RenderDeck

AI-powered presentation generation as an MCP server. Describe the presentation you want in conversation with your LLM, and RenderDeck generates a .pptx with Gemini-created slide images.

Quick start: After installing, tell your LLM "How do I use RenderDeck?" to get a detailed explanation of all tools, workflows, and example prompts.

Getting Started

1. Install

pip install renderdeck-mcp
# or run directly with uvx (no install needed):
uvx renderdeck-mcp serve

2. Configure your LLM client

Add RenderDeck as an MCP server in your client's config.

Claude Desktop — add to ~/Library/Application Support/Claude/claude_desktop_config.json:

{
  "mcpServers": {
    "renderdeck": {
      "command": "uvx",
      "args": ["renderdeck-mcp", "serve"],
      "env": {
        "GOOGLE_GEMINI_API_KEY": "your-api-key-here"
      }
    }
  }
}

Claude Code — add to .claude/settings.json or ~/.claude/settings.json:

{
  "mcpServers": {
    "renderdeck": {
      "command": "uvx",
      "args": ["renderdeck-mcp", "serve"],
      "env": {
        "GOOGLE_GEMINI_API_KEY": "your-api-key-here"
      }
    }
  }
}

Cursor — add to .cursor/mcp.json:

{
  "mcpServers": {
    "renderdeck": {
      "command": "uvx",
      "args": ["renderdeck-mcp", "serve"],
      "env": {
        "GOOGLE_GEMINI_API_KEY": "your-api-key-here"
      }
    }
  }
}

3. Set up your API key

Ask your LLM to run the setup_gemini_key tool with your Gemini API key, or set GOOGLE_GEMINI_API_KEY in the server's environment.

4. Develop your storyline

Tell your LLM what presentation you need — the topic, audience, tone, and any specific points to cover. The LLM reads the renderdeck://reference resource to learn the slide prompt format, then collaborates with you to develop:

• Storyline and structure — how many slides, what each one covers, the narrative arc
• Visual direction — style, color palette, imagery for each slide
• Speaker notes — what to say on each slide, with timing guidance

You iterate in conversation until the storyline feels right. The LLM then writes the slide prompt file — a structured markdown document — so you never need to learn the format yourself.

5. Validate and generate

The LLM calls validate_prompt_file to catch any formatting issues, then generate_deck to produce a .pptx with Gemini-generated slide images.

6. Iterate

Review the generated deck. Ask the LLM to tweak specific slides — adjust the visual prompt, reword speaker notes, or restructure the flow. Use regenerate_slide to re-render individual slides without rebuilding the entire deck.

Example Prompts

Just tell your LLM what you need — no need to learn the prompt file format:

"Create a 10-slide deck on our Q1 product roadmap for the engineering all-hands. Audience: 50 engineers. Tone: confident but honest about delays. Include a timeline slide and a risks slide."

The LLM reads the reference, drafts a prompt file with 10 slides, validates it, and calls generate_deck.

"I have a blog post about our new API. Turn it into a 7-slide technical presentation for DevRel to present at a meetup. Use dark theme with code snippets on slides."

The LLM distills the blog post into key points, structures them as slides, and generates visuals matching the dark theme.

"Here is our investor update email [paste text]. Create a 12-slide board deck. Use notes_mode narration so I can feed it into Pictory for a video version."

The LLM extracts metrics and narrative from the email, builds slides with **Say:** notes for narration, and generates with notes_mode="narration".

"Generate the deck, then convert it to a narrated video using the 'roger' voice."

The LLM generates slides, then calls generate_video to compose a narrated MP4 with the Roger voice.

"Show me all available voices — I want something energetic and male."

The LLM calls list_voices and highlights male voices, noting style descriptors to help you choose.

"Create a 5-slide deck about our new API launch, then convert it to video with the 'guy' voice."

The LLM drafts a prompt file, generates the deck, and immediately calls generate_video with voice="guy" to produce a narrated MP4.

Getting the Best Results

For best results, don't jump straight to slide generation. Use the LLM to develop the raw material first:

1. Brainstorm — Tell the LLM your topic, audience, and goal. Ask it to outline key messages and a narrative arc.

   "I need a presentation about [topic] for [audience]. The goal is [goal]. Help me identify the 5-7 key messages and suggest a narrative arc."

2. Structure — Ask the LLM to organise the outline into a slide sequence with one idea per slide and clear transitions.

   "Organise these messages into a slide-by-slide outline. One idea per slide, with clear transitions. Suggest a title for each slide."

3. Enrich — Paste in any source material (docs, emails, data, meeting notes). Ask the LLM to distill the most compelling points for your audience.

   "Here is my source material: [paste docs/emails/data]. Distill the most compelling points for my audience and weave them into the outline."

4. Generate — Once the storyline is solid, say "now generate the deck". The LLM writes the prompt file and calls the tools.

   "The outline looks good. Now generate the deck using RenderDeck."

5. Iterate — Review the .pptx, then ask the LLM to tweak individual slides, adjust visuals, or reword notes.

   "Slide 4 needs a stronger visual — make it more data-driven. And reword the speaker notes on slide 7 to be more conversational."

Pro tip: The more context you give the LLM up front (audience, tone, key data points, what to emphasise, what to skip), the better the first draft. Treat the LLM as a presentation coach, not just a generator.

MCP Tools

MCP Resources

MCP Prompts

Security & Privacy

RenderDeck runs entirely on your local machine as an MCP server process. Your slide prompt files and generated images stay on disk — the only external communication is with the Google Gemini API, which receives the text prompt for each slide and returns a generated image. No data is sent to any other service. Your Gemini API key is stored locally with Fernet encryption.

Tech Stack

Cost Guidance

• Nano Banana (gemini-2.5-flash-image): ~$0.039 per slide image
• Nano Banana Pro (gemini-3-pro-image-preview): ~$0.12 per slide image
• Cached images are reused automatically when the prompt hasn't changed

Changelog

See CHANGELOG.md for release notes.