Un servidor de Protocolo de Contexto de Modelo (MCP) que proporciona una interfaz fluida para la gestión de correo electrónico a través de Claude. Esta integración permite gestionar correos electrónicos directamente mediante conversaciones en lenguaje natural con Claude, lo que permite funciones como la búsqueda, la lectura y el envío seguro de correos electrónicos.
📧 Buscar correos electrónicos por rango de fechas y palabras clave
📅 Ver estadísticas diarias de correo electrónico
📝 Lea el contenido completo del correo electrónico con soporte para subprocesos
✉️ Enviar correos electrónicos con soporte para destinatarios CC
Manejo seguro de correo electrónico con TLS
Related MCP server: IMAP MCP Server
Python 3.12 o superior
Una cuenta de Gmail (u otro proveedor de correo electrónico)
Si usa Gmail:
Autenticación de dos factores habilitada
Aplicación de escritorio Claude
Instalar uv:
# MacOS/Linux
curl -LsSf https://astral.sh/uv/install.sh | sh
# Remember to restart your terminal after installationClonar y configurar el proyecto:
# Clone the repository
git clone https://github.com/ZilongXue/claude-post.git
cd claude-post
# Create and activate virtual environment
uv venv
source .venv/bin/activate # On Windows: .venv\Scripts\activate
# Install dependencies
uv pip install -e .Cree un archivo .env en la raíz del proyecto:
EMAIL_ADDRESS=your.email@gmail.com
EMAIL_PASSWORD=your-app-specific-password
IMAP_SERVER=imap.gmail.com
SMTP_SERVER=smtp.gmail.com
SMTP_PORT=587Configurar Claude Desktop:
Primero, asegúrate de tener instalado Claude para Escritorio. Puedes instalar la última versión aquí . Si ya tienes Claude para Escritorio, asegúrate de tener la última versión.
Abra el archivo de configuración de Claude Desktop:
# MacOS
~/Library/Application Support/Claude/claude_desktop_config.json
# Create the file if it doesn't exist
mkdir -p ~/Library/Application\ Support/Claude
touch ~/Library/Application\ Support/Claude/claude_desktop_config.jsonAgregue la siguiente configuración:
{
"mcpServers": {
"email": {
"command": "/Users/username/.local/bin/uv",
"args": [
"--directory",
"/path/to/claude-post/src/email_client",
"run",
"email-client"
]
}
}
}Reemplace /Users/username y /path/to/claude-post con sus rutas reales.
Después de actualizar la configuración, reinicie Claude Desktop para que los cambios surtan efecto.
El servidor se ejecuta automáticamente a través de Claude Desktop:
El servidor se iniciará cuando se inicie Claude si está configurado correctamente
No es necesaria la gestión manual del servidor
El servidor se detiene cuando se cierra Claude
Puedes interactuar con tus correos electrónicos mediante comandos de lenguaje natural. Aquí tienes algunos ejemplos:
"Muéstrame los correos electrónicos de la semana pasada"
"Buscar correos electrónicos con el asunto 'reunión'"
Búsqueda de correos electrónicos de recruiting@linkedin.com entre el 01/01/2024 y el 07/01/2024
"Buscar correos electrónicos enviados del último mes"
"Muéstrame el contenido del correo electrónico n.° 12345"
"¿Cuál es el mensaje completo del último correo electrónico de RR.HH?"
¿Cuántos correos electrónicos recibí hoy?
"Muéstrame el recuento diario de correos electrónicos de la última semana"
Quiero enviar un correo electrónico a john@example.com
Enviar confirmación de reunión a team@company.com
Nota: Por razones de seguridad, Claude siempre le mostrará los detalles del correo electrónico para confirmación antes de realizar el envío.
claude-post/
├── pyproject.toml
├── README.md
├── LICENSE
├── .env # Not included in repo
├── .python-version # Python version specification
└── src/
└── email_client/
├── __init__.py
├── __main__.py
└── server.py # Main implementationUtilice contraseñas específicas de la aplicación en lugar de la contraseña de su cuenta principal
Para usuarios de Gmail:
Habilite la verificación en dos pasos en su cuenta de Google
Generar una contraseña de aplicación para esta aplicación
Utilice la contraseña de la aplicación en su archivo .env
La aplicación registra información detallada en email_client.log . Consulte este archivo para obtener información de depuración y mensajes de error.
Este proyecto está licenciado bajo la licencia MIT: consulte el archivo de LICENCIA para obtener más detalles.
Count emails received for each day in a date range
| Name | Required | Description | Default |
|---|---|---|---|
| end_date | Yes | End date in YYYY-MM-DD format | |
| start_date | Yes | Start date in YYYY-MM-DD format |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, description carries full burden. It does not disclose scope (e.g., all folders, spam), side effects, rate limits, or output format. Minimal behavioral context beyond the basic operation.
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?
Single sentence, zero waste, front-loaded with verb and resource.
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?
Missing output format (array of date-count objects), scope (which mailbox), and assumptions about missing days. No output schema to compensate.
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%, so baseline is 3. Description adds no extra meaning beyond schema; it implies date range but doesn't clarify inclusive/exclusive bounds or format validation.
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 'Count emails received for each day in a date range' uses a specific verb ('count') and resource ('emails') and clearly distinguishes from sibling tools like 'search-emails' or 'send-email'.
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 tool versus alternatives. It does not mention when not to use it or compare to other tools like 'search-emails' for broader queries.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get the full content of a specific email by its ID
| Name | Required | Description | Default |
|---|---|---|---|
| email_id | Yes | The ID of the email to retrieve |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description must carry the full burden. It says 'full content' but does not specify whether that includes attachments, headers, or metadata. No mention of permissions, rate limits, or destructive potential.
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, clear sentence with no redundant words. It is front-loaded with the action and resource.
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 low complexity (1 parameter, no output schema), the description is minimally adequate but lacks details on what 'full content' includes. It does not compensate for the missing output schema.
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 the description adds no additional meaning beyond what the schema already provides for email_id. It does not specify the format or source of the ID.
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 action (Get), resource (full content of an email), and the identifier (by its ID). It distinguishes from siblings like search-emails (which lists) and forward-email (which sends).
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 tool versus alternatives, such as after using search-emails to find an email ID, or what prerequisites exist (e.g., email must exist).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Search emails within a date range and/or with specific keywords
| Name | Required | Description | Default |
|---|---|---|---|
| end_date | No | End date in YYYY-MM-DD format (optional) | |
| folder | No | Folder to search in ('inbox' or 'sent', defaults to 'inbox') | |
| keyword | No | Keyword to search in email subject and body (optional) | |
| start_date | No | Start date in YYYY-MM-DD format (optional) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions search functionality but lacks critical details: it doesn't specify whether this is a read-only operation, what permissions are required, how results are returned (e.g., pagination, format), or any rate limits. For a search tool with zero annotation coverage, this is a significant gap.
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, efficient sentence that front-loads the core purpose ('search emails') and succinctly lists the search criteria. There's no wasted verbiage or redundancy, making it easy for an agent to parse quickly.
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 lack of annotations and output schema, the description is incomplete for a search tool. It doesn't explain what the tool returns (e.g., email summaries, IDs, full content), how results are structured, or any behavioral constraints. This leaves the agent with insufficient context to use the tool effectively beyond basic parameter input.
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 all parameters well-documented in the input schema (e.g., date formats, folder options, keyword usage). The description adds minimal value beyond the schema by implying date-range and keyword filtering but doesn't provide additional syntax or format details. This meets the baseline for high schema coverage.
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's purpose with specific verbs ('search emails') and resources ('emails'), and specifies search criteria ('within a date range and/or with specific keywords'). However, it doesn't explicitly differentiate from sibling tools like 'count-daily-emails' or 'get-email-content', which prevents a perfect score.
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 no guidance on when to use this tool versus alternatives like 'count-daily-emails' (for counting) or 'get-email-content' (for retrieving specific content). There's no mention of prerequisites, exclusions, or comparative use cases, leaving the agent to infer usage from the purpose alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
CONFIRMATION STEP: Actually send the email after user confirms the details. Before calling this, first show the email details to the user for confirmation. Required fields: recipients (to), subject, and content. Optional: CC recipients.
| Name | Required | Description | Default |
|---|---|---|---|
| cc | No | List of CC recipient email addresses (optional, confirmed) | |
| content | Yes | Confirmed email content | |
| subject | Yes | Confirmed email subject | |
| to | Yes | List of recipient email addresses (confirmed) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses the confirmation requirement and required/optional fields, which are behavioral traits. However, it doesn't mention other important aspects like authentication needs, rate limits, error handling, or what happens after sending (e.g., success confirmation, delivery status). For a mutation tool with zero annotation coverage, this leaves significant gaps.
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 appropriately sized and front-loaded with the most critical information (confirmation step and required fields). Every sentence earns its place by providing essential workflow guidance and parameter information without redundancy or unnecessary elaboration.
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 this is a mutation tool with no annotations and no output schema, the description should do more. It covers the confirmation workflow and parameter basics adequately, but lacks information about what happens after sending (response format, success indicators, error conditions). For a tool that performs an irreversible action like sending emails, this represents a meaningful gap in completeness.
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 fully documents all 4 parameters. The description adds minimal value by listing required fields (to, subject, content) and optional CC recipients, but doesn't provide additional semantic context beyond what's in the schema descriptions (e.g., format expectations, constraints). Baseline 3 is appropriate when the schema does the heavy lifting.
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 specific action ('send the email') and resource ('email'), distinguishing it from sibling tools like count-daily-emails, get-email-content, and search-emails which are read-only operations. It explicitly mentions the tool's role in the email workflow.
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 explicit guidance on when to use this tool: 'after user confirms the details' and 'Before calling this, first show the email details to the user for confirmation.' It clearly establishes a prerequisite workflow step, distinguishing it from alternatives that might send emails without confirmation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
v1.0.0count-daily-emailsget-email-contentsearch-emailssend-emailScored across 4 tools
Each tool has a clearly distinct purpose with no overlap: count-daily-emails aggregates email statistics, get-email-content retrieves a specific email's full content, search-emails finds emails based on criteria, and send-email handles email composition and sending. The descriptions clearly differentiate their functions, making misselection unlikely.
The tool names follow a consistent verb-noun pattern with hyphens (e.g., count-daily-emails, get-email-content), which is readable and predictable. The minor deviation is that send-email uses a simpler noun form (email instead of email-content or similar), but this does not break the overall consistency significantly.
With 4 tools, this server is well-scoped for email management, covering key operations: counting, retrieving, searching, and sending emails. Each tool earns its place by addressing a distinct aspect of the domain without being overly sparse or bloated.
The tool set provides good coverage for core email workflows, including read (count, get, search) and write (send) operations. A minor gap is the lack of update or delete tools for managing existing emails, but agents can work around this, and the surface is largely complete for the stated purpose.
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