MCP YouTube Transcript
An MCP server retrieving transcripts of YouTube videos
제작자가 쓴 설명(영어 원문)
Read-only Loggly search and analytics with aggregation-first traffic tools and IP intelligence.
이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.
이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.
쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.
LOGGLY_SUBDOMAIN, LOGGLY_TOKEN비밀로 표시된 값은 내 계정의 열쇠예요. 절대 다른 사람과 공유하거나 채팅에 붙여 넣지 마세요.
필요한 것
어떤 앱을 쓰세요?
위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.
Claude Desktop → Settings → Developer → Edit Config를 열고 claude_desktop_config.json에 이 내용을 붙여 넣으세요
{
"mcpServers": {
"loggly": {
"command": "npx",
"args": [
"-y",
"@andrewbabu/loggly-mcp"
],
"env": {
"LOGGLY_SUBDOMAIN": "your-value",
"LOGGLY_TOKEN": "your-value"
}
}
}
}터미널에서 이 명령어를 실행하세요
claude mcp add loggly --env LOGGLY_SUBDOMAIN=your-value --env LOGGLY_TOKEN=your-value -- npx -y @andrewbabu/loggly-mcp실행하기 전에 빈 값을 채워 주세요.
프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"loggly": {
"command": "npx",
"args": [
"-y",
"@andrewbabu/loggly-mcp"
],
"env": {
"LOGGLY_SUBDOMAIN": "your-value",
"LOGGLY_TOKEN": "your-value"
}
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"loggly": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@andrewbabu/loggly-mcp"
],
"env": {
"LOGGLY_SUBDOMAIN": "your-value",
"LOGGLY_TOKEN": "your-value"
}
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
이 서버는 내 컴퓨터에서 실행되는데, ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요. 다른 앱을 고르세요.
선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.
이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.
내 컴퓨터에서 실행돼요. 설치하면 AI 앱에 도구 목록이 나타나요.
누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 8일 점검
레지스트리 이름이 GitHub 계정 andrewbabu 기준으로 확인되었고, 이 계정이 저장소를 소유하고 있어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
내 컴퓨터에서 실행되는 서버라 인터넷 엔드포인트가 없어요
내 컴퓨터에서 실행되며, 대신 로컬 설정을 사용해요
내 컴퓨터에서 실행돼요. 도구 목록은 인터넷 엔드포인트가 있는 서버에서만 읽을 수 있어요
레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.
해당하는 기본 점검 1개 중 1개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.
입력해야 할 값: LOGGLY_SUBDOMAIN, LOGGLY_TOKEN
내 컴퓨터에서 실행돼요. AI 앱이 필요할 때 실행하고, 데이터는 제작자의 서버를 거치지 않아요(서버 자체가 온라인 서비스를 호출하는 경우는 제외).
GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(1.3.0)은 35일 전 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 Node.js도 있어야 해요.
같은 카테고리에는: MCP YouTube Transcript, Google Analytics MCP, BibiGPT YouTube Video Summarizer
같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.
카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i
An MCP server retrieving transcripts of YouTube videos
GA4 MCP server for AI agents: schema discovery, server-side aggregation, analysis-ready defaults.
AI video summarizer: summarize and transcribe YouTube, Bilibili, TikTok and podcast videos.
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
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.
For efficient log retrieval (less token use) and summarization, pair this server with a skill.
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" } } } }
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.
The server loads .env from its working directory on startup.
LOGGLY_SUBDOMAIN Loggly account subdomain or full Loggly URL (e.g. your-subdomain or https://your-subdomain.loggly.com)LOGGLY_TOKEN Loggly API tokenLOGGLY_AUTH_MODE bearer (default) or basicLOGGLY_MAX_RETRIES Default: 2LOGGLY_REQUEST_TIMEOUT_MS Default: 15000LOGGLY_LOG_LEVEL error, warn, info (default), or debugFor 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.
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.
docker build -t loggly-mcp .
docker run -d --name loggly-mcp -p 8787:8787 --env-file .env loggly-mcp
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.
account is omitted, the server uses LOGGLY_DEFAULT_ACCOUNT if set, otherwise "default", otherwise the single configured account if there's only one.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".
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:
discovered_fields in the result.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.host, path, status, user_agent, ip).Run list_fields yourself if you want to see every candidate before deciding on an override.
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.
Logs are written to stderr to avoid interfering with MCP stdio traffic. Use LOGGLY_LOG_LEVEL to control verbosity. Default is info.
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 metadata is stored in tool-manifest.json and verified against src/server.js.
npm run verify:manifest
Smoke test runs without Loggly credentials by setting LOGGLY_SMOKE_TEST=1.
npm run smoke
Low-level Loggly API wrappers:
connection_testcreate_searchget_eventssearch_and_get_eventsiterate_events_pageiterate_events_nextcount_eventsvolume_metricsstats_querylist_fieldsfield_facetsraw_api_callAggregation-first traffic tools:
search_logstraffic_by_iptraffic_by_hosttraffic_by_pathgroup_by_ipgroup_by_pathgroup_by_user_agenttimelinesample_eventsIP intelligence:
rdap_lookupip_reputationget_ip_contextExample tool argument payloads are in examples/.
npm test
npm test runs manifest verification and the smoke test. CI runs the same checks in .github/workflows/ci.yml.
VERSION contains the current release version.CHANGELOG.md tracks changes by release..env files must never be committed.LOGGLY_TOKEN, LOGGLY_ACCOUNTS, GREYNOISE_API_KEY, ABUSEIPDB_API_KEY, MCP_BEARER_TOKEN) are treated as secrets./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.