Context7
Up-to-date docs for AI agents
Descripción del creador (original en inglés)
Query logs from Graylog: get streams, search messages, aggregate, and get full data.
Estos tres nunca se combinan en una sola puntuación: las opiniones, las mediciones y la popularidad son cosas distintas.
Todavía no escribimos un resumen sencillo para este. Abajo están los datos que leímos del registro.
Elige la app de IA que usas y copia la configuración.
GRAYLOG_BASE_URL_INSTANCE_1, GRAYLOG_API_TOKEN_INSTANCE_1, GRAYLOG_LABEL_INSTANCE_1Los valores marcados como secretos son llaves de tu cuenta. Nunca los compartas ni los pegues en un chat.
Necesitas
¿Qué app usas?
Elige tu app arriba. La recordamos, así que la próxima vez el botón dirá “Instalar en …”.
Abre Claude Desktop → Settings → Developer → Edit Config y pega esto en 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"
}
}
}
}Ejecuta esto en tu terminal
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-mcpCompleta los valores vacíos antes de ejecutarlo.
Pégalo en .cursor/mcp.json de tu proyecto, o en ~/.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"
}
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Pégalo en .vscode/mcp.json de tu proyecto
{
"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"
}
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Este se ejecuta en tu computadora, y ChatGPT solo puede conectarse a servidores en internet. Elige otra app.
Tu elección se guarda en una cookie en este dispositivo; no necesitas cuenta.
GRAYLOG_LABEL_INSTANCE_1 envEsta configuración se genera a partir de la ficha del creador en el registro. Si el README dice otra cosa, sigue el README.
Se ejecuta en tu computadora; la lista de herramientas aparece en tu app de IA después de instalarlo.
Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 7 nov 2026
El nombre en el registro se verificó con la cuenta de GitHub jperelli, dueña del repo
Todavía no hemos leído este repo en GitHub
Todavía no hemos leído este repo en GitHub
Este se ejecuta en tu computadora; no hay endpoint en internet
Se ejecuta en tu computadora y usa ajustes locales en su lugar
Se ejecuta en tu computadora; solo podemos leer listas de herramientas de endpoints en internet
Comparado con todos los servidores activos de esta categoría en el registro. Las estrellas solo cuentan cuando quien lo publica es dueño del repo.
Superó 1 de 1 revisiones básicas aplicables. No hemos leído el código. Antes de agregar una clave o un token, revisa qué acceso pide el servidor y usa una clave que tenga solo los permisos que necesitas.
Debes completar: GRAYLOG_BASE_URL_INSTANCE_1, GRAYLOG_API_TOKEN_INSTANCE_1
Se ejecuta en tu computadora. Tu app de IA lo inicia cuando hace falta, y los datos no pasan por los servidores del creador (a menos que el propio servidor llame a un servicio en línea).
El repo de GitHub cambió por última vez –, y la última versión (1.3.0) llegó al registro hace 4 meses.
Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas Node.js en tu computadora.
En la misma categoría: Context7, Codebase Memory, Exa
Servidores de la misma categoría hechos por otros creadores, ordenados por estrellas.
Cómo leer una tarjeta:★ Estrellas de GitHubiTres pilares: reseñas · revisiones · usoiActualizado = fecha en que se publicó la última versión en el registroi
Up-to-date docs for AI agents
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Connect AI agents to Exa for web search, content fetching, and multi-step research.
Copiado tal cual del repo del creador. PopNx MCP no lo ha revisado ni lo respalda. Se quitaron HTML, imágenes y scripts. Los enlaces llevan fuera de este sitio.
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
Solo se muestra el principio; lee el resto en el repo