Context7
Up-to-date docs for AI agents
Beschreibung vom Entwickler (englisches Original)
Query logs from Graylog: get streams, search messages, aggregate, and get full data.
Diese drei werden nie zu einer Punktzahl zusammengefasst: Meinungen, Messungen und Beliebtheit sind verschiedene Dinge.
Für diesen Server haben wir noch keine Zusammenfassung in einfacher Sprache geschrieben. Unten stehen die Fakten, die wir aus der Registry gelesen haben.
Wähle die KI-App, die du nutzt, und kopiere die Einstellungen.
GRAYLOG_BASE_URL_INSTANCE_1, GRAYLOG_API_TOKEN_INSTANCE_1, GRAYLOG_LABEL_INSTANCE_1Als geheim markierte Werte sind Schlüssel zu deinem Konto. Gib sie nie weiter und füge sie nie in einen Chat ein.
Du brauchst
Welche App nutzt du?
Wähle oben deine App. Wir merken sie uns, damit der Button beim nächsten Mal „In … installieren“ anzeigt.
Öffne Claude Desktop → Settings → Developer → Edit Config und füge dies in claude_desktop_config.json ein
{
"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"
}
}
}
}Führe das in deinem Terminal aus
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-mcpTrag die leeren Werte ein, bevor du ihn startest.
In .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen
{
"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"
}
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
In .vscode/mcp.json in deinem Projekt einfügen
{
"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"
}
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
Dieser Server läuft auf deinem Computer, und ChatGPT kann sich nur mit Servern im Internet verbinden. Wähle eine andere App.
Deine Auswahl bleibt in einem Cookie auf diesem Gerät; kein Konto nötig.
GRAYLOG_LABEL_INSTANCE_1 envDiese Einstellungen werden aus dem Registry-Eintrag des Entwicklers erzeugt. Wenn in der README etwas anderes steht, folge der README.
Läuft auf deinem Computer; die Tool-Liste erscheint nach der Installation in deiner KI-App.
Wir prüfen Informationen, die jeder sehen kann; den Code haben wir nicht gelesen. Checks, die nicht zutreffen, werden nicht mitgezählt. · Geprüft am 6. Nov. 2026
Der Registry-Name wurde mit dem GitHub-Konto jperelli bestätigt, dem das Repo gehört
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieser Server läuft auf deinem Computer; es gibt keinen Endpunkt im Internet
Läuft auf deinem Computer und nutzt stattdessen lokale Einstellungen
Läuft auf deinem Computer; Tool-Listen können wir nur von Endpunkten im Internet lesen
Verglichen mit allen aktiven Servern dieser Kategorie in der Registry. Sterne zählen nur, wenn dem Herausgeber das Repo gehört.
Er hat 1 von 1 zutreffenden Basischecks bestanden. Den Code haben wir nicht gelesen. Bevor du einen Schlüssel oder Token hinzufügst, sieh nach, welche Zugriffe der Server verlangt, und nutze einen Schlüssel, der nur die Berechtigungen hat, die du brauchst.
Das musst du eintragen: GRAYLOG_BASE_URL_INSTANCE_1, GRAYLOG_API_TOKEN_INSTANCE_1
Er läuft auf deinem Computer. Deine KI-App startet ihn bei Bedarf, und die Daten laufen nicht über die Server des Entwicklers (außer der Server ruft selbst einen Onlinedienst auf).
Das GitHub-Repo wurde zuletzt – geändert, und die neueste Version (1.3.0) kam vor 4 Monaten in die Registry.
Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code. Außerdem brauchst du Node.js auf deinem Computer.
In derselben Kategorie: Context7, Codebase Memory, Exa
Server derselben Kategorie von anderen Entwicklern, sortiert nach Sternen.
So liest du eine Karte:★ GitHub-SterneiDrei Säulen: Bewertungen · Checks · NutzungiAktualisiert = neueste Version in der Registry veröffentlichti
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.
Unverändert aus dem Repo des Entwicklers übernommen. PopNx MCP hat den Inhalt weder geprüft noch empfiehlt es ihn. HTML, Bilder und Skripte wurden entfernt. Links führen von dieser Website weg.
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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