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Convierte URLs sin procesar en éxitos virales. Porque escribir publicaciones manualmente es tan de 2025.
ViralTransformer es un servidor MCP de alto rendimiento que convierte a Claude en un hacker de crecimiento de redes sociales 24/7. No solo extrae información; piensa, analiza y redacta.
Característica | Descripción |
El comando "Remake" | Dale a Claude una URL y di "remake this"Reescritura con un clic: dale a Claude un enlace y obtén directamente borradores comerciales profundos y contenido viral emocional |
Salida de doble versión | Obtén "Deep Insight" para LinkedIn y "High-Energy" para X/Redes SocialesDoble salida: genera simultáneamente observaciones profundas para LinkedIn y contenido viral emocional para X/Xiaohongshu |
Borradores locales | Guarda automáticamente cada idea genial en |
Related MCP server: MCP Google Maps
Cada ⭐ desbloquea una nueva capacidad creativa.
Estrellas | Logro |
⭐50 | El Maestro del Roast — La IA reescribe noticias con sarcasmo extremo |
⭐188 | Cyberpunk 2077 — Narrativa de cine negro tecnológico |
⭐300 | El Maestro de lo Abstracto — Estilo de "locura" posmoderna |
⭐520 | Perfil de "Cita a ciegas" — Noticias como una biografía de cita de alto nivel |
⭐888 | "El Agente Secreto" — Monitoreo automático de competidores |
FastMCP: Framework de Python de alto rendimiento para MCP.
Httpx: Motor asíncrono para una rápida recuperación de contenido.
BeautifulSoup4: Análisis robusto de HTML.
Pydantic: Garantiza una estricta seguridad de tipos y salidas de datos estructurados.
Python 3.10+
uv (Recomendado para la gestión de dependencias)
# Clone the repository
git clone https://github.com/BelleKou/mcp-viral-transformer.git
cd mcp-viral-transformer
# Install dependencies (Modern way)
uv pip install -e .
# Or the traditional way
pip install -r requirements.txtPara usar este servidor, necesitas una API Key de Anthropic. Configúrala en tu entorno:
ANTHROPIC_API_KEY: Tu clave de la consola de Anthropic.
Añade lo siguiente a tu claude_desktop_config.json:
{
"mcpServers": {
"viral-transformer": {
"command": "uv",
"args": [
"run",
"--with", "mcp",
"mcp", "run",
"/your/path/to/mcp-viral-transformer/server.py"
]
}
}
}⚠️ Reemplaza la ruta con tu ruta local real.
Fuente: Anthropic's $30B Compute Deal
Archivo generado: 📄 drafts/anthropic_30b.md
⚡️ LA HEGEMONÍA DE CÓMPUTO DE $30 MIL MILLONES: ANTHROPIC X GOOGLE X BROADCOM
🏛️ Versión A: Perspectiva profesional
Título: La muerte de la IA ligera en activos: La apuesta de integración vertical de Anthropic
La reciente asociación de $30 mil millones entre Anthropic, Google y Broadcom marca un cambio tectónico. Nos estamos alejando de la "Supremacía de Algoritmos" hacia la "Soberanía de Cómputo".
El pivote de hardware: Codiseñar ASICs con Broadcom para evitar el cuello de botella de NVIDIA.
Foso de infraestructura: Las leyes de escala ahora requieren una relación directa con la red eléctrica.
🚀 Versión B: Viral de alta energía
Título: $30 MIL MILLONES. Ese es el precio de entrada para la carrera de la AGI. 💸
Mientras todos discuten sobre prompts, Anthropic acaba de comprar el edificio. Y los chips. Y las líneas eléctricas.
🔮 ÁNGULO ÚNICO
La IA está pasando de ser software a una "Utilidad Digital". En 2026, la empresa de IA líder se parecerá menos a Microsoft y más a una combinación de TSMC y conglomerados energéticos.
Fuente: 36Kr - 吉利沃飞长空 IPO
Archivo generado: 📄 drafts/sky_economy.md
🚁 ¡11 OPIs! La última pieza del rompecabezas del "loco de los coches": la economía de baja altitud no es un sueño, es un negocio.
🏛️ Versión A: Observación comercial profunda
Título: De la "carretera bidimensional" al "espacio tridimensional": La estrategia de capital de Volant Aerotech
El inicio de la asesoría para la OPI de Volant Aerotech marca la entrada de la "economía de baja altitud" en la fase de cosecha de capital. Esto no es solo fabricar coches voladores, es la reconstrucción de la soberanía del espacio urbano.
🚀 Versión B: Contenido viral emocional
Título: ¡Deja de atascarte en el suelo! ¿Salir y tomar un "taxi aéreo" en solo 10 minutos? 💸
¡Las "locuras" de las que se burlaban antes ahora son realidad! El cielo se convierte oficialmente en un "carril", la era del transporte a baja altitud ha llegado. No venden aviones, venden el "privilegio de evitar el tráfico".
🔮 ÁNGULO ÚNICO
La estratificación de la soberanía del tiempo: en 2026, la estratificación de clases se reflejará en el "derecho de acceso vertical". Los 300 metros de altura que ocupa Volant Aerotech son la interpretación definitiva del orden urbano de los próximos 50 años.
.
├── server.py # Core MCP logic
├── LICENSE # MIT License
├── requirements.txt # Project dependencies
├── drafts/ # Generated markdown posts (Output)
└── README.md # DocumentationBajo la Licencia MIT. Abierto para modificación y uso personal.
Saves content with a safe filename to the /drafts folder.
| Name | Required | Description | Default |
|---|---|---|---|
| filename | Yes | ||
| content | Yes |
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states 'saves content' (implying a write operation) and mentions a 'safe filename', but doesn't clarify permissions, error handling, or what 'safe' entails. This leaves significant gaps for a mutation 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, efficient sentence that directly states the tool's action and destination. It's front-loaded with the core purpose and has no wasted words, making it highly concise and well-structured.
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 an output schema (which reduces the need to describe return values) but no annotations and 0% schema coverage, the description is minimally adequate. It covers the basic action and location but lacks details on behavior and parameters, making it incomplete for a mutation tool with undocumented inputs.
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 0%, so the description must compensate. It mentions 'safe filename' and '/drafts folder', which adds some context for the 'filename' parameter, but doesn't explain 'content' or provide details on filename safety rules. This partial compensation is insufficient for the 2 undocumented parameters.
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 ('Saves content') and target ('to the /drafts folder'), with the verb 'saves' being specific. However, it doesn't differentiate from the sibling tool 'scrape_article' (which appears unrelated), so it doesn't fully earn a 5.
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. It mentions saving to '/drafts folder' but doesn't specify use cases, prerequisites, or exclusions, leaving the agent with minimal context for decision-making.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Scrapes clean content from a URL, focusing on the main article body.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes |
| Name | Required | Description |
|---|---|---|
| result | Yes |
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 states the tool scrapes clean content and focuses on the main article body, which hints at behavior like content cleaning and body extraction. However, it lacks details on error handling, rate limits, authentication needs, or what 'clean' entails, leaving significant gaps for a tool with no annotation coverage.
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 action and focus. Every word earns its place, with no redundancy or unnecessary elaboration, making it highly concise and well-structured.
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 an output schema (which covers return values), no annotations, and a simple input schema, the description is minimally adequate. It specifies the tool's focus on article body content, but for a scraping tool with no behavioral annotations, it could benefit from more context on limitations or expected output format.
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 does not mention the 'url' parameter explicitly, but with only 1 parameter and 0% schema description coverage, it compensates by implying the parameter's purpose through context ('from a URL'). This adds meaning beyond the bare schema, though it doesn't detail format or constraints, keeping it from a perfect 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 clearly states the verb ('scrapes') and resource ('clean content from a URL'), specifying it focuses on the main article body. This distinguishes it from generic scraping tools, though it doesn't explicitly differentiate from the sibling 'save_draft' tool, which appears unrelated.
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, such as other scraping methods or tools. It mentions focusing on the main article body, which implies a context for article content extraction, but lacks explicit when/when-not instructions or named alternatives.
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.
v1.0.0save_draftscrape_articleScored across 2 tools
The two tools have completely distinct purposes: save_draft handles local file saving with safe naming, while scrape_article extracts clean content from URLs. There is no overlap in functionality or ambiguity between them.
Both tools follow a consistent verb_noun pattern (save_draft, scrape_article) with clear, descriptive names that align well with their functions. The naming style is uniform and predictable.
With only two tools, the server feels thin and under-scoped for a 'ViralTransformer' purpose, which implies content transformation or viral content handling. This minimal set limits functionality and suggests incomplete coverage of the domain.
The tool set is severely incomplete for a viral content transformation server. It lacks core operations like content generation, editing, publishing, analytics, or social media integration, leaving significant gaps that will hinder agent workflows.
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Connect any AI agent to 11+ social platforms: schedule, publish & track posts via hosted MCP.
