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ellmos-servercommander-mcp

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ellmos-servercommander-mcp

Servidor MCP en fase alfa para operaciones de servidor: simulaciones de despliegue, estado del correo, análisis de registros de acceso y comprobaciones de salud HTTP.

README en alemán: README_de.md

Parte de la familia ellmos-ai.

Licencia: MIT Versión npm Python Node.js MCP Estado: alfa Pytest: 37 superados Ecosistema: ellmos--ai open-bricks LLM--Ready: llms.txt

[!NOTA] Descubribilidad y búsqueda con IA: Publicado en npm como ellmos-servercommander-mcp, catalogado para ecosistemas MCP en server.json, glama.json y smithery.yaml, e indexado para búsqueda con IA/LLM en llms.txt.

Arquitectura visualizada

graph TD
    Client[MCP Host: Claude / Cursor] <-->|stdio / JSON-RPC| NodeWrapper[Node.js Entrypoint]
    NodeWrapper <-->|Spawn subprocess| PyServer[Python MCP Server]
    
    subgraph Tools [ServerCommander Tools]
        PyServer -->|sc_health_check| HTTP[HTTP/HTTPS Endpoint Check]
        PyServer -->|sc_logs_analyze| Logs[Apache/Nginx Access Logs]
        PyServer -->|sc_deploy / sc_deploy_status| Deploy[Dry-Run Manifest & SQLite History]
        PyServer -->|sc_mail_*| Mail[IMAP/SMTP Safe Readiness Diagnostics]
    end
    
    subgraph Storage [Local Storage]
        Deploy -->|Optional persist| SQLite[(SQLite Deploy History)]
        Logs -->|Optional persist| JSONReports[(JSON Log Reports)]
    end

Related MCP server: automation-health-mcp

Comience aquí

Objetivo

Comience con

Añadir ServerCommander a Claude Desktop, Claude Code, Cursor u otro host MCP

Configuración del cliente MCP

Comprobar un endpoint HTTP público o interno antes de un despliegue

sc_health_check

Inspeccionar registros de acceso de Apache/Nginx en busca de errores, bots, referentes y rutas sospechosas

sc_logs_analyze

Crear un manifiesto de despliegue en seco antes de que exista la ejecución SFTP/SSH

sc_deploy y sc_deploy_status

Preparar operaciones de correo para más adelante sin envíos accidentales hoy

sc_mail_list, sc_mail_read, sc_mail_send, sc_mail_search

Estado

  • Transporte: stdio mediante el SDK MCP de Python

  • Estado del paquete: paquete público en fase alfa bajo ellmos-ai

  • Núcleo actual: listado de herramientas MCP, envío de herramientas MCP, carga de configuración, comprobaciones de salud HTTP, análisis más completo de registros de acceso con informes JSON opcionales persistentes e historial opcional de despliegues en seco local

  • Manejadores seguros en alfa: sc_deploy crea manifiestos SHA256 locales, diagnósticos de configuración y registros opcionales en SQLite en modo seco; sc_mail_* informa de la preparación IMAP/SMTP específica del protocolo sin abrir conexiones de correo

  • i18n: descripciones de herramientas MCP localizadas, descripciones de campos del esquema de entrada y errores de herramienta desconocida para en, de, es, zh, ja, ru con fallback al inglés

Instalación

El paquete npm contiene un envoltorio Node que inicia el servidor Python. Aún necesita Python 3.10+ y el paquete Python mcp>=1.0.0.

Opción 1: Instalar desde npm

npm install -g ellmos-servercommander-mcp@alpha
ellmos-servercommander

Opción 2: Instalar desde el código fuente

git clone https://github.com/ellmos-ai/ellmos-servercommander-mcp.git
cd ellmos-servercommander-mcp
$env:PYTHONIOENCODING = "utf-8"
python -m pip install -e ".[dev]"
python -m pytest -q

Evite crear un .venv dentro de carpetas sincronizadas en la nube si su cliente de sincronización bloquea archivos. Si necesita un entorno aislado, créelo fuera de esa carpeta.

Iniciar desde el código fuente

$env:PYTHONPATH = "src"
python -m servercommander.server

Configuración del cliente MCP

Instalación global de npm

{
  "mcpServers": {
    "servercommander": {
      "command": "ellmos-servercommander"
    }
  }
}

npx sin instalación global

{
  "mcpServers": {
    "servercommander": {
      "command": "npx",
      "args": ["-y", "ellmos-servercommander-mcp@alpha"]
    }
  }
}

Ejecución directa de Python

{
  "mcpServers": {
    "servercommander": {
      "command": "python",
      "args": ["-m", "servercommander.server"],
      "env": {
        "PYTHONPATH": "C:/path/to/ellmos-servercommander-mcp/src",
        "SERVERCOMMANDER_CONFIG_PATH": "C:/path/to/config/servercommander.toml"
      }
    }
  }
}

Configuración

ServerCommander busca la configuración en este orden:

  1. Variable de entorno SERVERCOMMANDER_CONFIG_PATH

  2. ./servercommander.toml

  3. ./config/servercommander.toml

  4. ~/.config/servercommander/servercommander.toml

Se incluye una plantilla anotada en config/servercommander.example.toml.

[server]
name = "servercommander"
log_level = "INFO"
language = "en"

[deploy.profiles.staging]
target = "sftp://staging.example.com/var/www/app"
local_path = "./dist"
protocol = "sftp"
dry_run = true
record_history = true

[mail]
execution_enabled = false
smtp_host = "smtp.example.com"
smtp_port = 587
imap_host = "imap.example.com"
imap_port = 993

Los secretos deben referenciarse mediante variables de entorno, por ejemplo $MAIL_PASSWORD o $SFTP_PASSWORD.

Herramientas

  • sc_health_check: comprueba endpoints HTTP y devuelve el código de estado más la latencia; las URL de endpoint mal formadas se devuelven como comprobaciones fallidas, de modo que una entrada incorrecta no interrumpe un lote

  • sc_logs_analyze: analiza registros de acceso de Apache/Nginx desde texto en línea o un archivo local, incluyendo clases de estado, bytes, referentes, rutas de error, marcadores de solicitudes sospechosas y persistencia opcional de informes JSON mediante persist_report

  • sc_deploy: crea un plan de despliegue con un manifiesto SHA256 local y diagnósticos de perfil, pero aún no sube; las comprobaciones de preparación verifican campos obligatorios, rutas locales manifestables y protocolos compatibles antes de record_history=true opcional; los enlaces simbólicos anidados se notifican pero se excluyen para que un manifiesto no pueda atravesar silenciosamente más allá del directorio de lanzamiento seleccionado

  • sc_deploy_status: muestra los perfiles de despliegue configurados, diagnósticos del perfil seleccionado e historial reciente de simulaciones desde la base de datos SQLite local

  • sc_mail_list, sc_mail_read, sc_mail_send, sc_mail_search: respuestas de estado alfa seguras con diagnósticos de preparación IMAP/SMTP específicos de la acción y sin conexiones de correo por defecto. Con [mail].execution_enabled = true, sc_mail_list ejecuta una sonda de alcance IMAP de solo lectura en vivo (conectar + listar carpetas) reutilizando el módulo canónico mail-connector — no reimplementa un cliente IMAP; la lectura/búsqueda a nivel de mensaje siguen siendo dominio de mail-connector, y el envío SMTP permanece sin ejecución

Búsqueda y desambiguación

ServerCommander es el servidor MCP de operaciones de ellmos para flujos de trabajo de administración de servidores locales. Use este repositorio cuando busque:

  • Herramientas de operaciones de servidor MCP

  • Servidor MCP de simulación de despliegue

  • Analizador de registros de acceso MCP

  • Herramienta de comprobación de salud HTTP MCP

  • Gestión de servidores local primero MCP

  • MCP de operaciones de servidor para Claude Code

  • MCP de planificación de despliegue SFTP seguro

No es el servidor MCP de GitHub, no es un servidor MCP de comandos shell genérico, no es un panel de control de proveedor de alojamiento y no es un ejecutor de SFTP/IMAP en producción. La superficie alfa actual es intencionadamente diagnóstica y de simulación primero.

Ecosistema ellmos-ai

Este servidor MCP forma parte del ecosistema ellmos-ai — infraestructura de IA, servidores MCP y herramientas inteligentes.

Familia de servidores MCP

Servidor

Herramientas

Enfoque

npm

FileCommander

46

Sistema de archivos, gestión de procesos, sesiones interactivas, operaciones seguras en la nube

ellmos-filecommander-mcp

CodeCommander

22

Análisis de código, reparación JSON, importaciones, diferencias, regex

ellmos-codecommander-mcp

Clatcher

12

Reparación de archivos, conversión de formato, operaciones por lotes

ellmos-clatcher-mcp

n8n Manager

18

Gestión de flujos de trabajo n8n mediante asistentes de IA

n8n-manager-mcp

ControlCenter

20

Descubrimiento de pila MCP, gestión de perfiles, plano de control

ellmos-controlcenter-mcp

Homebase

45

Memoria LLM local primero, conocimiento, estado, enrutamiento, orquestación de enjambre

ellmos-homebase-mcp (alfa)

ServerCommander

8

Operaciones de servidor: comprobaciones de salud, análisis de registros, simulaciones de despliegue, diagnósticos de correo

ellmos-servercommander-mcp (alfa)

Blender Use

3

Control de calidad de activos Blender sin cabeza y verificación de reimportación FBX

ellmos-blender-use-mcp (alfa)

Open Compute

10

Uso de ordenador independiente del modelo: captura, acciones con protección de seguridad, UIA de Windows

open-compute-mcp (alfa)

Infraestructura de IA y herramientas para desarrolladores

Project

Descripción

BACH

SO local basada en texto para agentes LLM — 113+ manejadores, 550+ herramientas, memoria SQLite

open-compute

Núcleo de uso computacional agnóstico al modelo que potencia Open Compute MCP

clutch

Orquestación LLM neutral al proveedor con enrutamiento automático y seguimiento de presupuesto

rinnsal

Memoria ligera para agentes, conectores e infraestructura de automatización

ellmos-stack

Pila de investigación de IA auto-alojada (Ollama + n8n + Rinnsal + KnowledgeDigest)

MarbleRun

Marco de cadenas de agentes autónomos para Claude Code

gardener

Prototipo minimalista de SO LLM basado en base de datos (4 funciones, 1 tabla)

ellmos-tests

Marco de pruebas para sistemas operativos LLM (7 dimensiones)

sqlite-transit-sync

Sincronización de tránsito SQLite cifrada y motor de réplica de solo lectura aditivo

workflowhooker

Automatización de flujos de trabajo impulsada por hooks de Git y límites de seguridad de ejecución

system-explorer

Composición de sistemas local-first, introspección de módulos y verificación de flotas

companion-for-agy

Compañero de desarrollo Antigravedad y puente de telemetría

Software de Escritorio

Nuestra organización colaboradora open-bricks agrupa aplicaciones de escritorio nativas de IA — un conjunto de software moderno y de código abierto construido para la era de la IA. Las categorías incluyen gestión de archivos (ProFiler), herramientas documentales (DokuZen, PDFtoPDFocr), utilidades para desarrolladores (DevCenter, CodeBox) y más.

Desarrollo

$env:PYTHONIOENCODING = "utf-8"
python -m pytest -q
npm run smoke
npm pack --dry-run

Próximo paso útil: agregar adaptadores de ejecución configurados explícitamente para SFTP e IMAP/SMTP, manteniendo las opciones predeterminadas de simulación/solo estado.

Available Tools

8 tools
sc_deployB

Build a safe deployment plan. Alpha only: execution requires dry_run=true.

ParametersJSON Schema
NameRequiredDescriptionDefault
dry_runNoBuild the plan without executing deployment.
profileNoDeployment profile name.
local_pathNoLocal source path.
remote_pathNoRemote target path.
record_historyNoPersist this dry-run deployment plan in the local history database.

TDQS

B3.1/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full behavioral burden. It mentions alpha status and a dry_run constraint, but does not disclose side effects such as record_history writing to a local database, permissions, or return behavior. The phrase "execution requires dry_run=true" is also ambiguous because dry_run=true means no execution per the schema.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two compact sentences with no wasted words, and the core purpose is front-loaded before the alpha constraint.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The schema fully documents all five parameters, and the description adds the important alpha/dry_run limitation. However, with no annotations and no output schema, the description omits enough behavioral context (side effects, return values, alternatives) that the definition is only minimally complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the parameter meanings are already documented in the input schema. The description only repeats the dry_run requirement and adds no syntax, format, or interaction details beyond what the schema provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource: "Build a safe deployment plan." It distinguishes the tool from an actual deployment execution, and the alpha-only note further narrows scope. However, it does not explicitly differentiate itself from the sibling sc_deploy_status tool.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives a constraint ("Alpha only: execution requires dry_run=true") but no guidance on when to use this tool versus alternatives such as sc_deploy_status. There is no when-to-use or when-not-to-use context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

sc_deploy_statusC

Show configured deployment profiles and alpha deployment-history status.

ParametersJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of results.
profileNoDeployment profile name.

TDQS

C2.9/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full disclosure burden. 'Show' implies read-only, but there is no mention of auth requirements, whether the profile filter is required or optional, what happens when no profile is given, or how the limit interacts with history versus profiles.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single front-loaded sentence with no waste. It is slightly compressed to the point of ambiguity ('alpha deployment-history status'), but it does not pad or bury the key information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a low-complexity read tool with two optional, fully documented params and no output schema, the description is minimally adequate. It still leaves the meaning of the returned deployment status and the 'alpha' qualifier unexplained, which an agent would need to interpret results.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so both parameters (limit, profile) are already documented. The description hints at their roles ('configured deployment profiles', 'deployment-history') but adds no syntax, defaults, or filtering semantics beyond what the schema states, so the baseline of 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb ('Show') and two concrete resources (configured deployment profiles, deployment-history status), so an agent understands it is a read/status query. It does not, however, differentiate itself from the sibling sc_deploy, and the qualifier 'alpha' is unexplained jargon that muddies what is actually being reported.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no statement of when to call this versus sc_deploy or the other siblings, and no prerequisites or exclusions. Usage is only inferable from the fact that it is a status-style read, which is weak guidance for an agent choosing among eight tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

sc_health_checkB

Check HTTP endpoints and return status codes plus latency.

ParametersJSON Schema
NameRequiredDescriptionDefault
timeoutNoRequest timeout in seconds.
endpointsNoHTTP endpoint URLs to check.

TDQS

B3.4/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full behavioral burden. It usefully discloses the return shape (status codes plus latency) but says nothing about authentication, redirect handling, concurrency, or per-endpoint failure behavior. Adequate disclosure of outputs, silent on operating conditions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single tight sentence with the action and the two return values front-loaded. No filler, nothing to trim.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple two-parameter read tool with no output schema, stating that it returns status codes plus latency covers the main return-value gap. Deployment/auth context that would make it fully self-sufficient is absent, but nothing critical to invoking it correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% – both 'timeout' (seconds, default 5) and 'endpoints' (URL list) are already documented in the schema. The description restates the purpose but adds no format, batching, or default details beyond the schema, so baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (check), resource (HTTP endpoints), and outputs (status codes plus latency), so the agent immediately knows what the tool does. It doesn't distinguish itself from siblings, but the siblings (sc_deploy, sc_mail_*, sc_logs_analyze) occupy unrelated domains, so cross-confusion risk is low.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No when-to-use guidance, no prerequisites, and no alternatives named. The health-check intent is only implied by the tool name and the endpoint wording. Nothing tells the agent when this is preferable to reading logs via sc_logs_analyze.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

sc_logs_analyzeB

Analyze Apache/Nginx access logs from inline text or a local file path.

ParametersJSON Schema
NameRequiredDescriptionDefault
formatNoLog format hint.
log_pathNoLocal access-log file path.
log_textNoInline access-log text.
top_pathsNoNumber of top paths to include.
report_nameNoOptional report filename stem.
persist_reportNoPersist the analysis summary as a JSON report.

TDQS

B3.3/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full behavioral burden, yet it discloses only the input sources. It says nothing about whether the tool writes anything to disk (relevant given persist_report and report_name), what permissions or file access are required, or how results are returned.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single front-loaded sentence with zero waste; scope and input modes are stated immediately with no filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With six optional parameters, no output schema, and no annotations, the description is only partially complete. It omits what the analysis yields and the side effect of persisting a report, but the schema covers the individual parameters so the gap is moderate rather than critical.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all six parameters including format, log_path, log_text, top_paths, report_name, and persist_report. The description only restates the two input modes and adds no new parameter semantics, so the baseline of 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (Analyze) and resource (Apache/Nginx access logs), plus the two input modes (inline text or local file path). This clearly distinguishes it from unrelated siblings like sc_deploy and sc_mail_send, though it does not describe what the analysis produces.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is implied by the tool name and the two accepted input sources, but there is no explicit when-to-use/when-not guidance or mention of preconditions. Adequate but leaves the agent to infer context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

sc_mail_listC

Alpha mail status endpoint for listing an IMAP folder.

ParametersJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of results.
folderNoMail folder name.INBOX

TDQS

C2.5/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full behavioral burden, and it says almost nothing: 'listing' weakly implies read-only, but there is no mention of pagination, return format, ordering, or folder-must-exist behavior. An agent gets minimal signal about what happens on invocation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single short sentence is appropriately sized, but the front-loaded 'Alpha mail status endpoint' framing is noise that misdirects rather than informing. It is concise but not well-structured around the actual operation.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No annotations and no output schema mean the description must explain behavior and results, and it does neither. For a list tool with defaults (limit=10, INBOX), an agent lacks the context needed to call it confidently or interpret the response.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% and both parameters (limit, folder) are documented in the schema, so the baseline is 3. The description adds no extra meaning such as default pagination behavior or folder-name semantics beyond what the schema already states.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The verb 'listing' and resource 'IMAP folder' are present, so the core action is inferable. However, the lead phrase 'Alpha mail status endpoint' muddles the purpose (status vs. listing) and the description never distinguishes this from siblings like sc_mail_search or sc_mail_read.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this versus sc_mail_search (filtered retrieval) or sc_mail_read (single message). No prerequisites, no exclusions, nothing beyond an implied 'use this to list a folder'.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

sc_mail_readC

Alpha mail status endpoint for reading a message.

ParametersJSON Schema
NameRequiredDescriptionDefault
message_idNoMessage identifier.

TDQS

C2.5/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full behavioral burden, and it discloses almost nothing: it does not say the operation is read-only, what happens if the message_id is unknown, whether the caller needs authorization, or what the response contains. 'Status endpoint' hints at a return shape but never explains it.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

It is a single short sentence with no filler, which is structurally clean. The problem is under-specification rather than verbosity, and the most useful information (what it returns) is absent.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a read tool with no annotations and no output schema, the description should at least characterize the returned data, but it only offers the ambiguous label 'status endpoint'. With one parameter required and zero required params declared, an agent cannot determine preconditions or expected output from this definition.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% for the single message_id parameter, so the schema already documents it. The description adds no format, source, or lookup guidance beyond that, making the baseline 3 the correct score.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a verb ('reading') and resource ('a message'), which loosely separates it from siblings like sc_mail_list, sc_mail_send, and sc_mail_search. However, the phrase 'Alpha mail status endpoint' is unexplained jargon that muddies whether this reads message content or fetches a delivery/status record, so the purpose is only partially pinned down.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no statement of when to use this tool versus sc_mail_list or sc_mail_search, both of which plausibly retrieve messages. The agent is left to infer that a known message_id is a prerequisite for this tool, and no exclusions or alternatives are given.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

sc_mail_sendC

Alpha mail status endpoint for sending mail; does not send yet.

ParametersJSON Schema
NameRequiredDescriptionDefault
toYesEmail recipient.
bodyYesEmail body text.
subjectYesEmail subject.

TDQS

C2.6/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden, and it does disclose one important trait: the endpoint does not actually send yet, which prevents a false assumption of a side effect. However, it omits auth requirements, what the call returns (no output schema), and whether it errors or silently no-ops, leaving key behavior undefined.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

It is a single short sentence with no padding, and the caveat is placed immediately after the purpose. The only cost is that the phrasing itself is ambiguous rather than the length.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a three-required-parameter call with no annotations and no output schema, the description should clarify what the invocation returns or does. It only asserts the tool 'does not send yet,' leaving return behavior, error cases, and the resulting state entirely unspecified.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and all three required parameters (to, subject, body) carry their own descriptions, so the schema does the heavy lifting. The description adds nothing about parameter formats or constraints, so baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose2/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description is internally muddled: it calls itself a 'status endpoint' for 'sending mail' while also saying it 'does not send yet.' An agent cannot confidently tell whether this sends, checks status, or is a no-op, and the sibling set (sc_mail_list/read/search) offers no disambiguation. The verb+resource pair is stated but immediately undercut.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no when-to-use, when-not-to-use, or alternative-tool guidance. The phrase 'does not send yet' hints the tool is a stub, but it never tells the agent when this tool should be preferred over other mail siblings or when to avoid it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 8 tool updatesv0.1.0-alpha.21
    • First observedsc_deploy
    • First observedsc_deploy_status
    • First observedsc_health_check
    • First observedsc_logs_analyze
    • First observedsc_mail_list
    • First observedsc_mail_read
    • First observedsc_mail_search
    • First observedsc_mail_send

TDQS

B3/5.0

Scored across 8 tools

Disambiguation4/5

Each tool targets a fairly distinct area: deploy vs deploy_status differ by planning versus status inspection, and the four mail tools split cleanly along list/read/send/search. The main risk is sc_deploy vs sc_deploy_status, which could be confused at a glance, but descriptions clarify the boundary.

Naming Consistency4/5

All tools share an sc_ prefix and snake_case, with mostly predictable noun_verb ordering (sc_mail_list, sc_health_check, sc_logs_analyze). sc_deploy is a bare verb outlier and the mail_* group reads as noun_action rather than verb_noun, but the scheme is readable and consistent overall.

Tool Count4/5

Eight tools is well within a sensible range for a server-commander surface spanning deploy, mail, logs, and health. No obvious redundancy or padding, though half the set is devoted to mail operations that are still alpha stubs.

Completeness3/5

Mail coverage (list/read/send/search) and deploy (plan + status) are reasonably complete, but several operations are explicitly non-functional alpha status endpoints (send 'does not send yet') and there is no log tailing/filtering beyond one-shot analysis. The server-commander domain lacks service restart, config, or process-management operations, leaving notable gaps.

Maintenance

ActivityActive
ResponsivenessNo issues

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