# Draft slide decks from your knowledge base

> Ask the library for the argument, then generate presentation outlines — the deck writes itself from sources you trust.

- For: Consultant
- Category: Team Knowledge & Library Ops
- MCP tools: deep_context, run_youtube_tool
- HTML version: https://veridive.com/mcp/use-cases/decks-from-knowledge-base

## The problem

The deck is due Thursday and the material exists — that's the frustrating part. The argument you need to present is distributed across sources you've already curated: the expert talks in your library, the conference sessions you imported, the research you collected precisely because a moment like this would come. What stands between the curated material and the deck is a day of re-reading, extracting and structuring that Thursday doesn't have.

Consultants, analysts and anyone who presents for a living knows the shape: the thinking is done, the sources are gathered, and the assembly still costs the day. Assembly is the delegable part.

## How veridive MCP helps

**deep_context** builds the argument from your curated sources: scope the question to the relevant imports and get the synthesis **cited to the chunks** — the claims, the supporting points, the expert framings, each traceable to a source you chose to trust when you curated it.

**run_youtube_tool**'s `presentation` and `slides` handle the structural half: outlines and slide-shaped content from the source material. You assemble the final deck with judgment — order, emphasis, the client-specific frame — while the extraction and structuring that used to eat the day runs as prompts. The deck ships Thursday with citations in the appendix, which lands especially well in rooms that ask "says who?"

## How to run it

1. **Connect veridive MCP** — One-time setup: add the veridive MCP server to Claude, ChatGPT, Cursor or any MCP client and generate your API key. Takes about two minutes.
2. **Build the argument from the library** — The deck's spine, synthesized from your curated sources with citations.

   ```
   From my library items tagged '<topic>': build the argument for <deck's thesis> — key claims, supporting evidence, expert framings, cited to the sources.
   ```
3. **Structure it as a deck** — Outline and slide-shaped content from the strongest source material.

   ```
   Turn that argument into a presentation outline — slide by slide, with the supporting point and source per slide.
   ```
4. **Apply the judgment layer** — Order, emphasis, the audience-specific frame — the part that stays yours.

   ```
   Reorder for a <audience> audience: lead with <their concern>, and flag which slides need my own client-specific data.
   ```

## Problems it solves

- The material exists, curated and trusted — assembly still costs the day Thursday lacks.
- Re-reading sources to extract the argument repeats work the curation already did.
- Decks built under deadline skip sourcing, then meet the room that asks 'says who?'
- Presentation structure is mechanical and eats the hours judgment deserved.

## Why it's valuable

- The argument assembles from sources you already vetted — trust travels into the deck.
- Citations arrive with the synthesis; the appendix builds itself.
- Your hours move up the stack: order, emphasis and audience-fit instead of extraction.
- The same library serves every future deck — curation compounds across engagements.

## Example prompts

```
From '<topic>'-tagged items: the argument for <thesis>, cited.
```

```
Presentation outline, slide by slide, point + source each.
```

```
Reorder for <audience>; flag slides needing my own data.
```

## FAQ

**What makes this better than asking a general assistant to draft the deck?**

The grounding: every claim comes from your curated, trusted sources with citations — not from a model's general knowledge. For client work, 'sourced from the material we vetted' is the difference between a draft and a liability.

**Which tools produce the slide content?**

deep_context for the cited argument, then run_youtube_tool's presentation and slides tools for the structural conversion. Final assembly in your deck tool stays manual — that's the judgment layer.

**Does this help recurring deck types — QBRs, industry updates?**

Best case for it: a maintained topic library plus a saved prompt sequence makes the recurring deck a refresh instead of a rebuild.

## Related use cases

- [Stand up a research library your whole team queries](https://veridive.com/mcp/use-cases/company-research-library.md) — Curate once, query forever: shared imports become a common brain with citations instead of link-dump Slack threads.
- [Draft the quarterly "what changed" memo](https://veridive.com/mcp/use-cases/quarterly-what-changed-memo.md) — Ground the quarter's shifts in imported commentary, then have chat shape it into a memo your PM can forward.
- [Replace book summaries with author talks](https://veridive.com/mcp/use-cases/author-talks-book-summaries.md) — Authors give away the thesis on the promo circuit; find their talks and summarize — closer to the source than any summary app.

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Part of the veridive MCP use-case library: https://veridive.com/mcp/use-cases.md
Server docs for agents: https://veridive.com/mcp.md