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Loggly MCP

by andrewbabuversion 1.3.0i★ –iRuns on your computer
Registry nameio.github.andrewbabu/loggly-mcp

Install

Overview

Description from the maker (original English)

Read-only Loggly search and analytics with aggregation-first traffic tools and IP intelligence.

PopNx MCP’s three pillars

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

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 on your computer
  • Transport: stdio
  • Category: Marketing & social media
  • You need to fill in: LOGGLY_SUBDOMAIN, LOGGLY_TOKEN

Install

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

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • You fill in yourself: LOGGLY_SUBDOMAIN, LOGGLY_TOKEN

Values marked secret are keys to your account. Never share them or paste them into a chat.

You need

  • npmNode.js installed (for the npx command)

Which app do you use?

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

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "loggly": {
      "command": "npx",
      "args": [
        "-y",
        "@andrewbabu/loggly-mcp"
      ],
      "env": {
        "LOGGLY_SUBDOMAIN": "your-value",
        "LOGGLY_TOKEN": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add loggly --env LOGGLY_SUBDOMAIN=your-value --env LOGGLY_TOKEN=your-value -- npx -y @andrewbabu/loggly-mcp

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

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

{
  "mcpServers": {
    "loggly": {
      "command": "npx",
      "args": [
        "-y",
        "@andrewbabu/loggly-mcp"
      ],
      "env": {
        "LOGGLY_SUBDOMAIN": "your-value",
        "LOGGLY_TOKEN": "your-value"
      }
    }
  }
}

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": {
    "loggly": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@andrewbabu/loggly-mcp"
      ],
      "env": {
        "LOGGLY_SUBDOMAIN": "your-value",
        "LOGGLY_TOKEN": "your-value"
      }
    }
  }
}

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.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

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

Values you fill in

  • LOGGLY_SUBDOMAIN required env
    Loggly account subdomain or full Loggly URL (e.g. your-subdomain or https://your-subdomain.loggly.com).
  • LOGGLY_TOKEN secret required env
    Loggly API token (read access).

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

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

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 9, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account andrewbabu, which owns the repo

  • … 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 applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Marketing & social mediai

  • More stars than 0% of the other 3632 servers in this category
  • Published to the registry more recently than 45% of the other 3632 servers in this category
  • Basic checks equal to or better than 100% of the other 3632 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 Loggly MCP 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?

You need to fill in: LOGGLY_SUBDOMAIN, LOGGLY_TOKEN

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (1.3.0) reached the registry 36 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.

What can I use instead?

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

Alternatives

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

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by surendranbGrowing↓ 1.1K/wk★ 244Updated 12 days ago

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BibiGPT YouTube Video Summarizer

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

by JimmyLvGrowing★ 137Updated 12 days ago

Runs in the cloud✓ bibigpt.co

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.

Loggly MCP

Read-only Model Context Protocol (MCP) server for Loggly /apiv2/* APIs, plus IP intelligence (RDAP, GreyNoise, AbuseIPDB). Exposes Loggly search/analytics/field tools, aggregation-first traffic tools, and IP-context tools, while blocking write endpoints.


Skill Usage

For efficient log retrieval (less token use) and summarization, pair this server with a skill.


Quickstart

Install from npm

LOGGLY_SUBDOMAIN=your-subdomain LOGGLY_TOKEN=your-token npx -y @andrewbabu/loggly-mcp

MCP client configuration:

{

"mcpServers": { "loggly": { "command": "npx", "args": ["-y", "@andrewbabu/loggly-mcp"], "env": { "LOGGLY_SUBDOMAIN": "your-subdomain", "LOGGLY_TOKEN": "your-token" } } } }

Run from source

git clone https://github.com/andrewbabu/loggly-mcp.git

cd loggly-mcp npm install cp .env.example .env

Edit .env with your Loggly credentials, then run:

npm start

Once the repo is trusted in Codex, the MCP server can also be started automatically via .codex/config.toml.


Configuration

The server loads .env from its working directory on startup.

Required

  • LOGGLY_SUBDOMAIN Loggly account subdomain or full Loggly URL (e.g. your-subdomain or https://your-subdomain.loggly.com)
  • LOGGLY_TOKEN Loggly API token

Optional

  • LOGGLY_AUTH_MODE bearer (default) or basic
  • LOGGLY_MAX_RETRIES Default: 2
  • LOGGLY_REQUEST_TIMEOUT_MS Default: 15000
  • LOGGLY_LOG_LEVEL error, warn, info (default), or debug

Remote (HTTP) Server

For a stdio server anyone on the team can reach from Claude Code without a local checkout, run the HTTP variant instead and host it on an internal server/VM.

cp .env.example .env

Edit .env with your Loggly credentials plus MCP_BEARER_TOKEN (generate one with node -e "console.log(require('crypto').randomBytes(32).toString('hex'))"), then:

npm run start:http

This starts a stateless Streamable HTTP MCP server on MCP_HTTP_PORT (default 8787):

  • GET /healthz — unauthenticated liveness check.
  • POST /mcp — the MCP endpoint. Requires Authorization: Bearer ; every other request to /mcp gets 401.

The Loggly credentials stay server-side — everyone connecting shares the same Loggly account access. MCP_BEARER_TOKEN only gates access to the MCP server itself, so treat it as a secret and rotate it if it leaks (e.g. re-generate and redistribute).

Only run this behind your internal network/VPN, not exposed directly to the public internet — there's a single shared token, not per-user auth.

Connecting from Claude Code

Each org member adds the remote server once:

claude mcp add --transport http loggly https://your-internal-host:8787/mcp \

--header "Authorization: Bearer "

Swap in the internal hostname/port you deployed to and the token you were given.

Running with Docker

docker build -t loggly-mcp .

docker run -d --name loggly-mcp -p 8787:8787 --env-file .env loggly-mcp


Multiple Accounts / Domains

The server can hold credentials for several Loggly accounts (different subdomains, different tokens) at once and target them per tool call.

Set LOGGLY_ACCOUNTS to a JSON object mapping an account name to its credentials:

LOGGLY_ACCOUNTS={"acme":{"subdomain":"acme","token":"acme_token","authMode":"bearer"},"beta":{"subdomain":"beta","token":"beta_token"}}

When LOGGLY_ACCOUNTS is set, it replaces LOGGLY_SUBDOMAIN/LOGGLY_TOKEN/LOGGLY_AUTH_MODE. Every tool then accepts an optional account argument (e.g. account: "acme") to pick which account's credentials to use for that call.

  • If account is omitted, the server uses LOGGLY_DEFAULT_ACCOUNT if set, otherwise "default", otherwise the single configured account if there's only one.
  • An unknown account value returns an error listing the configured account names.
  • iterate_events_next can also infer the account from the next_url host when account is omitted, as long as exactly one configured account matches that host.

Existing single-account setups (just LOGGLY_SUBDOMAIN/LOGGLY_TOKEN) keep working unchanged — they're treated as one account named "default".


Aggregation-First Traffic Tools

Raw event dumps are slow and expensive to reason about. These tools return a summary — totals, top-N breakdowns, a bucketed timeline, and a small representative sample — instead:

  • search_logs — the general-purpose version: query + time range in, aggregated summary out.
  • traffic_by_ip / traffic_by_host / traffic_by_path — same aggregation, pre-scoped to one IP/hostname/path.
  • group_by_ip / group_by_path / group_by_user_agent — facet counts only (thin wrappers over field_facets), for when you just need a breakdown, not the full aggregate.
  • timeline — bucketed counts over a range, computed client-side via repeated /apiv2/events/count calls (Loggly's volume-metrics endpoint doesn't accept a free-text query, so this is the only way to get a timeline for an arbitrary search).
  • sample_events — a handful of representative raw events, when you need examples rather than the complete result set.

Field naming depends on how each Loggly source parses its logs, and can differ between accounts and even between tags within one account — so these tools resolve field names discovery-first: for any role not explicitly overridden (host_field/path_field/status_field/user_agent_field/ ip_field arguments, or the LOGGLY_FIELD_HOST/_PATH/_STATUS/_USER_AGENT/_IP env vars), they check /apiv2/fields/ for the actual query and match candidates against known role patterns:

  • Exactly one match → used automatically, reported under discovered_fields in the result.
  • Multiple plausible matches (e.g. a source with both ClientIp and CustIP) → never guessed between — reported under ambiguous_fields instead, falling back to the configured default. Pass the correct one explicitly via the matching *_field argument.
  • No match → falls back to the configured default (host, path, status, user_agent, ip).

Run list_fields yourself if you want to see every candidate before deciding on an override.


IP Intelligence

  • rdap_lookup — IP ownership/network registration (RIR, netblock, org, country) via public RDAP (rdap.org). No API key required.
  • ip_reputation — GreyNoise (internet-wide scanning noise) + AbuseIPDB (community abuse reports) for an IP. Requires GREYNOISE_API_KEY / ABUSEIPDB_API_KEY; either one missing just comes back as available: false for that source, not an error.
  • get_ip_context — combines all of the above with Loggly traffic (1h/24h/30d counts, first/last seen, hosts, top paths) checked across every configured Loggly account unless account is given, and flags cross_domain_correlation when the IP shows activity in more than one account. Per the bot-traffic-triage playbook, that cross-domain pattern is the single strongest signal for distinguishing targeted reconnaissance from background noise.

Treat all IP-intel output as one input among several — identity/reputation data (who owns an IP, third-party scanner reports) should carry less weight than behavioral evidence from your own logs. See the bot-traffic-triage skill for the full investigation methodology.


Logging

Logs are written to stderr to avoid interfering with MCP stdio traffic. Use LOGGLY_LOG_LEVEL to control verbosity. Default is info.


Timeouts, Retries & Concurrency

Requests enforce a per-call timeout of LOGGLY_REQUEST_TIMEOUT_MS (default 15000). Transient failures (429, 500 with timeout-like body, 503, 504, or network timeouts) are retried up to LOGGLY_MAX_RETRIES times, honoring a Retry-After header on 429 when Loggly sends one, falling back to exponential backoff otherwise.

The aggregation tools (search_logs, traffic_by_*, get_ip_context, etc.) fan out several requests per call via Promise.all (facets + timeline buckets + a sample). LOGGLY_MAX_CONCURRENT_REQUESTS (default 4) caps how many of those run at once per account, so that fan-out doesn't trip Loggly's own rate limit by itself. If you still see 429s from a single aggregation call, lower this; if Loggly's limit is more generous, raise it.


Tool Manifest

Tool metadata is stored in tool-manifest.json and verified against src/server.js.

npm run verify:manifest

Smoke Test

Smoke test runs without Loggly credentials by setting LOGGLY_SMOKE_TEST=1.

npm run smoke

Implemented MCP Tools

Low-level Loggly API wrappers:

  • connection_test
  • create_search
  • get_events
  • search_and_get_events
  • iterate_events_page
  • iterate_events_next
  • count_events
  • volume_metrics
  • stats_query
  • list_fields
  • field_facets
  • raw_api_call

Aggregation-first traffic tools:

  • search_logs
  • traffic_by_ip
  • traffic_by_host
  • traffic_by_path
  • group_by_ip
  • group_by_path
  • group_by_user_agent
  • timeline
  • sample_events

IP intelligence:

  • rdap_lookup
  • ip_reputation
  • get_ip_context

Examples

Example tool argument payloads are in examples/.


Development

npm test

npm test runs manifest verification and the smoke test. CI runs the same checks in .github/workflows/ci.yml.


Versioning

  • VERSION contains the current release version.
  • CHANGELOG.md tracks changes by release.

Security Notes

  • .env files must never be committed.
  • Tokens and API keys (LOGGLY_TOKEN, LOGGLY_ACCOUNTS, GREYNOISE_API_KEY, ABUSEIPDB_API_KEY, MCP_BEARER_TOKEN) are treated as secrets.
  • This server enforces read-only access to Loggly /apiv2/* endpoints. IP-intel calls (RDAP/GreyNoise/AbuseIPDB) are read-only GET requests to those third-party services; no Loggly credentials are ever sent to them, and no IP-intel keys are sent to Loggly.
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