Context7
Up-to-date docs for AI agents
제작자가 쓴 설명(영어 원문)
Query logs from Graylog: get streams, search messages, aggregate, and get full data.
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.
GRAYLOG_BASE_URL_INSTANCE_1, GRAYLOG_API_TOKEN_INSTANCE_1, GRAYLOG_LABEL_INSTANCE_1비밀로 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": {
"graylog": {
"command": "npx",
"args": [
"-y",
"@jperelli/graylog-mcp"
],
"env": {
"GRAYLOG_BASE_URL_INSTANCE_1": "your-value",
"GRAYLOG_API_TOKEN_INSTANCE_1": "your-value",
"GRAYLOG_LABEL_INSTANCE_1": "your-value"
}
}
}
}터미널에서 이 명령어를 실행하세요
claude mcp add graylog --env GRAYLOG_BASE_URL_INSTANCE_1=your-value --env GRAYLOG_API_TOKEN_INSTANCE_1=your-value --env GRAYLOG_LABEL_INSTANCE_1=your-value -- npx -y @jperelli/graylog-mcp실행하기 전에 빈 값을 채워 주세요.
프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"graylog": {
"command": "npx",
"args": [
"-y",
"@jperelli/graylog-mcp"
],
"env": {
"GRAYLOG_BASE_URL_INSTANCE_1": "your-value",
"GRAYLOG_API_TOKEN_INSTANCE_1": "your-value",
"GRAYLOG_LABEL_INSTANCE_1": "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": {
"graylog": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@jperelli/graylog-mcp"
],
"env": {
"GRAYLOG_BASE_URL_INSTANCE_1": "your-value",
"GRAYLOG_API_TOKEN_INSTANCE_1": "your-value",
"GRAYLOG_LABEL_INSTANCE_1": "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.
GRAYLOG_LABEL_INSTANCE_1 env이 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 6일 점검
레지스트리 이름이 GitHub 계정 jperelli 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: GRAYLOG_BASE_URL_INSTANCE_1, GRAYLOG_API_TOKEN_INSTANCE_1
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 4개월 전 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 Node.js도 있어야 해요.
같은 카테고리에는: Context7, Codebase Memory, Exa
같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.
카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i
Up-to-date docs for AI agents
Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.
Connect AI agents to Exa for web search, content fetching, and multi-step research.
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
A minimal MCP (Model Context Protocol) server in JavaScript that integrates with Graylog.
search (read matching log lines across multiple streams), analyze (aggregate matches by a field, with an optional time histogram), list_fields (which fields exist), list_streams (discover readable streams), and get_message (fetch one full document)list_fields and analyze's valueContains let an agent look up real field names and values instead of inventing them, since a wrong guess returns 0 hits and reads as "no logs exist"search returns a concise projection of high-signal fields by default; opt into full documents with verboseConfigure one or more Graylog instances using numbered env vars:
| Variable | Required | Description |
|---|---|---|
GRAYLOG_BASE_URL_INSTANCE_N | yes | Graylog base URL for instance N |
GRAYLOG_API_TOKEN_INSTANCE_N | yes | API token for instance N |
GRAYLOG_LABEL_INSTANCE_N | no | Human-readable label (default: instance_N) |
Replace N with 1, 2, 3, … to register as many instances as needed. Only instances with both BASE_URL and API_TOKEN set will be active.
No installation needed, npx downloads and runs the server automatically.
claude mcp add graylog-mcp \
-e GRAYLOG_BASE_URL_INSTANCE_1=http://your-graylog-production.example.com:9000 \ -e GRAYLOG_API_TOKEN_INSTANCE_1=your_production_token \ -e GRAYLOG_LABEL_INSTANCE_1=production \ -e GRAYLOG_BASE_URL_INSTANCE_2=http://your-graylog-staging.example.com:9000 \ -e GRAYLOG_API_TOKEN_INSTANCE_2=your_staging_token \ -e GRAYLOG_LABEL_INSTANCE_2=staging \ -- npx -y @jperelli/graylog-mcp@latest
Or add it manually to ~/.claude.json:
{
"mcpServers": { "graylog-mcp": { "command": "npx", "args": ["-y", "@jperelli/graylog-mcp@latest"], "env": { "GRAYLOG_BASE_URL_INSTANCE_1": "http://your-graylog-production.example.com:9000", "GRAYLOG_API_TOKEN_INSTANCE_1": "your_production_token", "GRAYLOG_LABEL_INSTANCE_1": "production",
"GRAYLOG_BASE_URL_INSTANCE_2": "http://your-graylog-staging.example.com:9000", "GRAYLOG_API_TOKEN_INSTANCE_2": "your_staging_token", "GRAYLOG_LABEL_INSTANCE_2": "staging" } } } }
Add to ~/.cursor/mcp.json:
{
"mcpServers": { "graylog-mcp": { "command": "npx", "args": ["-y", "@jperelli/graylog-mcp@latest"], "env": { "GRAYLOG_BASE_URL_INSTANCE_1": "http://your-graylog-production.example.com:9000", "GRAYLOG_API_TOKEN_INSTANCE_1": "your_production_token", "GRAYLOG_LABEL_INSTANCE_1": "production",
"GRAYLOG_BASE_URL_INSTANCE_2": "http://your-graylog-staging.example.com:9000", "GRAYLOG_API_TOKEN_INSTANCE_2": "your_staging_token", "GRAYLOG_LABEL_INSTANCE_2": "staging" } } } }
Config file locations:
~/Library/Application Support/Claude/claude_desktop_config.json~/.config/claude-desktop/claude_desktop_config.json%APPDATA%\Claude\claude_desktop_config.jsonUse the same JSON structure shown above for Cursor.
Once configured, the tools become available and are called automatically when needed. The usual flow is to search the Default Stream (000000000000000000000001), which covers everything the token can read, then analyze to spot patterns, search to read individual lines, and get_message to inspect one hit in full. Reach for list_streams only to scope to a specific named stream. Example prompts:
Search Graylog for errors in the payments namespace in the last 15 minutes.
Query the "staging" instance.
Which containers produced the most errors in the last hour?
Which namespaces have "payments" in the name?
Don't let the agent guess field names or values. A query on a field or value that doesn't exist matches nothing, which looks exactly like "there are no logs". list_fields answers which fields exist, and analyze with valueContains answers which values a field actually has.
List the streams the configured API token can read (id + title). Only readable ones are returned.
You usually don't need this: pass the Default Stream id 000000000000000000000001 to search/analyze to cover everything the token can read. A cluster can hold thousands of streams (the author's has 1,205), so output is capped — use titleContains when you want one specific named stream.
Parameters:
instance (string, optional): Label of the Graylog instance to query. Defaults to the first configured instance.titleContains (string, optional): Case-insensitive substring filter on the stream title (e.g. catalogue).limit (number, optional): Max streams to return. Default: 50. The Default Stream is always included and never counts against the cap.List the message fields that actually exist in the index. Use it before searching on a field you haven't seen in a result, so you never guess a field name.
A cluster indexes thousands of fields (the author's: 3,269), and near-duplicates are common — namespace_name, Pod_namespace, pod_namespace and Namespace may all exist while only one is populated by your shipper. Pass contains to narrow.
Parameters:
contains (string, optional): Case-insensitive substring filter on the field name, e.g. namespace, pod, level.limit (number, optional): Max field names to return. Default: 100.instance (string, optional): Instance label. Defaults to the first configured instance.Read matching log lines across one or more streams, merged newest-first. By default it returns a concise projection of high-signal fields (timestamp, source, level, container_name, pod_name, namespace_name, application_name, service, logger_name, name, msg, err, stack, message) plus each hit's _id/_index, with the raw message body truncated to 500 chars, this keeps the agent's context small. Set verbose: true (or pass explicit fields) to get every populated field, untruncated. Stream IDs are required, an all-streams search is not performed implicitly, because a limited-permission token would be rejected with 403 Not authorized.
name/msg/err/stack are there because a shipper that parses a JSON log line (pino, bunyan, structlog) extracts its keys into real fields. Those fields *are* the summary of the event, and they're cheap — the raw message body that contains them is neither, which is why it's truncated hard by default.
Reach for `analyze` before `search`. Raw lines are the most expensive thing this server returns. A hundred repetitions of one error cost a hundred times as much via
searchas one aggregated row viaanalyze, and tell you less. Usesearchonce you know which line you want.
Tip: to search everything the token can see (including messages not routed to a named stream), pass the Default Stream id
000000000000000000000001.list_streamsalso surfaces it.
Parameters:
query (string, required): Search query, using Graylog/Elasticsearch syntax. Examples: msg:Error, namespace_name:app-payments-qa AND error, source:api-*, *.streams (string, required): Comma-separated stream IDs to search. Get them from list_streams.instance (string, optional): Label of the Graylog instance to query. Defaults to the first configured instance.searchTimeRangeInSeconds (number, optional): Relative time range in seconds. Default: 900 (15 minutes).from / to (string, optional): Absolute window in ISO-8601 UTC (e.g. 2026-07-11 14:00:00). When both are set they override the relative range, use them to investigate a known incident window.searchCountLimit (number, optional): Max number of messages. Default: 50.messageChars (number, optional): Max characters of the raw message body per hit. Default: 500. Raise it only when the detail you need lives in the raw body rather than the parsed fields.verbose (boolean, optional): Return every populated field, untruncated, instead of the concise projection. Default: false.fields (string, optional): Comma-separated explicit field list to return. Overrides the concise projection.The response is { returned, total_matched, streams, messages, note?, projection?, why_no_results? }, where total_matched is the total number of hits across the streams (may exceed returned, which is capped by searchCountLimit); when it does, note explains how to see more.
When a search matches nothing, it tells you why. A bare total_matched: 0 is ambiguous, and the three causes need opposite responses, so why_no_results names the one that applies:
list_fields / analyze.That last case is easy to misread as "this service produced no logs", and it's the reason this project exists in its current shape: the pipeline can lag ingestion by hours under load.
Note on log levels — severity must be discovered, not guessed. Some services emit a top-level Graylog
level(syslog: 3=error, 4=warn). Others log JSON, and the shipper extracts its keys into their *own* fields: pino's{"level":50,"msg":"Error","name":"SvcX"}typically becomes fieldsmsgandname, while its numericlevelis lost — it collides with the container's ownlevel(often7), solevel:50andlevel:ERRORboth match nothing even though the errors are plainly there. Guessing a disjunction likelevel:ERROR OR level:50 OR error OR exception OR fatalis how agents waste turns. Instead runlist_fields(contains: "level","msg","err"), thenanalyzeonmsgto see the actual values. Free-texterrorworks as a fallback; don't assumeexceptionorfatalexist. And avoid"level":50as a query, a quoted string before:is invalid Lucene.
Aggregate matching messages by the top values of a field instead of returning raw lines, e.g. which source, container_name, or level dominates the errors in a window. Optionally add a time histogram of total
앞부분만 보여 드려요. 나머지는 저장소에서 읽어 보세요