LogBrew

Name: LogBrew
Author: LogBrewCo

by LogBrewCoversion 0.4.0i★ –iRuns in the cloud

Registry nameco.logbrew/mcp

Install

Overview

Description from the maker (original English)

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

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs in the cloud
Transport: Streamable HTTP
Category: Marketing & social media

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on the maker’s server: what you ask it goes through their server.
The registry lists no key to fill in.

You need

Runs in the cloudNothing to install; it connects over the internet

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Works in Claude on the web, desktop and mobile:

Open Settings → Connectors
Press Add custom connector
Paste the address below and press Add
If it asks you to sign in, sign in with the maker

https://mcp.logbrew.co/mcp

Run this in your terminal

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

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

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

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

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

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

ChatGPT connects only to servers on the internet:

Open ChatGPT on the web → Settings → Connectors (Apps)
Press Create or Add (some plans need Developer mode under Advanced first)
Paste the address below, give it a name and save
If it asks you to sign in, sign in with the maker

https://mcp.logbrew.co/mcp

Menu names can differ slightly by plan and over time.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

We have not read this server’s tool list yet; we check endpoints in rotation.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 6, 2026

✓ Pass
Maker matches the repo
The registry name was verified against the domain logbrew.co (the registry checks domain ownership)
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
… Not checked yet
Endpoint responds
Not checked yet; we check endpoints in rotation
… Not checked yet
Sign-in with OAuth
Not checked yet; we check endpoints in rotation
… Not checked yet
No hidden instructions in tool descriptions
Not checked yet; we read the tool list when we check the endpoint

Compared with others in Marketing & social mediai

More stars than 0% of the other 2957 servers in this category
Published to the registry more recently than 83% of the other 2957 servers in this category
Basic checks equal to or better than 100% of the other 2957 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is LogBrew safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs in the maker’s cloud. Connect over the internet with nothing to install, but what you send passes through the maker’s servers.

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.4.0) reached the registry 7 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. It connects by URL, so apps that accept remote MCP servers work too, such as ChatGPT in developer mode.

What can I use instead?

In the same category: MCP YouTube Transcript, Google Analytics MCP, BibiGPT YouTube Video Summarizer

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

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AI video summarizer: summarize and transcribe YouTube, Bilibili, TikTok and podcast videos.

Runs in the cloud★ 137MITUpdated 9 days ago

Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

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:

Tool	What it does
`search`	Finds operations and returns the contract of one operation: its input and output schemas, permission, cost, safety and stability.
`execute`	Runs 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

Operation	What it reads
`issues.investigate.v16`	The `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.v17`	The `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.v15`	The `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.v14`	One 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.v13`	The `issues.investigate.v14` result without typed breadcrumb `data`.
`logs.investigate.v1`	One log, its captured context and bounded related evidence.
`traces.investigate.v3`	One trace, its failure evidence and cross-signal links.
`spans.investigate.v1`	One exact span and its diagnostic evidence.
`actions.investigate.v1`	One recorded product action and its related evidence. This does not perform the action.
`metrics.investigate.v2`	A metric's meaning, captured description and linked evidence.
`releases.investigate.v5`	One release, deployment comparisons and captured release markers.

Ownership and activity

Operation	What it reads
`issues.owners.v2`	The `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.v1`	Suggested 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.v1`	One 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.v2`	The `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.v3`	The `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.v1`	A 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

Operation	What it reads
`projects.list.v2`	The 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.v1`	Whether one project holds sample data, with the count of each sample signal: issue events, logs, trace spans and actions.
`issues.list.v1`	Grouped issues through bounded cursor pages.
`issues.list.v2`	Grouped 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.v3`	The `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.v4`	The `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.v5`	The `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.v7`	The `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.v1`	Logs through bounded cursor pages.
`traces.list.v1`	Traces with naming-quality coverage and cursor pagination.
`actions.list.v1`	Recorded product actions through bounded cursor pages.

| `met

Only the beginning is shown; read the rest in the repo

LogBrew

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Marketing & social mediai

Common questions

Alternatives

MCP YouTube Transcript

Google Analytics MCP

BibiGPT YouTube Video Summarizer

README from the maker

LogBrew MCP

What an agent can do

Supported clients

Operation reference

Investigations

Ownership and activity

Lists