UNO (Unified Narrative Operator) ist ein magisches Tool zur Textverbesserung, das gewöhnliche Story-Inhalte in reichhaltige, detaillierte Erzählungen verwandelt. Unter Verwendung fortschrittlicher literarischer Techniken und heuristischer Analysen kann UNO die Länge Ihres Textes verdoppeln, während die ursprüngliche Stimme und Absicht erhalten bleiben.
Betrachten Sie UNO als Ihren persönlichen Erzähl-Assistenten, der zu Folgendem fähig ist:
📊 Analyse Ihres Textes, um Stärken und Schwächen zu verstehen
🌱 Ausbau unterentwickelter Story-Elemente
🎨 Anreicherung von Umgebungsbeschreibungen
⚡ Intensivierung von Action-Sequenzen
🌊 Glättung von Sprachfluss und Rhythmus
🔄 Eliminierung repetitiver Sprache
Related MCP server: Galaxy Brain
UNO bietet drei leistungsstarke MCP-Tools:
analyze_textFührt eine tiefgehende Analyse Ihrer Story-Seiten durch und erstellt einen umfassenden Bericht, der Folgendes beinhaltet:
📝 Bewertung der narrativen Position (Anfang, Mitte, Höhepunkt, Auflösung)
👤 Identifizierung des Charakter-Fokus
🎭 Klassifizierung des Szenentyps
🌡️ Bewertung von Stimmung und Tonfall
📈 Verbesserungsempfehlungen für jede Technik
🔄 Erkennung von Wiederholungsmustern
enhance_textTransformiert Ihren Text durch Anwendung aller fünf Verbesserungstechniken:
Automatische Erweiterung des Textes auf die Zielvorgabe (Standard: 200%)
Intelligente Anwendung von Techniken basierend auf den größten Bedürfnissen Ihres Textes
Ausgewogene Erweiterungen über den gesamten Text hinweg
custom_enhance_textBietet Ihnen die volle Kontrolle über den Verbesserungsprozess:
Auswahl der anzuwendenden Verbesserungstechniken
Festlegung benutzerdefinierter Erweiterungsziele (100%-500%)
Fokus auf spezifische Aspekte Ihrer Erzählung
Identifiziert unterentwickelte Elemente in Ihrer Geschichte und baut diese aus:
Entwicklung erwähnter, aber nicht ausgearbeiteter Charaktere
Erforschung impliziter, aber unerklärter Handlungselemente
Hervorhebung von Subtext und verborgenen Bedeutungen
Bereichert Ihre Schauplätze mit immersiven Details:
Hinzufügen lebendiger sensorischer Erfahrungen (visuell, auditiv, taktil, olfaktorisch)
Schaffung einprägsamer Fokus-Momente auf unbedeutende Objekte
Vertiefung von Atmosphäre und Stimmung
Verwandelt Action-Sequenzen in dynamische, hochintensive Erlebnisse:
Manipulation der wahrgenommenen Zeit (Verlangsamung entscheidender Momente)
Intensivierung sensorischer Details während der Action
Schaffung eines rhythmischen Wechsels zwischen explosiver Action und momentaner Stille
Einbeziehung der Umgebung als aktiver Teilnehmer der Action
Verbessert den Fluss und Rhythmus Ihres Schreibstils:
Verbesserung der Übergänge zwischen Absätzen
Variation der Satzstruktur für bessere Lesbarkeit
Schaffung eines natürlichen Rhythmus, der die Leser durch den Text zieht
Reduziert unbeabsichtigte Wiederholungen bei gleichzeitiger Wahrung des Stils:
Identifizierung und Ersetzung wiederholter Wörter durch sinnvolle Alternativen
Wahrung der Stimme und Absicht des Autors
Unterscheidung zwischen beabsichtigten und unbeabsichtigten Wiederholungen
Um den Unified Narrative Operator für Claude Desktop automatisch über Smithery zu installieren:
npx -y @smithery/cli install @MushroomFleet/uno-mcp --client claudeNode.js (v14 oder höher)
NPM (v6 oder höher)
Repository klonen oder herunterladen
git clone https://github.com/your-username/uno-mcp.git
cd uno-mcpAbhängigkeiten installieren
npm installTypeScript-Dateien bauen
npm run buildServer ausführbar machen (unter Windows überspringen)
chmod +x dist/index.jsServer testen
node test-run.jsDies führt den Server mit einer Beispielgeschichte aus und generiert drei Dateien:
test-analysis.md: Beispiel-Analysebericht
test-enhanced.txt: Beispiel für verbesserten Text (200%)
test-custom-enhanced.txt: Beispiel für benutzerdefinierte Verbesserung (150%)
Claude-Konfigurationsdatei bearbeiten
Windows: C:\Users\[Benutzername]\AppData\Roaming\Claude\claude_desktop_config.json
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
UNO zum MCP-Server-Bereich hinzufügen
{
"mcpServers": {
"uno": {
"command": "node",
"args": ["/absolute/path/to/uno-mcp/dist/index.js"],
"disabled": false,
"autoApprove": []
}
}
}Stellen Sie sicher, dass Sie den absoluten Pfad zu Ihrer UNO-Installation verwenden.
Claude neu starten Starten Sie nach dem Speichern der Konfiguration Claude neu, um den UNO MCP-Server zu aktivieren.
VS Code Claude-Erweiterungskonfiguration bearbeiten
Windows: c:\Users\[Benutzername]\AppData\Roaming\Code\User\globalStorage\saoudrizwan.claude-dev\settings\cline_mcp_settings.json
macOS: ~/Library/Application Support/Code/User/globalStorage/saoudrizwan.claude-dev/settings/cline_mcp_settings.json
Fügen Sie dieselbe Konfiguration wie oben für Claude Desktop gezeigt hinzu.
Starten Sie VS Code neu oder laden Sie das Fenster neu.
<use_mcp_tool>
<server_name>uno</server_name>
<tool_name>analyze_text</tool_name>
<arguments>
{
"text": "As Sarah walked into the garden, she noticed the old statue in the corner. It was covered in moss and vines, almost hidden from view. She felt drawn to it somehow."
}
</arguments>
</use_mcp_tool>Dies liefert einen detaillierten Analysebericht mit Erkenntnissen über die narrative Position, den Charakter-Fokus, Verbesserungsmöglichkeiten und mehr.
<use_mcp_tool>
<server_name>uno</server_name>
<tool_name>enhance_text</tool_name>
<arguments>
{
"text": "As Sarah walked into the garden, she noticed the old statue in the corner. It was covered in moss and vines, almost hidden from view. She felt drawn to it somehow."
}
</arguments>
</use_mcp_tool>Dies liefert eine Version Ihres Textes, die etwa doppelt so lang wie das Original ist, wobei alle fünf Verbesserungstechniken angewendet wurden.
<use_mcp_tool>
<server_name>uno</server_name>
<tool_name>custom_enhance_text</tool_name>
<arguments>
{
"text": "As Sarah walked into the garden, she noticed the old statue in the corner. It was covered in moss and vines, almost hidden from view. She felt drawn to it somehow.",
"expansionTarget": 150,
"enableGoldenShadow": true,
"enableEnvironmental": true,
"enableActionScene": false,
"enableProseSmoother": true,
"enableRepetitionElimination": false
}
</arguments>
</use_mcp_tool>Dieses Beispiel wendet nur Golden Shadow Enhancement, Environmental Expansion und Prose Smoothing an, mit einem Ziel von 150% Erweiterung.
Can you enhance this scene with more environmental details?
<use_mcp_tool>
<server_name>uno</server_name>
<tool_name>custom_enhance_text</tool_name>
<arguments>
{
"text": "Jack entered the abandoned warehouse, searching for clues.",
"expansionTarget": 300,
"enableEnvironmental": true,
"enableGoldenShadow": false,
"enableActionScene": false,
"enableProseSmoother": false,
"enableRepetitionElimination": false
}
</arguments>
</use_mcp_tool>Let me analyze this paragraph to give you feedback:
<use_mcp_tool>
<server_name>uno</server_name>
<tool_name>analyze_text</tool_name>
<arguments>
{
"text": "[student's writing sample]"
}
</arguments>
</use_mcp_tool>
Based on the analysis, I recommend focusing on developing your character motivations more clearly.Here's a more intense version of your action scene:
<use_mcp_tool>
<server_name>uno</server_name>
<tool_name>custom_enhance_text</tool_name>
<arguments>
{
"text": "[original action scene]",
"enableActionScene": true,
"enableEnvironmental": true,
"enableGoldenShadow": false,
"enableProseSmoother": true,
"enableRepetitionElimination": true
}
</arguments>
</use_mcp_tool>Let me help you expand this chapter:
<use_mcp_tool>
<server_name>uno</server_name>
<tool_name>enhance_text</tool_name>
<arguments>
{
"text": "[chapter excerpt]",
"expansionTarget": 180
}
</arguments>
</use_mcp_tool>🔍 Beginnen Sie immer mit analyze_text, um zu verstehen, was Ihr Text benötigt
🎯 Für subtile Verbesserungen verwenden Sie custom_enhance_text mit einem niedrigeren Erweiterungsziel (120-150%)
🧩 Teilen Sie längere Texte zur Verarbeitung in kleinere Abschnitte auf und kombinieren Sie die Ergebnisse anschließend
🔄 Wenden Sie Repetition Elimination als letzten Schritt bei der Verbesserung längerer Werke an
⚡ Verwenden Sie enableActionScene: true nur für Szenen, die Action-Elemente enthalten
ISC
UNO basiert auf fortschrittlichen literarischen Verbesserungstechniken und Erzähltheorie. Besonderer Dank gilt den Geschichtenerzählern, Schriftstellern und Erzähltheoretikern, deren Arbeit dieses Projekt inspiriert hat.
⭐ Mit Liebe vom UNO-Team gemacht ⭐
TranscriptionTools-MCP — Transkript-Verarbeitung
DeepLucid3D-MCP — Kognitive Verarbeitung
UNO-MCP — Narrative Verbesserung
gitea-mcp — Gitea-Integration
zero-vector-MCP — Prozedurale Generierung
Analyzes a story page and generates a report with insights
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | The story page text to analyze or enhance |
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 analysis and report generation but lacks details on what 'insights' entail, whether the operation is read-only or has side effects, performance characteristics, or error handling. This is a significant gap 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 functionality ('Analyzes a story page') and adds the outcome ('generates a report with insights') without any wasted words. It is appropriately sized for the tool's apparent complexity.
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. It doesn't explain what the 'report' or 'insights' look like, potential limitations, or how it differs from sibling tools. For a tool with no structured behavioral or output information, more context is needed to guide effective use.
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 schema description coverage is 100%, with the single parameter 'text' documented as 'The story page text to analyze or enhance'. The description adds no additional parameter semantics beyond what the schema provides, so the baseline score of 3 is appropriate as the schema handles the documentation adequately.
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 a specific verb ('analyzes') and resource ('a story page'), and specifies the output ('generates a report with insights'). However, it doesn't explicitly differentiate from sibling tools like 'custom_enhance_text' or 'enhance_text', which appear to have related but potentially different functions.
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 its siblings ('custom_enhance_text' and 'enhance_text'), nor does it mention any prerequisites, alternatives, or exclusions. It only states what the tool does without contextual usage information.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Enhances a story page using selected techniques
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | The story page text to enhance | |
| expansionTarget | No | Target expansion percentage (default: 200) | |
| enableGoldenShadow | No | Enable Golden Shadow enhancement | |
| enableEnvironmental | No | Enable Environmental expansion | |
| enableActionScene | No | Enable Action Scene enhancement | |
| enableProseSmoother | No | Enable Prose Smoothing | |
| enableRepetitionElimination | No | Enable Repetition Elimination |
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 states the tool 'enhances' text, implying a transformation, but doesn't describe the nature of the enhancement, potential side effects, rate limits, or output format. This is a significant gap for a tool with multiple parameters and no output schema.
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 ('enhances a story page'). It avoids unnecessary words, but could be more informative given the tool's complexity, making it slightly under-specified rather than perfectly concise.
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's complexity (7 parameters, no annotations, no output schema), the description is incomplete. It doesn't explain what 'enhance' entails, how techniques interact, or what the output looks like, leaving critical gaps for an agent to understand and use the tool effectively.
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 fully documents all 7 parameters. The description mentions 'selected techniques' but doesn't add meaning beyond the schema, which already details each enhancement technique and parameter. The baseline score of 3 reflects adequate coverage by the schema alone.
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 states the tool 'enhances a story page using selected techniques,' which provides a general purpose but lacks specificity. It mentions the resource ('story page') and verb ('enhances'), but doesn't clarify what 'enhance' means or how it differs from sibling tools like 'enhance_text' and 'analyze_text', leaving the purpose somewhat vague.
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 offers no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'enhance_text' or 'analyze_text', nor does it specify prerequisites, contexts, or exclusions for usage, leaving the agent without clear direction on tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Enhances a story page using all techniques to meet expansion target
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | The story page text to enhance | |
| expansionTarget | No | Target expansion percentage (default: 200) |
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 'using all techniques' but doesn't explain what these techniques are, whether the enhancement is reversible, what permissions or rate limits apply, or what the output looks like. For a tool with no annotations and an implied mutation ('enhances'), this leaves critical behavioral traits undisclosed.
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. It avoids unnecessary words and gets straight to the point. However, it could be slightly more structured by explicitly separating purpose from constraints, but overall it's appropriately concise for the tool's complexity.
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's implied complexity (enhancing text with multiple techniques) and lack of annotations and output schema, the description is incomplete. It doesn't explain what 'enhance' entails, what techniques are used, or what the result looks like. For a tool that likely modifies content, more context is needed to guide the agent effectively.
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 schema description coverage is 100%, with clear descriptions for both parameters ('text' and 'expansionTarget'). The description adds no additional meaning beyond what the schema provides, such as examples or contextual usage. However, since the schema adequately documents the parameters, a baseline score of 3 is appropriate as the description doesn't detract from the schema's clarity.
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 states the tool 'enhances a story page using all techniques to meet expansion target', which provides a vague purpose. It specifies the resource ('story page') and goal ('meet expansion target'), but the verb 'enhances' is generic and doesn't clearly differentiate from sibling tools like 'analyze_text' or 'custom_enhance_text'. The description lacks specificity about what 'enhance' means operationally.
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 doesn't mention sibling tools like 'analyze_text' or 'custom_enhance_text', nor does it specify contexts, prerequisites, or exclusions for usage. The agent must infer usage based on the tool name alone, which is insufficient for informed selection.
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.
analyze_textcustom_enhance_textenhance_textScored across 3 tools
The tools 'custom_enhance_text' and 'enhance_text' have overlapping purposes, both focused on enhancing story pages, with only a vague distinction based on technique selection versus using all techniques. This creates ambiguity where an agent might struggle to choose between them for a given enhancement task. The 'analyze_text' tool is more distinct but the enhancement tools lack clear boundaries.
All tools follow a consistent snake_case naming pattern with a verb_noun structure (e.g., analyze_text, enhance_text). The naming is predictable and readable, with only minor deviation in 'custom_enhance_text' where the adjective 'custom' adds some variation but maintains the overall convention.
With only 3 tools, the server feels thin for a domain like story analysis and enhancement, potentially lacking coverage for broader operations. While it covers basic analyze and enhance functions, the low count may limit agent capabilities in handling more complex workflows or additional CRUD-like actions.
The tool set is severely incomplete for a story analysis and enhancement domain, as it only includes analysis and enhancement without any CRUD operations (e.g., create, update, delete story pages) or lifecycle management. This creates significant gaps that will likely cause agent failures when trying to perform full workflows beyond simple text processing.
Generate full stories, chapters, characters & cover art from a premise (planner-writer pipeline).
LLM chat, text tools, image generation, editing, batch image jobs, and asynchronous video generation
Fan out deep research across multiple AI providers, synthesize into one unified report.
Exactly 50 data transformation and live web verification tools for AI agents.
