de en es ja ko ru zh

ai-disk-doctor-integrations

Name: ai-disk-doctor-integrations
Author: quzhiii

by quzhiii

Overview Schema Source Related Servers Discussions Admin

JavaScript

Local

AI Disk Doctor Integraciones

Agent Skill local universal y servidor MCP de solo lectura para AI Disk Doctor Core.

Este repositorio es una capa de integración y distribución. No implementa un segundo escáner, limpiador, motor de riesgos, modelo de recuperación ni sistema de políticas. El Core local sigue siendo la fuente de ejecución y de políticas.

Alcance Alpha

El servidor MCP expone cuatro herramientas:

Herramienta	Comportamiento	Efecto secundario en Core
`core_status`	Comprueba la disponibilidad de Core y la superficie de comandos requerida	Ninguno
`scan_summary`	Ejecuta el contrato existente de `aidisk scan --json`	Core puede guardar `.aidisk/reports/scan-*.json`
`ai_model_inventory`	Ejecuta el contrato existente de `aidisk models inventory --json`	Ninguno previsto
`scan_history`	Lista los metadatos de instantáneas locales propiedad de Core	Ninguno

I0 no expone ninguna herramienta de clean, restore, quarantine, delete, shell arbitrario o mutación arbitraria del sistema de archivos. explain_storage no se incluye intencionadamente hasta que el M1C Explainability Contract fusionado esté disponible en el Core público.

Related MCP server: local-tools-mcp-server

Instalación

Requisitos previos

Node.js 18 o superior.
AI Disk Doctor Core v1.7.0 o un Core posterior compatible en PATH como aidisk/aidisk.exe.
Establece AIDISK_EXE cuando el binario de Core esté instalado en otra ubicación.

Instalar desde un checkout:

git clone https://github.com/quzhiii/ai-disk-doctor-integrations.git
cd ai-disk-doctor-integrations
npm install
npm start

Para una instalación local determinista, fija el checkout del repositorio o usa una release etiquetada. La dependencia npm está fijada a @modelcontextprotocol/sdk 1.30.0 en package-lock.json.

El proceso usa el transporte stdio de MCP y debe ser iniciado por un cliente MCP, no abierto como programa interactivo independiente.

OpenCode

OpenCode admite declaraciones MCP locales de proyecto en opencode.json o opencode.jsonc:

{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "ai-disk-doctor": {
      "type": "local",
      "command": ["node", "C:/absolute/path/to/ai-disk-doctor-integrations/src/server.js"],
      "cwd": "C:/absolute/path/to/your-workspace",
      "enabled": true
    }
  }
}

Para una instalación global, usa rutas absolutas para los argumentos de command y establece AIDISK_EXE en environment si es necesario. Establece cwd en el espacio de trabajo del usuario donde deban almacenarse las instantáneas de Core, en lugar del checkout de integración. Luego usa opencode mcp list o pide al agente que compruebe core_status. El ejemplo incluido está en adapters/opencode/opencode.jsonc.

Las Agent Skills de OpenCode se descubren desde .opencode/skills, .claude/skills o .agents/skills. Copia o crea un enlace simbólico de skills/ai-disk-doctor en una de esas ubicaciones para una instalación de proyecto o de usuario.

Qwen Code

Qwen Code admite servidores MCP stdio locales mediante qwen mcp o settings.json:

qwen mcp add --scope user --transport stdio ai-disk-doctor node ./src/server.js

Entrada equivalente en .qwen/settings.json:

{
  "mcpServers": {
    "ai-disk-doctor": {
      "command": "node",
      "args": ["/absolute/path/to/ai-disk-doctor-integrations/src/server.js"],
      "cwd": "/absolute/path/to/your-workspace",
      "env": { "AIDISK_EXE": "aidisk" },
      "trust": false
    }
  }
}

La raíz del repositorio es un paquete de extensión de Qwen a través de su qwen-extension.json. Instala el repositorio como extensión local después de npm install; consulta adapters/qwen/README.md. La Skill canónica sigue siendo la misma Skill, no una implementación de gobernanza específica de Qwen.

CodeBuddy / WorkBuddy

Usa la superficie de configuración MCP local compatible con el producto instalado y apúntala al mismo proceso stdio node ./src/server.js. Establece su directorio de trabajo en el espacio de trabajo donde deba residir el historial de instantáneas de Core. No se incluye ninguna persona Expert ni lógica de riesgo específica del proveedor. El empaquetado exacto se pospone hasta que exista un contrato de cliente CodeBuddy / WorkBuddy oficial y comprobable localmente; consulta adapters/codebuddy/README.md.

TRAE

Usa la configuración MCP de proyecto documentada de TRAE y añade el mismo proceso stdio local. Establece su directorio de trabajo en el espacio de trabajo donde deba residir el historial de instantáneas de Core. El empaquetado exacto del proyecto se pospone hasta que un cliente TRAE esté disponible localmente para su validación; consulta adapters/trae/README.md.

Diagnóstico de Core

# Verify the Core directly
aidisk --help

# Verify the integration server syntax
npm run check

# Override the Core executable
# Windows PowerShell:
$env:AIDISK_EXE = 'C:\\Tools\\aidisk.exe'
# POSIX shells:
export AIDISK_EXE=/opt/aidisk

Si Core falta o devuelve una salida malformada/incompatible, core_status informa de un fallo estructurado. El proceso MCP no descarga Core, no clona repositorios, no contacta con un servicio en la nube ni sustituye silenciosamente a otro escáner.

Límite de seguridad

El transporte MCP es solo stdio local.
El servidor inicia únicamente el ejecutable aidisk configurado con subcomandos fijos orientados a lectura.
No existe ninguna herramienta de shell arbitrario ni de comando arbitrario.
No existe ninguna herramienta de limpieza, ejecución de cuarentena, restauración, eliminación o mutación.
scan_summary está marcado como readOnlyHint: false porque la persistencia actual de escaneos de Core puede escribir una instantánea propiedad de AI Disk Doctor. Sigue siendo destructiveHint: false y no modifica archivos de usuario o del espacio de trabajo.
El inventario de modelos contiene solo metadatos según el contrato de Core; esta integración no lee contenido de prompts, transcripciones, fuentes, documentos, tokens, cookies ni credenciales.
Las rutas proporcionadas a las herramientas se pasan únicamente al comando de Core correspondiente o al lector de metadatos de historial. Esta integración no las lee recursivamente.

Los agentes nunca deben eludir estas reglas eliminando rutas con comandos de shell. Si se aprueba un flujo de mutación futuro, debe usar una superficie de autorización separada.

Desarrollo

npm install
npm run check
npm test

Para una prueba de humo real de Core, instala/compila la revisión fijada de Core, pon aidisk en PATH o establece AIDISK_EXE, y ejecuta npm test. La prueba con Core real se omite cuando AIDISK_EXE no está establecido. El resto de pruebas de protocolo usan directorios temporales y un caso con Core ausente; no simulan que los clientes del proveedor estén instalados.

Licencia

El código fuente de la integración tiene doble licencia MIT o Apache-2.0. Consulta LICENSE-MIT y LICENSE-APACHE. La licencia de Core sigue regulada por el repositorio público de Core.

Estado

I0 Alpha. Este repositorio no es el Desktop comercial y no contiene cuentas, facturación, derechos de uso, telemetría, sincronización en la nube ni código propietario de Desktop.

Available Tools

4 tools

ai_model_inventoryAI Model And Cache InventoryA

Read-onlyIdempotent

Use AI Disk Doctor's existing metadata-only model inventory with Core defaults and return a bounded asset projection. It does not read model, prompt, source, token, or credential contents and does not mutate files.

ParametersJSON Schema

Name	Required	Description	Default
`tool`	No	Optional Core inventory tool selector.

Output Schema

ParametersJSON Schema

Name	Required	Description
`ok`	Yes
`tool`	Yes
`roots`	Yes
`assets`	Yes
`summary`	Yes
`truncated`	Yes
`provenance`	Yes
`generated_at`	No
`total_assets`	Yes
`schema_version`	No
`returned_assets`	Yes
`stale_after_days`	No

TDQS

A3.8/5.0

Behavior4/5

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

Annotations already provide readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds key behavioral context: it explicitly states 'does not read model, prompt, source, token, or credential contents' and 'does not mutate files.' This goes beyond the hints by specifying what is not read and what is not mutated, which is valuable for the agent. No contradiction with annotations.

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 a single, concise sentence that states purpose, scope, and key behavioral constraints. It is front-loaded with the action ('return a bounded asset projection') and includes critical exclusions. Every clause earns its place, with no fluff.

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?

Given that the tool has an output schema (which presumably describes the return projection), the description doesn't need to explain return values. The tool is simple (1 optional parameter) and has strong annotations. The description covers behavior and constraints well. It is complete enough for the agent to understand what the tool does and what it avoids. The only minor gap is not providing more context on when to use it vs. siblings, but given the simplicity, a 4 is justified.

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%, meaning the schema documents the 'tool' parameter with its enum values. The description adds context by saying 'Optional Core inventory tool selector,' but this is largely redundant with the schema's 'Optional Core inventory tool selector' description. Since the schema already covers the parameter well, the description adds minimal extra meaning, but it does reinforce the optionality, so a baseline 3 is appropriate.

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 clearly states that the tool returns a 'bounded asset projection' using 'AI Disk Doctor's existing metadata-only model inventory with Core defaults.' It specifies the resource (model inventory) and the action (return a projection), which is clear enough. However, it does not explicitly distinguish from sibling tools like scan_summary or core_status, though the resource and action are specific enough to imply differentiation.

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?

The description implies usage by stating it uses 'Core defaults' and an optional tool selector, but it does not provide explicit when-to-use guidance or mention alternatives. It doesn't say when to use this tool vs. siblings, but the context of a metadata-only inventory is somewhat clear. The guidance is implied rather than explicit, so it earns a 3.

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

core_statusAI Disk Doctor Core StatusA

Read-onlyIdempotent

Check local AI Disk Doctor Core availability, required command surface, semantic version, and compatibility provenance without scanning or modifying files.

ParametersJSON Schema

Name	Required	Description	Default
No parameters

Output Schema

ParametersJSON Schema

Name	Required	Description
`ok`	Yes
`core`	Yes
`server`	Yes

TDQS

A4.3/5.0

Behavior4/5

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

The description adds contextual detail beyond the annotations by listing specific aspects checked (availability, command surface, semantic version, compatibility provenance) and explicitly reaffirms non-invasive behavior. Annotations already declare readOnly and idempotent, so the description enhances rather than contradicts them.

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, well-structured sentence conveys all essential details without redundancy. Every phrase earns its place, and the sentence is front-loaded with the primary action and resource.

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

Completeness5/5

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

Given the tool is low-complexity (no parameters) and an output schema exists, the description sufficiently covers what the tool checks (availability, command surface, version, provenance) and its side-effect-free nature. It is complete for an information-only status check.

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

Parameters4/5

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

The tool has no parameters and the schema is fully covered. Since there are no parameters to describe, the description is not expected to elaborate on them, and the zero-parameter baseline of 4 is appropriate.

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

Purpose5/5

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

The description uses a clear verb ('Check') with a specific resource ('local AI Disk Doctor Core availability, required command surface, semantic version, and compatibility provenance'). It differentiates from sibling tools like scan_summary and ai_model_inventory by emphasizing it does not scan or modify files.

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?

The description implies this is a safe read-only status check but does not explicitly state when to choose it over alternatives. It notes it avoids scanning and modifying, which hints at contrast with scan_summary, but lacks explicit when-to-use or when-not-to-use guidance.

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

latest_diffAI Disk Doctor Latest DiffA

Read-onlyIdempotent

Use Core-owned latest snapshot discovery and diff semantics through aidisk diff --latest --json. No reports directory or paths are accepted from the model.

ParametersJSON Schema

Name	Required	Description	Default
No parameters

Output Schema

ParametersJSON Schema

Name	Required	Description
`ok`	Yes
`tool`	Yes
`after`	No
`before`	No
`changes`	Yes
`summary`	Yes
`truncated`	Yes
`provenance`	Yes
`generated_at`	No
`total_changes`	Yes
`returned_changes`	Yes

TDQS

A4.4/5.0

Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true. The description adds no contradictory information; it explains that the tool uses Core-owned semantics and the `--latest --json` options, which is additional context beyond the annotations, though it doesn't describe side effects because there are none.

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 concise, consisting of two sentences that are front-loaded with the purpose and immediately state the key constraint (no paths accepted). Every word adds value.

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?

Given the tool has no parameters, an output schema exists (though not detailed), and annotations cover safety traits, the description is complete for its purpose. It might benefit from clarifying the return format, but the output schema presumably handles that, so this is adequate.

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

Parameters4/5

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

The tool has zero parameters, and the schema description coverage is 100%, meaning no parameters need explanation. The description clarifies the inherent behavior (using latest snapshot and JSON output) without needing to describe parameter semantics, so it adequately handles the absence of parameters.

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

Purpose5/5

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

The description clearly states the tool performs 'Core-owned latest snapshot discovery and diff semantics' via the `aidisk diff --latest --json` command, which is a specific verb and resource. It distinguishes itself from siblings by indicating it uses Core-owned semantics and does not accept paths or reports directories.

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

Usage Guidelines4/5

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

The description implies when to use this tool: when the model needs the latest diff using Core-owned discovery. It explicitly notes that no reports directory or paths are accepted, which guides usage, but does not explicitly contrast with sibling tools such as scan_summary or ai_model_inventory.

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

scan_summaryAI Disk Doctor Scan SummaryA

Run AI Disk Doctor's existing non-destructive scan and return a bounded projection of Core JSON evidence. The current Core CLI may persist an AI Disk Doctor-owned snapshot under .aidisk/reports; it does not mutate user files.

ParametersJSON Schema

Name	Required	Description	Default
`category`	No	Optional Core rule category filter. The integration validates only bounds; Core owns category semantics.

Output Schema

ParametersJSON Schema

Name	Required	Description
`ok`	Yes
`tool`	Yes
`policy`	No
`summary`	Yes
`volumes`	Yes
`scan_time`	No
`truncated`	Yes
`provenance`	Yes
`top_findings`	Yes
`total_findings`	Yes
`returned_findings`	Yes

TDQS

A4.5/5.0

Behavior5/5

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

Description goes beyond annotations by explicitly disclosing non-destructive behavior, no mutation of user files, and potential snapshot persistence under .aidisk/reports. Annotations have readOnlyHint: false, but description clarifies safety profile, adding significant value.

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?

Two sentences efficiently convey purpose, scope, side effects, and safety. No redundant phrasing or filler; carefully front-loaded with the core action and outcome.

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

Completeness5/5

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

For a single optional parameter tool with output schema present, description covers purpose, return projection, side effects, and guarantees about user files. Includes relevant environmental detail (CLI snapshot). Complete enough for agent to safely invoke.

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?

The only parameter 'category' has full schema description (100% coverage) explaining it as an optional Core rule category filter with bounds validation. The tool description does not add extra semantics, but schema already provides adequate meaning, so baseline 3 is appropriate.

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

Purpose5/5

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

Description uses specific verb 'Run' with clear resource 'AI Disk Doctor's existing non-destructive scan' and states output 'bounded projection of Core JSON evidence'. It clearly distinguishes from siblings (core_status, ai_model_inventory, latest_diff) by focusing on scan execution and non-destructiveness.

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

Usage Guidelines4/5

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

States when to use (run scan) and provides context about non-destructive nature, but does not explicitly mention alternatives or when not to use. Sibling tools are present, but no comparative guidance given. Clear purpose implies usage context, but no exclusions.

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.

4 tool updatesv0.1.0-alpha.2Aug 20, 2026
- First observedai_model_inventory
- First observedcore_status
- First observedlatest_diff
- First observedscan_summary

Deploy Server

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

A4.1/5.0

Scored 2026-08-20 15:31 across 4 tools

Disambiguation5/5

Each tool has a clearly distinct purpose: scan_summary runs a scan, core_status checks the Core installation, ai_model_inventory lists models, and latest_diff computes diffs. No overlap or ambiguity in their responsibilities.

Naming Consistency3/5

All names are lowercase snake_case, but they do not follow a consistent verb_noun pattern. scan_summary starts with a verb, while core_status, ai_model_inventory, and latest_diff are noun-led or adjective-noun, creating slight inconsistency.

Tool Count4/5

With 4 tools, the set is small but well-focused on the disk doctor integration's core needs: scanning, status, inventory, and diffing. It is neither bloated nor insufficient for the stated purpose.

Completeness4/5

The tools cover primary operations (scan, check status, list models, diff latest snapshots), but lack explicit snapshot management or detailed per-file reporting. Minor gaps that an agent could potentially work around.

Maintenance

ActivitySlowing

ResponsivenessNo issues

Resources

GitHub Repository

Need Help?

Related Servers

Related MCP Connectors

ORANO Personal Context MCP
io.github.manuvamp
Read-only MCP server: let AI agents read your ORANO saved-video library, tasks, and memory.
Knowledge & Memory Entertainment & Media Project Management
1
ORANO MCP Server
io.github.infotik
Read-only MCP server exposing a user ORANO library to their own AI agent.
Note Taking Knowledge & Memory Search
1
operant-mcp A
io.github.saagpatel
Read-only MCP server for the OPERANT AI operating-agent calibration benchmark.
Autonomous Agents Agent Orchestration Testing & QA Tools
52
ovanek-mcp
io.github.yofor
Ovanek MCP: Model Context Protocol server for Ovanek platform tools; writes are dry-run by default.
1

Related MCP Servers

CodeAudit MCP
Code Analysis Testing & QA Tools Developer Tools
priyanshuchawda
A
license
Not graded
quality
C
maintenance
A read-only MCP server for AI coding agents to inspect repositories, audit code quality, route engineering skills, and plan safe issue/PR workflows.
Updated 5 months ago (2026-05-04 04:27 UTC)
1
MIT
local-tools-mcp-server
fenhuayue
F
license
A
quality
D
maintenance
A read-only MCP server that enables AI assistants to search files, list directories, retrieve system info, and get file metadata on the local file system.
Updated 3 months ago (2026-07-20 09:22 UTC)
4
-
autopsy-mcp
Databases Search File Systems
th0r10293847
A
license
Not graded
quality
C
maintenance
Read-only MCP server that exposes Autopsy digital forensics case data as tools, enabling LLM clients like Cline to browse filesystems, query artifacts, and search keywords without modifying the case.
Updated 2 months ago (2026-08-07 13:16 UTC)
1
MIT
Sumi-Docs-MCP
Documentation Access Search RAG Systems
starSumi
A
license
Not graded
quality
B
maintenance
Read-only MCP server for Markdown, MDX, and OpenAPI docs, exposing list, search, fetch, and OpenAPI spec tools over stdio.
Updated a month ago (2026-09-09 10:43 UTC)
1
MIT