Alai
Alai - KI-Präsentations-Maker MCP-Server
KI-Präsentations-Maker und Foliengenerator für Claude, Cursor und MCP-Clients. Erstellen Sie Präsentationen, Pitch-Decks und Folien auf Designerniveau aus Text. Export nach PowerPoint (PPTX) und PDF.
Was ist Alai?
Alai ist ein KI-Präsentations-Maker und der schnellste Weg, hochwertige, ansprechende Folien ohne Designkenntnisse zu erstellen.
Folien aus Text generieren - Verwandeln Sie Notizen, Markdown, URLs oder Dokumente in ausgefeilte Präsentationen
Bestehende Folien verschönern - Gestalten Sie Ihre PowerPoint-Präsentationen mit KI neu und verbessern Sie sie
Überall exportieren - Als PowerPoint (PPTX), PDF oder teilbaren Link herunterladen
Professionelle Designs - Vorlagen auf Designerniveau für jeden Anlass
Sprechernotizen - KI-generierte Stichpunkte für jede Folie
Nano Banana Pro Bildfolien - Themenbezogene Generierung von Bildfolien, die zum visuellen Stil Ihres Decks passen
Bearbeiten und iterieren - Nehmen Sie gezielte Änderungen an Text, Symbolen und Bildern auf bestehenden Folien vor
Related MCP server: Google Slides MCP Server
Anwendungsfälle
Pitch-Decks - Erstellen Sie investorenbereite Präsentationen aus Ihren Notizen
Verkaufspräsentationen - Generieren Sie überzeugende Folien für Interessenten
Besprechungsnotizen zu Folien - Verwandeln Sie Ihre Notizen in teilbare Decks
PowerPoint-Verschönerung - Gestalten Sie bestehende Folien mit professionellen Designs neu
Marketing-Präsentationen - Erstellen Sie schnell Produkt- und Kampagnen-Decks
Funktionen
Generieren Sie Präsentationen auf Designerniveau aus Text, Markdown oder Besprechungsnotizen
KI-gestützte Verschönerung und Neugestaltung von Folien
Export nach PowerPoint (PPTX) oder PDF
Professionelle Pitch-Deck-Designs
Hinzufügen und Entfernen von Folien aus bestehenden Präsentationen
Bearbeiten und Iterieren bestehender Folien mit gezielten Prompts
Automatische Generierung von Sprechernotizen
Server-URL
https://slides-api.getalai.com/mcp/Glama / Lokaler Wrapper
Dieses Repository enthält einen lokalen MCP-Wrapper, damit Glama den Server automatisch erstellen, starten und inspizieren kann.
Der Wrapper läuft über stdio und leitet Tool-Aufrufe an den gehosteten Alai MCP-Endpunkt weiter:
ALAI_MCP_URL- optionale Überschreibung für die Upstream-MCP-URLALAI_API_KEY- optionaler API-Schlüssel, der bei der Weiterleitung von Tool-Aufrufen an den Upstream verwendet wirdapi_key- alternativer Name für die Umgebungsvariable, der für Glama-Platzhalterargumente unterstützt wird
Die Tool-Introspektion funktioniert ohne Anmeldedaten, was für Glama ausreicht, um den Server zu inspizieren. Die tatsächliche Tool-Ausführung erfordert einen gültigen API-Schlüssel.
Lokal ausführen
npm install
npm startMit Upstream-Anmeldedaten:
ALAI_API_KEY=sk_your_key npm startAuthentifizierung
Der Server akzeptiert entweder einen statischen API-Schlüssel oder ein OAuth 2.1-Bearer-Token am selben Endpunkt.
API-Schlüssel
Holen Sie sich einen Schlüssel von getalai.com und übergeben Sie ihn in einem dieser Header:
api-key: sk_your_keyAuthorization: Bearer sk_your_key
OAuth 2.1 mit dynamischer Client-Registrierung
Der Server implementiert RFC 9728 Protected Resource Metadata und delegiert die Autorisierung an Supabase, das RFC 7591 Dynamic Client Registration und PKCE (S256) unterstützt. Spezifikationskonforme MCP-Clients (z. B. Claude Desktop, MCP Inspector) können den Ablauf automatisch erkennen:
GET https://slides-api.getalai.com/.well-known/oauth-protected-resourceDer authorization_servers-Eintrag der Antwort verweist auf den Supabase-Autorisierungsserver, dessen /.well-known/oauth-authorization-server-Dokument den registration_endpoint, authorization_endpoint und token_endpoint bewirbt. Nach dem Autorisierungscode + PKCE-Ablauf sendet der Client Authorization: Bearer <jwt> an den MCP-Endpunkt.
Verfügbare Tools
Tool | Beschreibung |
| Überprüfen Sie Ihren API-Schlüssel und geben Sie Ihre Benutzer-ID zurück |
| Erstellen Sie eine Präsentation aus Textinhalt |
| Überprüfen Sie den Status des asynchronen Vorgangs |
| Listen Sie die für den authentifizierten Benutzer verfügbaren Designs auf |
| Listen Sie die für den authentifizierten Benutzer verfügbaren Vibes (visuelle Stile) auf |
| Listen Sie alle Ihre Präsentationen auf |
| Fügen Sie einer bestehenden Präsentation eine Folie (klassisch oder kreativ) hinzu |
| Entfernen Sie eine Folie aus einer Präsentation |
| Exportieren Sie in PDF, PPTX oder als teilbaren Link |
| Generieren Sie Sprechernotizen für Folien |
| Löschen Sie eine Präsentation dauerhaft |
Arbeitsablauf
Rufen Sie
generate_presentationmit Ihrem Inhalt aufFragen Sie
get_generation_statusalle 2-5 Sekunden ab, bis der StatuscompletedlautetVerwenden Sie die zurückgegebene
presentation_idfür weitere Vorgänge
Beispielanwendung
Eine Präsentation generieren
Rufen Sie zuerst get_themes und get_vibes auf, um die für Ihr Konto verfügbaren IDs zu ermitteln, und übergeben Sie diese dann:
{
"input_text": "Benefits of AI in the workplace: increased productivity, enhanced creativity, improved efficiency",
"title": "AI in the Workplace",
"theme_id": "<id from get_themes>",
"vibe_id": "<id from get_vibes>",
"slide_range": "2-5",
"include_ai_images": true,
"num_creative_variants": 1,
"total_variants_per_slide": 1,
"image_ids": [],
"export_formats": ["link"],
"language": "English"
}Nur input_text ist erforderlich. num_creative_variants muss 0–2 sein (auf ≥1 setzen, wenn vibe_id verwendet wird). total_variants_per_slide muss 1–4 sein. export_formats akzeptiert "link", "pdf", "ppt".
Generierungsstatus überprüfen
{
"generation_id": "abc123-def456"
}Präsentation exportieren
{
"presentation_id": "xyz789",
"formats": ["pdf", "link"]
}Verfügbare Designs
Rufen Sie get_themes auf, um die für Ihr Konto verfügbaren Designs zu ermitteln (gibt Design-IDs und Anzeigenamen zurück). Eine Handvoll integrierter Legacy-Designnamen, die Sie direkt als theme_id übergeben können:
AURORA_FLUXMIDNIGHT_EMBEREMERALD_FORESTDESERT_BLOOMDONUTOAKPRISMATICASIMPLE_LIGHTSIMPLE_DARKCYBERPUNK
Konfiguration
Für Claude Desktop / MCP-Clients
OAuth-fähige Clients (Claude Desktop, MCP Inspector, Cursor usw.) können nur die URL verwenden – der Client erkennt den OAuth 2.1 + DCR-Ablauf bei der ersten Verbindung und führt ihn aus:
{
"mcpServers": {
"alai-presentations": {
"url": "https://slides-api.getalai.com/mcp/",
"transport": "streamable-http"
}
}
}Wenn Sie OAuth überspringen und einen statischen API-Schlüssel verwenden möchten, fügen Sie einen Header-Block hinzu:
{
"mcpServers": {
"alai-presentations": {
"url": "https://slides-api.getalai.com/mcp/",
"transport": "streamable-http",
"headers": {
"api-key": "sk_your_api_key"
}
}
}
}Links
Lizenz
MIT-Lizenz - Siehe LICENSE-Datei für Details.
Available Tools
11 toolscreate_slideAInspect
Add a new slide to an existing presentation. Use this for targeted edits after a deck already exists, including classic content slides or more creative visually led slides.
| Name | Required | Description | Default |
|---|---|---|---|
| presentation_id | Yes | Target presentation that will receive the new slide. | |
| prompt | Yes | Instruction describing the content or intent of the new slide. | |
| slide_type | No | Choose classic for structured content or creative for more visual exploration. | |
| insert_after_slide_id | No | Existing slide identifier after which the new slide should be inserted. | |
| theme_id | No | Optional theme override for the new slide. | |
| vibe_id | No | Optional vibe override for the new slide. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must bear the full burden. It discloses the mutation (adding a slide) and mentions slide types, but lacks details on side effects, authentication, rate limits, or error behavior. Adequate but not rich.
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 with two clear sentences. It front-loads the main purpose and follows with usage context. No unnecessary words.
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 6 parameters with full schema descriptions and no output schema, the description provides adequate context for a creation tool. It mentions slide types and targeted edits, which is sufficient for most use cases.
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 covers all 6 parameters with descriptions (100% coverage). The description adds minimal extra meaning beyond the schema, such as explaining 'classic' vs 'creative' slide types. Baseline 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 clearly states the action (Add a new slide), the target resource (existing presentation), and distinguishes from siblings like generate_presentation (creates whole deck) and delete_slide (removes). The scope is well-defined.
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 explicitly mentions using this for targeted edits after a deck already exists, which provides clear context. It does not explicitly state when not to use it or list alternatives, but the sibling tool names imply other use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
delete_presentationAInspect
Delete a presentation permanently. Use this destructive action only when the caller explicitly intends to remove the deck.
| Name | Required | Description | Default |
|---|---|---|---|
| presentation_id | Yes | Presentation identifier to delete permanently. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses the destructive and permanent nature, but lacks details on cascading effects, permissions, or rate limits. Adequate for a simple delete action.
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 sentence that is front-loaded with the purpose and usage condition. No unnecessary words.
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?
The tool is simple with one parameter and no output schema. The description covers purpose, usage, and a key behavioral trait (permanence). It could mention return values or error conditions but is sufficient for the tool's simplicity.
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 of the sole parameter matches the schema. The description adds no extra meaning beyond what the schema already provides, meeting the baseline.
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 (delete) and the resource (presentation), with the modifier 'permanently' that distinguishes it from non-destructive operations. Sibling tools like delete_slide operate on different resources.
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 explicitly advises using this tool only when the caller intends permanent removal, providing a clear 'when to use' condition. It does not mention when not to use, but the condition covers that implicitly.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
delete_slideAInspect
Remove a slide from a presentation permanently. Use this only when you know the exact slide identifier to delete.
| Name | Required | Description | Default |
|---|---|---|---|
| presentation_id | Yes | Presentation that owns the slide. | |
| slide_id | Yes | Slide identifier to remove from the presentation. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description indicates the action is permanent ('permanently'), which is useful for a delete operation. However, it lacks details on side effects (e.g., impact on references, undo ability), and there are no annotations to supplement this. The description is adequate but not thorough for a destructive 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 consists of two short, front-loaded sentences with no unnecessary words. Every sentence adds value: first states the action, second provides usage context.
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 delete tool with two parameters and no output schema, the description covers the essential purpose and usage condition. It could mention whether deletion is reversible, but overall it is sufficient for an agent to understand and invoke the tool correctly.
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 provides complete descriptions for both parameters (presentation_id, slide_id), achieving 100% coverage. The tool description adds no additional meaning beyond what the schema already conveys, so the 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 clearly states the action ('Remove a slide from a presentation permanently') with a specific verb and resource, and it distinguishes itself from sibling tools like create_slide and delete_presentation by focusing on slides.
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: 'Use this only when you know the exact slide identifier to delete.' This tells the agent when to use the tool, though it doesn't mention alternatives or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
export_presentationAInspect
Export a finished presentation to PDF, PowerPoint, or a shareable link. Use this after generation or editing when you need a deliverable artifact.
| Name | Required | Description | Default |
|---|---|---|---|
| presentation_id | Yes | Presentation to export. | |
| formats | Yes | One or more export formats to generate. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility for transparency. It does not disclose whether the original presentation is modified, what permissions are required, rate limits, or behavior if the presentation is not finished. This is a significant gap for a tool that produces external artifacts.
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 consists of two concise sentences that front-load the action and outputs, then provide usage context. No unnecessary words.
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 2-parameter tool with no output schema, the description covers the basic purpose and usage context. However, it is incomplete regarding return values or side effects, which would be helpful for an agent.
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%, and the description adds minimal extra meaning beyond the schema. It reiterates the formats but does not elaborate on parameter syntax or constraints. Baseline 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 clearly states the tool exports a presentation to specific formats (PDF, PowerPoint, link), using a specific verb and resource. It distinguishes from sibling tools like create_slide or delete_presentation by focusing on the export action.
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 advises using the tool 'after generation or editing when you need a deliverable artifact,' providing clear usage context. However, it does not explicitly state when not to use it or mention alternatives, though none exist among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
generate_presentationAInspect
Create a new presentation from raw text or markdown. Use this to turn notes, outlines, meeting summaries, or draft content into an Alai deck before polling get_generation_status.
| Name | Required | Description | Default |
|---|---|---|---|
| input_text | Yes | The source content to transform into slides. | |
| title | No | Presentation title shown in the deck and exports. | |
| theme_id | No | Theme identifier from get_themes. Use this to control layout family. | |
| vibe_id | No | Visual style identifier from get_vibes. Use only after discovering valid IDs. | |
| language | No | Presentation language, for example English or Spanish. | |
| export_formats | No | Formats to generate when the deck is ready. | |
| slide_range | No | Requested slide count range such as 2-5. | |
| include_ai_images | No | Whether Alai should generate image content for slides. | |
| num_creative_variants | No | How many creative variants to generate per slide. | |
| total_variants_per_slide | No | Total variant count to generate for each slide. | |
| image_ids | No | Existing uploaded image identifiers to reuse in the deck. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It correctly implies the tool is asynchronous (by mentioning polling), but does not disclose auth needs, side effects, or error behavior. The description is adequate but could be more explicit about the generation process.
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 two sentences, front-loaded with the action verb 'Create'. Every word serves a purpose with no redundancy. It is concise and easy to parse.
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 complexity (11 parameters, no output schema), the description is minimal. It correctly sets up the workflow with get_generation_status but omits return value description, error cases, or parameter relationships (e.g., theme_id vs vibe_id). The parameter schema partially compensates.
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 baseline is 3. The tool description adds no additional parameter meaning beyond the schema. It mentions 'raw text or markdown' which aligns with input_text but doesn't augment the 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?
The description clearly states the tool creates a presentation from raw text or markdown, with explicit use cases (notes, outlines, meeting summaries). It distinguishes from siblings like create_slide (individual slides) and get_generation_status (polling), and even references the correct subsequent tool.
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 explains when to use the tool: to turn raw text into a deck before polling get_generation_status. It provides context for the workflow but does not explicitly exclude scenarios or mention alternatives like create_slide for single slides, though this is implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
generate_transcriptsAInspect
Generate speaker notes or transcripts for slides in an existing presentation. Use this when the deck visuals are ready and you need talking points for delivery.
| Name | Required | Description | Default |
|---|---|---|---|
| presentation_id | Yes | Presentation whose slides need speaker notes. | |
| slide_ids | No | Optional subset of slide identifiers to process. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It fails to mention whether the tool overwrites existing notes, is additive, or requires any permissions. The side effects and safety of the operation are unclear.
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 (two sentences) and well-structured, with the first sentence stating purpose and the second providing usage context. No unnecessary words.
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?
The tool has no output schema, so the description should indicate what is returned (e.g., updated presentation, success message). It does not, leaving agents uncertain about the outcome. Additionally, it does not clarify if the operation is synchronous or async, despite a sibling tool for generation status.
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?
Input schema coverage is 100%, with clear descriptions for both parameters. The description does not add significant meaning beyond the schema, except hinting that the output is speaker notes or transcripts. Baseline 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 clearly states the tool's purpose: 'Generate speaker notes or transcripts for slides in an existing presentation.' It uses a specific verb ('generate') and resource ('speaker notes or transcripts for slides'), and distinguishes from sibling tools like create_slide and generate_presentation.
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 usage guidance: 'Use this when the deck visuals are ready and you need talking points for delivery.' It implies when to use but does not explicitly mention when not to use or suggest alternatives, leaving some ambiguity.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_generation_statusAInspect
Check the status of an asynchronous presentation generation job. Use this after generate_presentation until the status reaches completed or failed.
| Name | Required | Description | Default |
|---|---|---|---|
| generation_id | Yes | Generation job identifier returned by generate_presentation. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses that the job is asynchronous and implies polling is needed, but lacks details on response structure, possible statuses, or error handling. Basic disclosure is present but not comprehensive.
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 extremely concise at two sentences, front-loading the purpose and usage guidance without any filler. Every word contributes meaning.
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 simplicity (one parameter, polling for status), the description is largely complete. It covers purpose and usage timing. It could mention possible status values or retry logic, but overall adequate.
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% for the single parameter, which already states it is a generation job identifier. The tool description adds no further semantic value for the parameter, so baseline 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 clearly states the tool's purpose: checking the status of an asynchronous presentation generation job. It specifies the resource (generation job) and action (check status), and distinguishes it from sibling tools like generate_presentation.
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 explicitly tells the agent to use this after generate_presentation and until the status reaches completed or failed, providing clear temporal guidance. However, it does not mention alternatives or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_presentationsAInspect
List presentations owned by the authenticated user. Use this when you need to pick an existing presentation_id before editing, exporting, or deleting.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must convey behavioral traits. It states the tool lists presentations 'owned by the authenticated user,' implying read-only access. However, it does not mention whether results are paginated, sorted, or limited, nor does it specify the output format. This is adequate for a simple list operation but leaves some 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 extremely concise: two sentences. The first states the action and scope, the second provides usage guidance. Every word adds value, and it is front-loaded with the core purpose.
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 no output schema and zero parameters, the description covers the tool's purpose and usage context well. It does not describe the return format or fields, which might be helpful, but the omission is minor for a listing tool that simply returns presentation objects. Sibling tools like 'get_themes' are similarly brief.
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, so no parameter documentation is needed. The description does not add parameter-level details, but none are required. With 100% schema coverage (no params), the baseline is 4.
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 that the tool lists presentations owned by the authenticated user, using a specific verb ('List') and resource ('presentations'). It distinguishes itself from sibling tools like 'create_slide' and 'delete_presentation' by explicitly mentioning its role as a prerequisite for editing, exporting, or deleting.
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 explicitly tells when to use this tool: 'when you need to pick an existing presentation_id before editing, exporting, or deleting.' This provides clear context and alternative actions (the editing/exporting/deleting tools), helping the agent decide correctly.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_themesAInspect
List themes available to the authenticated account. Call this before generate_presentation when you need valid theme_id values.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full behavioral burden. It indicates a read operation with no side effects, but lacks details on authentication, rate limits, or response structure. Adequate but minimal.
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 sentences, both front-loaded: first defines purpose, second gives usage tip. No wasted words, excellent conciseness.
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 no parameters and no output schema, the description is mostly complete, explaining what it does and why to use it. It could mention the output format, but the tip implies theme_id values are returned. Slightly lacking, but overall adequate.
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, so the schema is fully covered. The description adds no extra parameter info, but none is needed. Baseline score for zero parameters is 4.
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 lists themes and specifies it's for the authenticated account. It also provides a usage tip linking to generate_presentation, distinguishing it from other list tools like get_vibes.
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 explicitly advises to call this before generate_presentation to obtain valid theme_id values, giving clear context for when to use it. It does not mention exclusions or alternatives, but the guidance is sufficient for this simple tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_vibesAInspect
List available vibe identifiers that control the visual style of generated decks. Use this before setting vibe_id on generate_presentation or create_slide.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, but the description is straightforward about the behavior. It doesn't elaborate on response format or potential side effects, but the tool is simple with no parameters.
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 concise sentences, front-loaded with the primary action and purpose. No wasted words.
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 listing tool with no parameters and no output schema, the description is complete. It explains what it does and when to use it.
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, and the schema coverage is 100%. The description adds no extra info about parameters, but none is needed. Baseline score of 4 applies.
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 it lists vibe identifiers for visual style, with a specific verb and resource. It differentiates its purpose from siblings like get_themes by specifying that it's for controlling deck style.
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?
Explicitly instructs to use this tool before setting vibe_id on generate_presentation or create_slide, providing direct context for when to invoke it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
pingAInspect
Verify the configured Alai credentials and return account identity details. Use this first when you need to confirm authentication before creating or exporting presentations.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It discloses the action (verification) and output (identity details) but omits potential side effects or error scenarios. Adequate for a simple ping.
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 concise sentences: first states purpose, second gives usage context. No wasted words, front-loaded with key action.
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 tool with no parameters and no output schema, the description sufficiently explains purpose and usage. Could mention error handling or latency, but contextually complete for its simplicity.
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?
No parameters exist, and schema coverage is 100%. Description does not need to add parameter info, so baseline score applies.
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 the verb 'verify' and the resource 'Alai credentials', and specifies the return of 'account identity details'. Differentiates from sibling tools focused on presentation manipulation.
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?
Explicitly advises using this tool before creating or exporting presentations to confirm authentication. Does not mention when not to use, but provides clear positive guidance.
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.
11 tool updates
v0.1.0- First observed
create_slide - First observed
delete_presentation - First observed
delete_slide - First observed
export_presentation - First observed
generate_presentation - First observed
generate_transcripts - First observed
get_generation_status - First observed
get_presentations - First observed
get_themes - First observed
get_vibes - First observed
ping
TDQS
Scored across 11 tools
Each tool targets a distinct action and resource, such as creating, deleting, exporting, or listing. No two tools have overlapping purposes, making it easy for an agent to select the correct one.
All tool names follow a consistent verb_noun pattern in snake_case (e.g., create_slide, delete_presentation, get_themes). This predictability aids agent understanding.
With 11 tools covering creation, deletion, export, status checking, listing, and authentication, the count is well-scoped for a presentation generation service.
The set lacks update operations (e.g., update_slide, update_presentation) and retrieval of a single presentation's details (e.g., get_slides). This could force agents to work around gaps, though core create/delete/export flows exist.
Maintenance
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