OMOS-MCP
OMOS-MCP
Servidor MCP para que agentes de IA (Claude, ChatGPT, Cursor, etc.) lean documentos de proyectos en OMOS Shared Drive y respondan preguntas — cada respuesta referencia el archivo fuente con su enlace de Google Drive.
Estructura de Drive soportada:
OMOS/
├── Project A/
│ ├── Project Overview/
│ ├── Timeline/
│ ├── Design/
│ │ ├── System Flow/
│ │ ├── DB/
│ │ └── API/
│ └── BRD/
└── Project B/ ...Tools
Tool | Descripción |
| Índice de todo el Drive: todos los proyectos + todos los archivos con id y enlace (el agente lo llama primero siempre) |
| Búsqueda de texto completo en todo el Drive, con posibilidad de limitar el ámbito por proyecto/sección |
| Lee un archivo como texto — Google Docs/Sheets/Slides, PDF, .docx, .xlsx, md/text e imágenes (envía la imagen directamente al agente) |
| Reconstruye el índice inmediatamente (normalmente caché de 5 minutos) |
El agente recorrerá la búsqueda en este orden: filtrar por Nombre del Proyecto → si no encuentra, revisar Resumen del Proyecto y luego preguntar confirmación al usuario → continuar preguntando sobre Cronograma | BRD | Diseño (Flujo del Sistema / BD / API) → si la pregunta es demasiado amplia, preguntará de vuelta para reducir el ámbito (ya está incluido en las instrucciones del servidor).
Related MCP server: brkt-gdrive-mcp
Configuración única: Cuenta de servicio
El servidor accede a Drive mediante una cuenta de servicio (no es necesario que todos inicien sesión):
Ve a console.cloud.google.com → crea un proyecto nuevo (o usa uno existente)
APIs & Services → Library → busca Google Drive API → haz clic en Enable
IAM & Admin → Service Accounts → Create Service Account → ponle un nombre, por ejemplo
omos-mcp→ haz clic en Create (puedes saltarte el paso de rol, no es necesario asignar permisos)Entra en la cuenta de servicio creada → pestaña Keys → Add Key → Create new key → JSON → el archivo de clave se descargará
Copia el correo electrónico de la cuenta de servicio (tiene la forma
omos-mcp@<project>.iam.gserviceaccount.com) y comparte el Shared Drive / carpeta OMOS con este correo como ViewerEncuentra el folder id de la raíz de OMOS: abre la carpeta en el navegador y mira la URL
https://drive.google.com/drive/folders/<esto es el id>
Variables de entorno
Variable | Descripción |
| folder id de la raíz de OMOS (del paso 6) — obligatorio |
| Contenido completo del archivo JSON de clave, o ruta al archivo — obligatorio |
| (modo HTTP) token bearer que el cliente debe enviar |
| Tiempo de vida de la caché del índice en segundos (por defecto 300) |
| (modo HTTP) activa el modo OAuth para Claude.ai / ChatGPT web |
| (modo HTTP) puerto de escucha (por defecto 8000) |
Ejecutar localmente
Instala uv primero (curl -LsSf https://astral.sh/uv/install.sh | sh)
1) Configurar .env (el servidor lo carga automáticamente desde la raíz del repositorio):
cp .env.example .envEdita .env e introduce OMOS_ROOT_FOLDER_ID y la ruta al archivo de clave (por ejemplo, coloca el archivo de clave en ./service-account.json — ya está en gitignore)
2) Conectar con Claude Code (stdio):
claude mcp add omos -- uv run --directory "/path/to/OMOS-MCP" omos-mcpClaude Desktop / Cursor / Windsurf — introduce en la configuración de MCP:
{
"mcpServers": {
"omos": {
"command": "uv",
"args": ["run", "--directory", "/path/to/OMOS-MCP", "omos-mcp"]
}
}
}3) Probar: pregunta al agente "¿Qué proyectos hay en OMOS?" — debe devolver una lista de proyectos con sus enlaces.
(Opcional) Ejecutar como servidor HTTP local: activa OMOS_AUTH_TOKEN en .env y luego:
uv run omos-mcp-httpEl endpoint está en http://localhost:8000/mcp. Conéctate con:
claude mcp add --transport http omos http://localhost:8000/mcp -H "Authorization: Bearer <OMOS_AUTH_TOKEN>"Desplegar como enlace MCP (Render)
Sube este repositorio a GitHub (ya incluye
Dockerfile+render.yaml)Render → New → Blueprint → selecciona este repositorio
Configura las variables de entorno en el panel:
OMOS_ROOT_FOLDER_ID= folder id de la raíz de OMOSGOOGLE_SERVICE_ACCOUNT_JSON= contenido completo del archivo JSON de clave (pégalo directamente)OMOS_AUTH_TOKENRender lo genera aleatoriamente → cópialo para compartirlo con el equipo
Despliegue completado → el endpoint es
https://<app>.onrender.com/mcp
Los usuarios se conectan:
claude mcp add --transport http omos https://<app>.onrender.com/mcp \
-H "Authorization: Bearer <OMOS_AUTH_TOKEN>"Cursor / VS Code: introduce la URL + el header Authorization: Bearer <token> en la configuración de MCP
Para que Claude.ai / ChatGPT (web) lo use — OAuth
Los clientes web no tienen campo para cabeceras, por lo que se necesita OAuth a través de un proveedor como WorkOS AuthKit (gratuito hasta 1M de usuarios):
Regístrate en workos.com → activa AuthKit → configura el método de inicio de sesión + restringe solo al equipo
Panel → Connect → Configuration → activa Client ID Metadata Document y Dynamic Client Registration
Añade Resource Indicator =
https://<app>.onrender.com(sin/mcp)Configura 3 variables de entorno adicionales en Render:
OAUTH_ISSUER= dominio de AuthKit,OAUTH_AUDIENCE=https://<app>.onrender.com,PUBLIC_URL=https://<app>.onrender.comUsuarios: Claude.ai → Settings → Connectors → Add custom connector → introduce
https://<app>.onrender.com/mcp→ inicia sesión a través de WorkOS
El modo OAuth y el token bearer pueden coexistir — la web usa OAuth, la CLI puede seguir usando el token
Probar los convertidores
uv run python test_convert.pyAvailable Tools
4 toolsomos_indexA
Get the full index of the OMOS drive: every project and its files (with file ids and links). Use this whenever the user asks about any internal project, BRD, timeline, design, system flow, DB, API, or เอกสารโปรเจค — ALWAYS call this first, then filter by Project Name before drilling into Timeline / BRD / Design (System Flow, DB, API).
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It explicitly states the tool returns the full index of every project with file IDs and links, and implies a read-only operation (no side effects). It does not mention performance, caching, or rate limits, but the zero-parameter nature and output schema presence mitigate the need for deeper behavioral detail. The description adds meaningful context beyond the empty schema and missing annotations.
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 concise at three sentences with no wasted words. The first sentence clearly states the core purpose and what is returned. The second sentence provides specific when-to-use guidance. The third sentence prescribes the correct invocation sequence. Every sentence adds distinct value and the critical usage instructions are front-loaded.
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?
Given the tool has zero parameters and an output schema, the description covers all necessary aspects: what the tool returns (full index of projects and files with IDs and links), when to use it (specific user query scenarios), and how to use it correctly (call first, then filter by project name before drilling into details). The presence of an output schema reduces the need to describe return values, and the description's guidance is fully self-contained.
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?
The input schema has zero parameters and 100% schema coverage, meaning there is nothing for the description to add about parameters. The description correctly stays silent on parameters (there are none) and instead focuses on what the tool returns and when to use it. A slight deduction because the description could explicitly state 'no arguments required' to confirm no parameters are needed.
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 starts with a clear verb+resource combination: 'Get the full index of the OMOS drive' and immediately specifies the exact content: every project and its files with IDs and links. It thoroughly distinguishes itself from siblings like 'omos_search' by stating it returns the full unfiltered index, while also providing specific use cases where this tool should be used first.
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 explicit when-to-use guidance: 'whenever the user asks about any internal project, BRD, timeline, design, system flow, DB, API, or เอกสารโปรเจค.' It also provides a sequence: 'ALWAYS call this first, then filter by Project Name before drilling into Timeline / BRD / Design.' This effectively differentiates from omos_search (which presumably handles the filtering step) and sets clear expectations for invocation order.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
omos_readA
Read a file from the OMOS drive as text (Google Docs/Sheets/Slides, PDF, docx, xlsx, markdown/text) or as an image (png/jpg). The response starts with a citation block (file name, path, link) — always include that citation in your answer.
Args: file_id: the Drive file id from omos_index or omos_search
| Name | Required | Description | Default |
|---|---|---|---|
| file_id | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses key behaviors: it returns text or image content, starts with a citation block that must be included in answers, and accepts a Drive file ID from omos_index or omos_search. Since no annotations are provided, the description carries the full burden and provides solid behavioral context without contradictions.
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 short and well-structured: a one-sentence overview of what the tool does (including format types), then a specific instruction about the citation block, and finally a clear parameter description. Every sentence adds value, and the most critical information is front-loaded.
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?
Given the tool has only one parameter, limited schema, and no output schema, the description is complete for its simplicity. It explains the input, output format (including citation), and supported file types. A small gap is not explaining how the output type (text vs image) is determined (e.g., by file extension or a parameter).
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?
The description explains that the file_id parameter should come from omos_index or omos_search, adding meaning beyond the schema's simple type/required. With 0% schema description coverage, the description must compensate, and it does so effectively by specifying the source of valid file IDs.
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 clearly states the tool reads a file from the OMOS drive and specifies supported formats (text types and image types). The verb 'read' combined with the resource 'file from OMOS drive' provides a specific, actionable purpose that distinguishes it from sibling tools like omos_index (indexing) and omos_search (searching).
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 clear context for when to use this tool (to read a file), and implicitly distinguishes it from omos_index and omos_search which are for listing or searching. However, it does not explicitly state when NOT to use it or mention alternatives for non-file operations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
omos_refreshA
Rebuild the drive index so newly added projects/files show up immediately (the index is otherwise cached for a few minutes).
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses the caching side effect and the rebuild action, but does not mention potential costs (e.g., performance impact), whether it is asynchronous, or any required permissions. The behavior is generally clear but lacks some depth expected for an unannotated 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?
The description is a single, well-structured sentence that immediately conveys the action and purpose. No redundant words; every part earns its place.
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 parameterless tool with an output schema, the description covers the core functionality and caching behavior. It could be improved by noting typical usage scenarios (e.g., after uploads) or safe call frequency, but it is largely 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?
There are no parameters; schema description coverage is 100% by default. The description does not need to add parameter details. Baseline score of 3 is appropriate.
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 explicitly states the action ('Rebuild the drive index') and the effect ('so newly added projects/files show up immediately'). It distinguishes itself from sibling tools (index, search, read) by focusing on cache invalidation.
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 provides clear context on when to use the tool—after adding projects/files to bypass caching. It mentions the default caching behavior ('otherwise cached for a few minutes'), but does not explicitly state when not to use it or list alternative tools for similar purposes.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
omos_searchA
Full-text search across the OMOS drive. Returns matching files with project path and link; use omos_read on the ids to read content.
Args: query: keyword or phrase (searches file content and names) project: optional exact project name from omos_index to narrow the search section: optional section name (e.g. 'BRD', 'Timeline', 'Design', 'DB') to narrow further
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | ||
| project | No | ||
| section | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It accurately describes the search behavior, confirms it returns files with path and link, and mentions it searches both content and names. Could mention pagination or limits but not required for basic transparency.
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?
Two short paragraphs with minimal waste; first sentence immediately states purpose, then parameter list is clean. Every sentence adds value and is front-loaded.
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?
Given output schema exists, description need not detail return values; it still says 'Returns matching files with project path and link'. Parameter descriptions are thorough, and sibling references (omos_read, omos_index) provide complete context for usage.
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 0%, but description fully compensates by explaining each parameter's purpose: query searches content/names, project references omos_index for exact name, section gives concrete examples (BRD, Timeline, etc.). This adds significant meaning beyond the bare schema.
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?
Clearly states verb 'search' and resource 'OMOS drive', specifies full-text search, and explicitly directs to use omos_read for content retrieval, effectively distinguishing from siblings.
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?
Provides explicit guidance to use omos_read after search and mentions omos_index for project names, though it does not explicitly state when not to use this tool or describe alternatives beyond omos_read.
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 updates
v0.1.0- First observed
omos_index - First observed
omos_read - First observed
omos_refresh - First observed
omos_search
TDQS
Scored across 4 tools
Each tool has a clearly distinct purpose: omos_index provides the full index, omos_search performs full-text search with optional filters, omos_refresh rebuilds the index, and omos_read reads file content. There is no overlap or ambiguity between them.
All tools follow a consistent 'omos_<verb>' pattern (index, search, refresh, read). The naming is predictable and uniform, making it easy for an agent to understand the action each tool performs.
With 4 tools, the set is well-scoped for a drive retrieval server. Each tool addresses a necessary function (listing, searching, refreshing, reading) without being too few or excessive. The count matches the domain's core operations.
The tool surface covers the full read lifecycle for the OMOS drive: obtaining the index, searching, refreshing for updates, and reading file content. No obvious gaps exist for a retrieval-focused server; all necessary operations are present.
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