⭐ Hier klicken, um das Projekt auf GitHub zu unterstützen | Star this Project
Verwandle rohe URLs in virale Hits. Denn manuelle Beiträge zu schreiben ist so 2025.
ViralTransformer ist ein leistungsstarker MCP-Server, der Claude in einen 24/7 Social-Media-Growth-Hacker verwandelt. Er scrapt nicht nur; er denkt, analysiert und entwirft.
Funktion | Beschreibung |
Der "Remake"-Befehl | Gib Claude eine URL und sage "remake this"Ein-Klick-Überarbeitung: Gib Claude einen Link und erhalte direkt tiefgründige Business-Artikel oder emotionale virale Posts |
Dual-Version Output | Erhalte "Deep Insight" für LinkedIn und "High-Energy" für X/SocialDoppelte Ausgabe: Generiere gleichzeitig tiefgründige Analysen für LinkedIn und emotionale virale Posts für X/Xiaohongshu |
Lokale Entwürfe | Speichert jede geniale Idee sofort automatisch unter |
Related MCP server: MCP Google Maps
Jeder ⭐ schaltet eine neue kreative Fähigkeit frei.
Sterne | Errungenschaft |
⭐50 | Der Roast Master — KI schreibt Nachrichten mit extremem Sarkasmus um. |
⭐188 | Cyberpunk 2077 — Tech-Noir-Storytelling. |
⭐300 | Der Abstrakt-Meister — Postmoderner "Wahnsinns"-Stil. |
⭐520 | "Blind Date"-Profil — Nachrichten als High-End-Dating-Bio. |
⭐888 | "Der Geheimagent" — Automatische Überwachung der Konkurrenz. |
FastMCP: Leistungsstarkes Python-Framework für MCP.
Httpx: Async-First-Engine für schnellen Content-Abruf.
BeautifulSoup4: Robuste HTML-Analyse.
Pydantic: Gewährleistung strenger Typsicherheit und strukturierter Datenausgaben.
Python 3.10+
uv (Empfohlen für das Abhängigkeitsmanagement)
# 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.txtUm diesen Server zu nutzen, benötigst du einen Anthropic API Key. Setze ihn in deiner Umgebung:
ANTHROPIC_API_KEY: Dein Schlüssel aus der Anthropic-Konsole.
Füge Folgendes zu deiner claude_desktop_config.json hinzu:
{
"mcpServers": {
"viral-transformer": {
"command": "uv",
"args": [
"run",
"--with", "mcp",
"mcp", "run",
"/your/path/to/mcp-viral-transformer/server.py"
]
}
}
}⚠️ Ersetze den Pfad durch deinen tatsächlichen lokalen Pfad.
Quelle: Anthropic's $30B Compute Deal
Generierte Datei: 📄 drafts/anthropic_30b.md
⚡️ DIE $30B RECHENKRAFT-HEGEMONIE: ANTHROPIC X GOOGLE X BROADCOM
🏛️ Version A: Professionelle Einblicke
Titel: Das Ende von Asset-Light AI: Anthropics Wette auf vertikale Integration
Die kürzliche 30-Milliarden-Dollar-Partnerschaft zwischen Anthropic, Google und Broadcom markiert einen tektonischen Wandel. Wir bewegen uns weg von der "Algorithmus-Vorherrschaft" hin zur "Rechenkraft-Souveränität".
Der Hardware-Pivot: Gemeinsames Design von ASICs mit Broadcom, um den NVIDIA-Flaschenhals zu umgehen.
Infrastruktur-Burggraben: Skalierungsgesetze erfordern jetzt eine direkte Beziehung zum Stromnetz.
🚀 Version B: High-Energy Viral
Titel: 30 MILLIARDEN DOLLAR. Das ist der Eintrittspreis für das AGI-Rennen. 💸
Während alle über Prompts streiten, hat Anthropic gerade das Gebäude gekauft. Und die Chips. Und die Stromleitungen.
🔮 EINZIGARTIGER BLICKWINKEL
KI wandelt sich von Software zu einem "digitalen Versorgungsunternehmen". Im Jahr 2026 sieht das führende KI-Unternehmen weniger wie Microsoft aus und mehr wie eine Kombination aus TSMC und Energiekonzernen.
Quelle: 36Kr - Geely Aerofugia IPO
Generierte Datei: 📄 drafts/sky_economy.md
🚁 11 IPOs! Das letzte Puzzleteil des "Autoverrückten": Die Low-Altitude-Economy ist kein Traum, sondern ein Geschäft.
🏛️ Version A: Tiefgründige Business-Analyse
Titel: Von der "zweidimensionalen Straße" zum "dreidimensionalen Raum": Die Kapitalstrategie von Aerofugia
Der Start der IPO-Beratung für Aerofugia markiert den Übergang der "Low-Altitude-Economy" vom Konzept zur Kapitalernte. Dies ist nicht nur der Bau von fliegenden Autos, sondern eine Neugestaltung der städtischen Raumhoheit.
🚀 Version B: Emotionaler viraler Post
Titel: Hör auf, dich am Boden abzumühen! In Zukunft nur noch 10 Minuten mit dem "Flugtaxi"? 💸
Was damals als "verrücktes Gerede" verspottet wurde, ist jetzt Realität! Der Himmel wird offiziell zur "Fahrspur", das Zeitalter der Low-Altitude-Mobilität ist da. Verkauft wird nicht das Flugzeug, sondern das "Privileg, Staus zu umgehen".
🔮 EINZIGARTIGER BLICKWINKEL
Die Klassengesellschaft der Zeit-Souveränität: 2026 wird sich die Klassenschichtung im "vertikalen Zugangsrecht" widerspiegeln. Die 300-Meter-Höhe, die Aerofugia besetzt, ist die ultimative Deutungshoheit über die städtische Ordnung der nächsten 50 Jahre.
.
├── server.py # Core MCP logic
├── LICENSE # MIT License
├── requirements.txt # Project dependencies
├── drafts/ # Generated markdown posts (Output)
└── README.md # DocumentationLizenziert unter der MIT-Lizenz. Offen für Modifikationen und den persönlichen Gebrauch.
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.
PostHero MCP server — schedule and publish social media posts from any MCP-compatible AI tool
MCP server for QPost — lets AI agents publish video and image posts to YouTube, TikTok, Instagram.
WordPress MCP server: generate SEO posts, AI images, autoblog & WooCommerce on your self-hosted site
Social media MCP server: your Instagram, TikTok, YouTube, LinkedIn and Threads history for your AI.