issue's history, newest first: status, priority, assignee and severity rule changes, each with the account that made it, ending with when the issue was first seen. Follow next_cursor with cursor_time and cursor_id.
issues.activity.v2The issues.activity.v1 entries with team: the team of a team assignment, or null. An archive that ended by itself is a status entry with value unresolved and no account.
issues.activity.v3The issues.activity.v2 entries with archive on status entries: how an archive reopens (until is forever, escalating, time, events, or users, with reopen_at or count), and on an automatic reopen, the condition it met.
issues.ownership.v1A project's ownership rules and CODEOWNERS text, and the owners in them that name nobody with access to the project.

Owners and actors show a name and email only while that account can read the project. An account that lost access keeps only its ID in the activity and no longer appears as an owner. No owner means no rule matched the captured evidence; check inputs before you conclude that nobody owns the code.

An investigation may help locate a cause, but correlation alone does not prove one. Keep captured evidence separate from an inferred cause or a proposed fix. An absent description or source location remains absent. A later SDK upgrade does not backfill historical events.

Lists
OperationWhat it reads
projects.list.v2The projects this connection can read: each project's ID, name, creation time, setup status, last release and environment, and the signed-in user's access. It takes no input and returns every approved project in one response. Use it to find the project_id that other operations take.
projects.sample_data.v1Whether one project holds sample data, with the count of each sample signal: issue events, logs, trace spans and actions.
issues.list.v1Grouped issues through bounded cursor pages.
issues.list.v2Grouped issues with their priority (high, medium, low) and whether a user set it. Unless a user set it, the priority comes from how recent the issue is and how much it harms production. An issue someone archived reads as archived. Filter by status or priority.
issues.list.v3The issues.list.v2 fields plus each issue's assignee: user ID, name, and email, or null when nobody is assigned or the assignee can no longer read the project. Filter by assignee: me, none, or a user ID.
issues.list.v4The issues.list.v2 fields plus each issue's assignee: {type: user, user_id, name, email}, {type: team, team_id, slug, name}, or null. Filter by assignee: me, none, a user ID, team: , or my_teams.
issues.list.v5The issues.list.v4 fields plus archive on archived issues: until is forever, escalating, time, events, or users; reopen_at is the reopen time; count is the number of new events or users, or the events in 1 hour that count as escalating. Other issues have archive: null.
issues.list.v7The issues.list.v5 fields plus resolution on issues resolved in a release, user_impact and evidence on every issue. user_impact has status (complete, partial, not_captured, or unavailable), known_affected_users, count_method, coverage, and limitations, the same as impact.user_impact in issues.investigate.v17. evidence lists the fields of the latest occurrence that were captured, missing, redacted, or truncated, in the field names of the investigation's evidence. Each issue's next_action is investigate_issue; run issues.investigate.v17 for its ordered trace, logs, and breadcrumbs.
logs.list.v1Logs through bounded cursor pages.
traces.list.v1Traces with naming-quality coverage and cursor pagination.
actions.list.v1Recorded product actions through bounded cursor pages.

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只显示了开头部分;其余内容请在仓库中阅读

问 PopNx