Meeting Notes → Mave Research

import os, requests, time

HS = os.environ["HUBSPOT_ACCESS_TOKEN"]
MV = os.environ["MAVERA_API_KEY"]

# 1. Pull recent meetings
r = requests.post("https://api.hubapi.com/crm/v3/objects/meetings/search",
    headers={"Authorization": f"Bearer {HS}"},
    json={
        "filterGroups": [{"filters": [{"propertyName": "hs_meeting_outcome", "operator": "HAS_PROPERTY"}]}],
        "properties": ["hs_meeting_title", "hs_meeting_body", "hs_internal_meeting_notes", "hs_meeting_outcome"],
        "sorts": [{"propertyName": "hs_meeting_start_time", "direction": "DESCENDING"}],
        "limit": 25,
    })
if r.status_code == 429: time.sleep(1)
r.raise_for_status()
meetings = r.json().get("results", [])

# 2. Aggregate notes
notes = []
for m in meetings:
    p = m.get("properties", {})
    body = p.get("hs_internal_meeting_notes") or p.get("hs_meeting_body") or ""
    if body.strip():
        notes.append(f"Meeting: {p.get('hs_meeting_title','Untitled')}\nOutcome: {p.get('hs_meeting_outcome','')}\n{body[:500]}")

block = "\n\n---\n\n".join(notes[:20])

# 3. Mave synthesis
mave = requests.post("https://app.mavera.io/api/v1/mave/chat",
    headers={"Authorization": f"Bearer {MV}", "Content-Type": "application/json"},
    json={"message": f"""Synthesize key themes, objections, competitive mentions, and feature requests
from these {len(notes)} prospect meetings.

For each theme: frequency, representative quotes, strategic recommendation.
Top 3 objections with suggested responses. Competitive products mentioned.

{block}"""}).json()

print("--- Meeting Intelligence ---")
print(mave.get("content", "")[:2000])

const HS = process.env.HUBSPOT_ACCESS_TOKEN;
const MV = process.env.MAVERA_API_KEY;

// 1. Pull meetings
const meetings = await fetch("https://api.hubapi.com/crm/v3/objects/meetings/search", {
  method: "POST",
  headers: { Authorization: `Bearer ${HS}`, "Content-Type": "application/json" },
  body: JSON.stringify({
    filterGroups: [{ filters: [{ propertyName: "hs_meeting_outcome", operator: "HAS_PROPERTY" }] }],
    properties: ["hs_meeting_title", "hs_meeting_body", "hs_internal_meeting_notes", "hs_meeting_outcome"],
    sorts: [{ propertyName: "hs_meeting_start_time", direction: "DESCENDING" }],
    limit: 25,
  }),
}).then(r => r.json()).then(d => d.results || []);

// 2. Aggregate
const notes = meetings.map(m => {
  const p = m.properties || {};
  const body = p.hs_internal_meeting_notes || p.hs_meeting_body || "";
  return body.trim() ? `Meeting: ${p.hs_meeting_title || "Untitled"}\nOutcome: ${p.hs_meeting_outcome || ""}\n${body.slice(0, 500)}` : null;
}).filter(Boolean);

// 3. Mave synthesis
const mave = await fetch("https://app.mavera.io/api/v1/mave/chat", {
  method: "POST",
  headers: { Authorization: `Bearer ${MV}`, "Content-Type": "application/json" },
  body: JSON.stringify({
    message: `Synthesize key themes, objections, competitive mentions from these ${notes.length} meetings.\n\n${notes.slice(0, 20).join("\n\n---\n\n")}`,
  }),
}).then(r => r.json());

console.log("--- Meeting Intelligence ---");
console.log((mave.content || "").slice(0, 2000));