Context7
Up-to-date docs for AI agents
作者提供的说明(英文原文)
Query logs from Graylog: get streams, search messages, aggregate, and get full data.
这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。
我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。
选择你使用的 AI 应用,然后复制设置。
GRAYLOG_BASE_URL_INSTANCE_1, GRAYLOG_API_TOKEN_INSTANCE_1, GRAYLOG_LABEL_INSTANCE_1标为机密的值是你账户的钥匙。千万不要分享给别人,也不要粘贴到聊天里。
你需要
你用的是哪个应用?
在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。
打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json
{
"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"
}
}
}
}在终端中运行这条命令
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-mcp运行前请先填写空着的值。
粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"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"
}
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
粘贴到项目中的 .vscode/mcp.json
{
"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"
}
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。
你的选择通过 Cookie 保存在这台设备上,无需账户。
GRAYLOG_LABEL_INSTANCE_1 env这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。
它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日
注册名称已通过 GitHub 账户 jperelli 验证,该账户拥有此仓库
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
它在你的电脑上运行,没有互联网端点
在你的电脑上运行,改用本地设置
它在你的电脑上运行;我们只能读取互联网端点的工具列表
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
你需要填写:GRAYLOG_BASE_URL_INSTANCE_1, GRAYLOG_API_TOKEN_INSTANCE_1
它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。
GitHub 仓库最后更新于–,最新版本(1.3.0)于4个月前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Node.js。
同一分类中有:Context7, Codebase Memory, Exa
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i
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.
按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。
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
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