> ## Documentation Index
> Fetch the complete documentation index at: https://docs.mavera.io/llms.txt
> Use this file to discover all available pages before exploring further.

# Meeting Notes → Mave Analysis

### Scenario

Your team takes meeting notes in Notion — standups, strategy sessions, customer calls, board meetings. After weeks of meetings, patterns hide in plain sight: recurring decisions never executed, action items forgotten, themes nobody synthesized. This job pulls meeting pages from a database, extracts their block content, and sends the aggregate to Mave Agent for cross-meeting analysis.

**Flow:** Notion `POST /databases/{id}/query` (meeting notes DB) → `GET /blocks/{page_id}/children` per page → Aggregate text → Mavera `POST /api/v1/mave/chat` → Action items, decisions, themes

### Code

<CodeGroup>
  ```python Python theme={"dark"}
  import os, requests, time

  NOTION = os.environ["NOTION_API_KEY"]
  MV = os.environ["MAVERA_API_KEY"]
  NB = "https://api.notion.com/v1"
  MB = "https://app.mavera.io/api/v1"
  NH = {
      "Authorization": f"Bearer {NOTION}",
      "Notion-Version": "2022-06-28",
      "Content-Type": "application/json",
  }
  MH = {"Authorization": f"Bearer {MV}", "Content-Type": "application/json"}

  MEETINGS_DB_ID = "your-meetings-database-id"

  # 1. Query recent meeting pages
  pages = requests.post(f"{NB}/databases/{MEETINGS_DB_ID}/query", headers=NH, json={
      "filter": {
          "property": "Date",
          "date": {"past_month": {}},
      },
      "sorts": [{"property": "Date", "direction": "descending"}],
      "page_size": 30,
  }).json().get("results", [])

  print(f"Found {len(pages)} meeting pages in the past month")

  # 2. Extract text from each page's blocks
  def extract_text(block):
      """Recursively extract plain text from a Notion block."""
      btype = block.get("type", "")
      content = block.get(btype, {})
      rich_text = content.get("rich_text", [])
      return "".join(t.get("plain_text", "") for t in rich_text)

  def get_page_text(page_id, depth=0):
      """Fetch all blocks from a page and concatenate text."""
      texts = []
      cursor = None
      while True:
          params = {"page_size": 100}
          if cursor:
              params["start_cursor"] = cursor
          r = requests.get(f"{NB}/blocks/{page_id}/children", headers=NH, params=params)
          if r.status_code == 429:
              time.sleep(1)
              continue
          r.raise_for_status()
          data = r.json()
          for block in data.get("results", []):
              text = extract_text(block)
              if text.strip():
                  prefix = "- " if block.get("type") in ("bulleted_list_item", "numbered_list_item", "to_do") else ""
                  texts.append(f"{prefix}{text}")
              if block.get("has_children") and depth < 2:
                  texts.extend(get_page_text(block["id"], depth + 1))
          cursor = data.get("next_cursor")
          if not cursor:
              break
          time.sleep(0.4)
      return texts

  meetings_corpus = []
  for page in pages[:20]:
      props = page.get("properties", {})
      title_parts = props.get("Name", props.get("Title", {})).get("title", [])
      title = "".join(t.get("plain_text", "") for t in title_parts) or "Untitled Meeting"
      date = (props.get("Date", {}).get("date", {}) or {}).get("start", "unknown")

      text_lines = get_page_text(page["id"])
      if text_lines:
          meetings_corpus.append(f"## {title} ({date})\n" + "\n".join(text_lines[:50]))
      time.sleep(0.4)

  corpus = "\n\n---\n\n".join(meetings_corpus)
  print(f"Extracted text from {len(meetings_corpus)} meetings ({len(corpus)} chars)")

  # 3. Mave analysis
  analysis = requests.post(f"{MB}/mave/chat", headers=MH, json={
      "message": (
          f"Meeting intelligence analyst. Analyze {len(meetings_corpus)} meetings from the past month.\n\n"
          f"MEETING NOTES:\n{corpus[:12000]}\n\n"
          "Extract and structure:\n\n"
          "1. **ACTION ITEMS** — Who owes what, by when. Flag overdue or repeated items.\n"
          "2. **DECISIONS MADE** — Key decisions with date and context.\n"
          "3. **RECURRING THEMES** — Topics that appear across 3+ meetings.\n"
          "4. **BLOCKERS & RISKS** — Issues mentioned but unresolved.\n"
          "5. **STRATEGIC PATTERNS** — Higher-level trends across all meetings.\n"
          "6. **FOLLOW-UP RECOMMENDATIONS** — What should happen next based on the patterns.\n\n"
          "Quote directly from the notes. Include meeting titles for attribution."
      ),
  }).json()

  print(f"\n{'='*60}\nMEETING INTELLIGENCE REPORT\n{'='*60}")
  print(analysis.get("content", "")[:3000])
  ```

  ```javascript JavaScript theme={"dark"}
  const NOTION = process.env.NOTION_API_KEY;
  const MV = process.env.MAVERA_API_KEY;
  const NB = "https://api.notion.com/v1";
  const MB = "https://app.mavera.io/api/v1";
  const NH = {
    Authorization: `Bearer ${NOTION}`,
    "Notion-Version": "2022-06-28",
    "Content-Type": "application/json",
  };
  const MH = { Authorization: `Bearer ${MV}`, "Content-Type": "application/json" };

  const MEETINGS_DB_ID = "your-meetings-database-id";

  // 1. Query meeting pages
  const pages = await fetch(`${NB}/databases/${MEETINGS_DB_ID}/query`, {
    method: "POST", headers: NH,
    body: JSON.stringify({
      filter: { property: "Date", date: { past_month: {} } },
      sorts: [{ property: "Date", direction: "descending" }],
      page_size: 30,
    }),
  }).then(r => r.json()).then(d => d.results || []);

  console.log(`Found ${pages.length} meeting pages`);

  // 2. Extract page text
  function extractText(block) {
    const content = block[block.type] || {};
    return (content.rich_text || []).map(t => t.plain_text).join("");
  }

  async function getPageText(pageId, depth = 0) {
    const texts = [];
    let cursor = null;
    do {
      const params = new URLSearchParams({ page_size: "100" });
      if (cursor) params.set("start_cursor", cursor);
      const res = await fetch(`${NB}/blocks/${pageId}/children?${params}`, { headers: NH });
      if (res.status === 429) { await new Promise(r => setTimeout(r, 1000)); continue; }
      const data = await res.json();
      for (const block of data.results || []) {
        const text = extractText(block);
        if (text.trim()) {
          const prefix = ["bulleted_list_item", "numbered_list_item", "to_do"].includes(block.type) ? "- " : "";
          texts.push(`${prefix}${text}`);
        }
        if (block.has_children && depth < 2) texts.push(...await getPageText(block.id, depth + 1));
      }
      cursor = data.next_cursor;
      await new Promise(r => setTimeout(r, 400));
    } while (cursor);
    return texts;
  }

  const meetingsCorpus = [];
  for (const page of pages.slice(0, 20)) {
    const props = page.properties || {};
    const titleProp = props.Name || props.Title || {};
    const title = (titleProp.title || []).map(t => t.plain_text).join("") || "Untitled";
    const date = props.Date?.date?.start || "unknown";

    const textLines = await getPageText(page.id);
    if (textLines.length) meetingsCorpus.push(`## ${title} (${date})\n${textLines.slice(0, 50).join("\n")}`);
    await new Promise(r => setTimeout(r, 400));
  }

  const corpus = meetingsCorpus.join("\n\n---\n\n");
  console.log(`Extracted ${meetingsCorpus.length} meetings (${corpus.length} chars)`);

  // 3. Mave analysis
  const analysis = await fetch(`${MB}/mave/chat`, { method: "POST", headers: MH,
    body: JSON.stringify({
      message: `Meeting analyst. ${meetingsCorpus.length} meetings, past month.\n\n${corpus.slice(0, 12000)}\n\nExtract: 1) ACTION ITEMS (who, what, when) 2) DECISIONS 3) RECURRING THEMES (3+ meetings) 4) BLOCKERS 5) STRATEGIC PATTERNS 6) FOLLOW-UP RECOMMENDATIONS. Quote from notes with meeting titles.`,
    }),
  }).then(r => r.json());

  console.log(`\n${"=".repeat(60)}\nMEETING INTELLIGENCE REPORT`);
  console.log((analysis.content || "").slice(0, 3000));
  ```
</CodeGroup>

### Example Output

```text theme={"dark"}
Found 24 meeting pages in the past month
Extracted text from 20 meetings (18432 chars)

MEETING INTELLIGENCE REPORT
============================================================

## 1. ACTION ITEMS
- @Sarah: Finalize Q3 messaging framework (due Mar 7, mentioned in
  "Marketing Sync 3/3" and "Brand Review 3/5" — appears overdue)
- @Dev Team: Ship API v2 pagination (from "Sprint Planning 3/1",
  blocked by schema decision — see Blockers)
- @Mike: Schedule customer advisory board (mentioned 3 times,
  no progress noted)

## 2. DECISIONS MADE
- [3/5] Brand Review: Approved new tagline "Ship faster, learn faster"
- [3/3] Marketing Sync: Moved product launch from April 1 → April 15
- [3/1] Sprint Planning: Prioritized mobile onboarding over desktop

## 3. RECURRING THEMES (4+ meetings)
- "Customer onboarding friction" (7/20 meetings)
- "Enterprise pricing model" (5/20 meetings)
- "Competitor X free tier response" (4/20 meetings)

## 4. BLOCKERS
- API schema decision blocking 3 downstream features
- Legal review of new Terms of Service (2 weeks, no owner assigned)

## 5. FOLLOW-UP RECOMMENDATIONS
- Assign owner to ToS legal review immediately
- Escalate API schema decision to CTO — blocking velocity
- Consolidate "enterprise pricing" discussions into single meeting
```

### Error Handling

<AccordionGroup>
  <Accordion title="Nested blocks">Notion supports nested content (toggles, callouts with children). The code recurses up to depth 2. For deeply nested pages, increase the depth limit but watch rate limits.</Accordion>
  <Accordion title="Large pages">Pages with 200+ blocks require pagination via `start_cursor`. The code handles this automatically. Very large pages may hit the 12K character corpus limit — increase for thorough analysis.</Accordion>
  <Accordion title="Date property filter">The `past_month` filter requires the property to be a `date` type. If your database uses `created_time` instead, change the filter to `{"timestamp": "created_time", "created_time": {"past_month": {}}}`.</Accordion>
  <Accordion title="Missing page permissions">Each meeting page must be shared with the integration. If pages are in a shared workspace, sharing the parent database shares all child pages automatically.</Accordion>
</AccordionGroup>