プロトタイプ · プレビュー版:公式レジストリのすべてのサーバーを掲載し、30分ごとに同期しています。レビューとアカウント機能は今後のステップで始まります。
PopNx MCPAIを使う人のためのMCPサーバー · やさしい言葉で解説

LogBrew

作者:LogBrewCoバージョン 0.4.0i★ –iクラウドで動く
レジストリ名co.logbrew/mcp

インストール

概要

作者による説明(英語の原文)

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

PopNx MCPの3つの柱

この3つを1つのスコアにまとめることはしません。意見、測定、人気はそれぞれ別のものだからです。

できること

このサーバーのやさしい解説はまだ書いていません。以下はレジストリから読み取った事実です。

  • 接続方法: クラウドで動く
  • トランスポート: Streamable HTTP
  • カテゴリ: マーケティング・SNS

インストール

使っているAIアプリを選んで、設定をコピーしてください。

インストールの前に

  • 基本チェック:1項目中1項目に合格
  • 作者のサーバーで動きます。あなたが頼んだ内容は、作者のサーバーを通ります。
  • レジストリには、入力が必要なキーは載っていません。

必要なもの

どのアプリを使っていますか?

上でアプリを選んでください。選んだアプリを覚えておくので、次からはボタンに「…にインストール」と表示されます。

ウェブ、デスクトップ、モバイルのClaudeで使えます:

  1. Settings → Connectors を開く
  2. Add custom connector を押す
  3. 下のアドレスを貼り付けて Add を押す
  4. サインインを求められたら、作者のサービスにサインインする
SettingsConnectors1+ Add2https://…3
https://mcp.logbrew.co/mcp

ターミナルでこれを実行します

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

Cursorで開く

または、設定を自分でコピーする

プロジェクトの .cursor/mcp.json、または ~/.cursor/mcp.json に貼り付けます

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

ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。

VS Codeで開く

または、設定を自分でコピーする

プロジェクトの .vscode/mcp.json に貼り付けます

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

ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。

ChatGPTがつなげるのは、インターネット上のサーバーだけです:

  1. ウェブ版のChatGPTを開き → Settings → Connectors (Apps)
  2. Create または Add を押す(プランによっては、先に Advanced で Developer mode をオンにする必要があります)
  3. 下のアドレスを貼り付け、名前を付けて保存する
  4. サインインを求められたら、作者のサービスにサインインする
SettingsConnectors1+ Create2https://…3
https://mcp.logbrew.co/mcp

メニューの名前は、プランや時期によって少し違うことがあります。

選んだアプリは、この端末のCookieに保存されます。アカウントは不要です。

この設定は、作者のレジストリ登録情報から作成しています。READMEと違う場合は、READMEに従ってください。

できること

このサーバーのツール一覧はまだ読み取っていません。エンドポイントは順番にチェックしています。

基本チェックi

誰でも見られる情報をチェックしており、コードは読んでいません。当てはまらない項目は数に入れていません。 · 2026年11月6日にチェック

  • ✓ 合格

    作者とリポジトリが一致

    レジストリ名はドメイン logbrew.co で確認済みです(レジストリがドメインの所有を確認しています)

  • … 未チェック

    今もメンテナンスされている

    このリポジトリはまだGitHubから読み取っていません

  • … 未チェック

    ライセンスがある

    このリポジトリはまだGitHubから読み取っていません

  • … 未チェック

    エンドポイントが応答する

    まだチェックしていません。エンドポイントは順番にチェックしています

  • … 未チェック

    OAuthでサインイン

    まだチェックしていません。エンドポイントは順番にチェックしています

  • … 未チェック

    ツールの説明に隠れた指示がない

    まだチェックしていません。エンドポイントをチェックするときにツール一覧を読み取ります

マーケティング・SNSのほかのサーバーとの比較i

  • このカテゴリのほかの2956件のうち0%よりスターが多い
  • このカテゴリのほかの2956件のうち83%より最近レジストリに公開
  • 基本チェックの結果が、このカテゴリのほかの2956件のうち100%と同じかそれ以上

レジストリでこのカテゴリにある有効なすべてのサーバーと比較しています。スターは、公開者がリポジトリの所有者である場合だけ数えます。

よくある質問

LogBrewは安全ですか?

当てはまる基本チェック1項目のうち1項目に合格しました。コードは読んでいません。キーやトークンを追加する前に、サーバーがどんなアクセスを求めているかを確認し、必要な権限だけを持つキーを使ってください。

どんなキーやコードが必要ですか?

レジストリには必須のキーは載っていません。ただし、最初に使うときにサインインを求めるサーバーもあります。

パソコンで動きますか、それともクラウドですか?

作者のクラウドで動きます。インストール不要でインターネット経由でつながりますが、送った内容は作者のサーバーを通ります。

今もメンテナンスされていますか?

GitHubリポジトリの最終更新は–、最新バージョン(0.4.0)がレジストリに届いたのは6 日前です。

どのアプリで使えますか?

Claude Desktop、Claude Code、Cursor、VS CodeなどのMCP対応アプリで使えます。URLでつながるので、リモートMCPサーバーに対応したアプリ(開発者モードのChatGPTなど)でも使えます。

代わりに使えるものは?

同じカテゴリには:MCP YouTube Transcript, Google Analytics MCP, BibiGPT YouTube Video Summarizer

代わりの候補

同じカテゴリで、ほかの作者が作ったサーバー。スターの多い順。

カードの見方:★ GitHubスターi3つの柱:レビュー · チェック · 利用状況i更新=最新バージョンをレジストリに公開した日i

Google Analytics MCP

作者:surendranb

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

パソコンで動く★ 244MIT9 日前更新
インストール

作者のREADME

READMEを開く

作者のリポジトリから書かれたとおりにコピーしたものです。PopNx MCPは内容を確認・推奨していません。HTML、画像、スクリプトは取り除いています。リンクはこのサイトの外へ移動します。

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.

| `met

冒頭だけを表示しています。続きはリポジトリで読めます

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