ellmos-servercommander-mcp
Officialellmos-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.
[!NOTA] Descubribilidad y búsqueda con IA: Publicado en npm como
ellmos-servercommander-mcp, catalogado para ecosistemas MCP enserver.json,glama.jsonysmithery.yaml, e indexado para búsqueda con IA/LLM enllms.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)]
endRelated MCP server: automation-health-mcp
Comience aquí
Objetivo | Comience con |
Añadir ServerCommander a Claude Desktop, Claude Code, Cursor u otro host MCP | |
Comprobar un endpoint HTTP público o interno antes de un despliegue |
|
Inspeccionar registros de acceso de Apache/Nginx en busca de errores, bots, referentes y rutas sospechosas |
|
Crear un manifiesto de despliegue en seco antes de que exista la ejecución SFTP/SSH |
|
Preparar operaciones de correo para más adelante sin envíos accidentales hoy |
|
Estado
Transporte: stdio mediante el SDK MCP de Python
Estado del paquete: paquete público en fase alfa bajo
ellmos-aiNúcleo 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_deploycrea 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 correoi18n: descripciones de herramientas MCP localizadas, descripciones de campos del esquema de entrada y errores de herramienta desconocida para
en,de,es,zh,ja,rucon 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-servercommanderOpción 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 -qEvite 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.serverConfiguración 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:
Variable de entorno
SERVERCOMMANDER_CONFIG_PATH./servercommander.toml./config/servercommander.toml~/.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 = 993Los 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 lotesc_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 mediantepersist_reportsc_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 derecord_history=trueopcional; los enlaces simbólicos anidados se notifican pero se excluyen para que un manifiesto no pueda atravesar silenciosamente más allá del directorio de lanzamiento seleccionadosc_deploy_status: muestra los perfiles de despliegue configurados, diagnósticos del perfil seleccionado e historial reciente de simulaciones desde la base de datos SQLite localsc_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_listejecuta una sonda de alcance IMAP de solo lectura en vivo (conectar + listar carpetas) reutilizando el módulo canónicomail-connector— no reimplementa un cliente IMAP; la lectura/búsqueda a nivel de mensaje siguen siendo dominio demail-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 |
46 | Sistema de archivos, gestión de procesos, sesiones interactivas, operaciones seguras en la nube | ||
22 | Análisis de código, reparación JSON, importaciones, diferencias, regex | ||
12 | Reparación de archivos, conversión de formato, operaciones por lotes | ||
18 | Gestión de flujos de trabajo n8n mediante asistentes de IA | ||
20 | Descubrimiento de pila MCP, gestión de perfiles, plano de control | ||
45 | Memoria LLM local primero, conocimiento, estado, enrutamiento, orquestación de enjambre |
| |
8 | Operaciones de servidor: comprobaciones de salud, análisis de registros, simulaciones de despliegue, diagnósticos de correo |
| |
3 | Control de calidad de activos Blender sin cabeza y verificación de reimportación FBX |
| |
10 | Uso de ordenador independiente del modelo: captura, acciones con protección de seguridad, UIA de Windows |
|
Infraestructura de IA y herramientas para desarrolladores
Project | Descripción |
SO local basada en texto para agentes LLM — 113+ manejadores, 550+ herramientas, memoria SQLite | |
Núcleo de uso computacional agnóstico al modelo que potencia Open Compute MCP | |
Orquestación LLM neutral al proveedor con enrutamiento automático y seguimiento de presupuesto | |
Memoria ligera para agentes, conectores e infraestructura de automatización | |
Pila de investigación de IA auto-alojada (Ollama + n8n + Rinnsal + KnowledgeDigest) | |
Marco de cadenas de agentes autónomos para Claude Code | |
Prototipo minimalista de SO LLM basado en base de datos (4 funciones, 1 tabla) | |
Marco de pruebas para sistemas operativos LLM (7 dimensiones) | |
Sincronización de tránsito SQLite cifrada y motor de réplica de solo lectura aditivo | |
Automatización de flujos de trabajo impulsada por hooks de Git y límites de seguridad de ejecución | |
Composición de sistemas local-first, introspección de módulos y verificación de flotas | |
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-runPróximo paso útil: agregar adaptadores de ejecución configurados explícitamente para SFTP e IMAP/SMTP, manteniendo las opciones predeterminadas de simulación/solo estado.
Available Tools
8 toolssc_deployB
Build a safe deployment plan. Alpha only: execution requires dry_run=true.
| Name | Required | Description | Default |
|---|---|---|---|
| dry_run | No | Build the plan without executing deployment. | |
| profile | No | Deployment profile name. | |
| local_path | No | Local source path. | |
| remote_path | No | Remote target path. | |
| record_history | No | Persist this dry-run deployment plan in the local history database. |
TDQS
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.
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.
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.
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.
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.
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.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum number of results. | |
| profile | No | Deployment profile name. |
TDQS
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.
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.
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.
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.
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.
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.
| Name | Required | Description | Default |
|---|---|---|---|
| timeout | No | Request timeout in seconds. | |
| endpoints | No | HTTP endpoint URLs to check. |
TDQS
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.
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.
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.
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.
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.
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.
| Name | Required | Description | Default |
|---|---|---|---|
| format | No | Log format hint. | |
| log_path | No | Local access-log file path. | |
| log_text | No | Inline access-log text. | |
| top_paths | No | Number of top paths to include. | |
| report_name | No | Optional report filename stem. | |
| persist_report | No | Persist the analysis summary as a JSON report. |
TDQS
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.
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.
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.
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.
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.
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.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum number of results. | |
| folder | No | Mail folder name. | INBOX |
TDQS
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.
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.
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.
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.
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.
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.
| Name | Required | Description | Default |
|---|---|---|---|
| message_id | No | Message identifier. |
TDQS
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.
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.
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.
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.
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.
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_searchC
Alpha mail status endpoint for searching mail.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum number of results. | |
| query | Yes | Search query. |
TDQS
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 does not say whether this is a read-only operation, how results are ordered or paginated, or any auth constraints. 'Status endpoint' is vague and arguably misleading for a search tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
It is a single short sentence, so it is not bloated, but the phrase 'Alpha mail status endpoint' is filler that occupies the front-loaded position where useful routing information should be. Efficient in length, poor in information density.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a search tool sitting among several mail siblings with no annotations and no output schema, the description is far too thin. It should at minimum explain how search differs from list, what the query matches, and what results look like.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% with only two simple parameters (query, limit), so the schema already documents everything needed. The description adds no syntax, format, or matching-semantics detail beyond the schema, which is the baseline 3 case.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States the verb (searching) and resource (mail), so the general purpose is recoverable. However, the phrase 'Alpha mail status endpoint' is muddled and adds no meaning, and nothing distinguishes it from the sibling sc_mail_list, which could plausibly be mistaken for the same capability.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this versus sc_mail_list or sc_mail_read, no mention of prerequisites, and no indication of what a search query should look like. The agent is left to guess the routing.
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.
| Name | Required | Description | Default |
|---|---|---|---|
| to | Yes | Email recipient. | |
| body | Yes | Email body text. | |
| subject | Yes | Email subject. |
TDQS
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.
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.
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.
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.
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.
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.
8 tool updates
v0.1.0-alpha.21- First observed
sc_deploy - First observed
sc_deploy_status - First observed
sc_health_check - First observed
sc_logs_analyze - First observed
sc_mail_list - First observed
sc_mail_read - First observed
sc_mail_search - First observed
sc_mail_send
TDQS
Scored across 8 tools
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.
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.
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.
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
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