granola-local-dev-loop（格兰诺拉麦片本地开发循环）

Granola Local Dev Loop

Overview

Access Granola meeting data programmatically using three methods: the local cache file (zero-auth, offline), the MCP server (AI agent integration), or the Enterprise API (workspace-wide access). Build developer workflows that turn meeting outcomes into code tasks, documentation, and project artifacts.

Prerequisites

• Granola installed with meetings captured
• Node.js 18+ or Python 3.10+ for scripts
• For MCP: Claude Code, Cursor, or another MCP-compatible client
• For Enterprise API: Business/Enterprise plan + API key

Instructions

Step 1 — Read the Local Cache (Zero Auth)

Granola stores meeting data in a local JSON cache file:

# macOS cache location
CACHE_FILE="$HOME/Library/Application Support/Granola/cache-v3.json"

# Check if cache exists and get size
ls -lh "$CACHE_FILE"

The cache has a double-JSON structure (JSON string inside JSON):

#!/usr/bin/env python3
"""Extract meetings from Granola local cache."""
import json
from pathlib import Path

CACHE_PATH = Path.home() / "Library/Application Support/Granola/cache-v3.json"

def load_granola_cache():
    raw = json.loads(CACHE_PATH.read_text())
    # Cache contains a JSON string that needs secondary parsing
    state = json.loads(raw) if isinstance(raw, str) else raw
    data = state.get("state", state)
    return {
        "documents": data.get("documents", {}),
        "transcripts": data.get("transcripts", {}),
        "meetings_metadata": data.get("meetingsMetadata", {}),
    }

cache = load_granola_cache()
docs = cache["documents"]
print(f"Found {len(docs)} meetings in local cache")

# List recent meetings
for doc_id, doc in sorted(docs.items(),
                          key=lambda x: x[1].get("updated_at", ""),
                          reverse=True)[:10]:
    print(f"  {doc.get('title', 'Untitled')} — {doc.get('updated_at', 'N/A')}")

Step 2 — Set Up Granola MCP Server

Granola's official MCP integration connects meeting context to AI tools:

// claude_desktop_config.json or .mcp.json
{
  "mcpServers": {
    "granola": {
      "command": "npx",
      "args": ["-y", "granola-mcp-server"]
    }
  }
}

With MCP connected, Claude Code and Cursor can:

• Search across all your meetings by topic or person
• Pull context from specific meetings into coding sessions
• Create tickets based on discussed bugs or features
• Scaffold code based on architectural decisions from meetings

Community MCP servers with additional features:

• pedramamini/GranolaMCP — CLI + programmatic + MCP access, reads local cache
• mishkinf/granola-mcp — semantic search with LanceDB vector embeddings
• proofgeist/granola-mcp-server — lightweight local cache reader

Step 3 — Extract Action Items to Dev Tools

#!/usr/bin/env python3
"""Extract action items from Granola notes and create GitHub issues."""
import json, re, subprocess
from pathlib import Path

def extract_action_items(note_content: str) -> list[dict]:
    """Parse action items from enhanced Granola notes."""
    items = []
    # Matches: - [ ] @person: task description
    pattern = r'- \[ \] @?(\w+):?\s+(.+)'
    for match in re.finditer(pattern, note_content):
        items.append({
            "assignee": match.group(1),
            "task": match.group(2).strip(),
        })
    return items

def create_github_issue(repo: str, title: str, body: str, assignee: str):
    """Create a GitHub issue using gh CLI."""
    cmd = [
        "gh", "issue", "create",
        "--repo", repo,
        "--title", title,
        "--body", body,
        "--assignee", assignee,
    ]
    result = subprocess.run(cmd, capture_output=True, text=True)
    if result.returncode == 0:
        print(f"  Created: {result.stdout.strip()}")
    else:
        print(f"  Error: {result.stderr.strip()}")

# Usage with cache data
cache = load_granola_cache()  # from Step 1
for doc_id, doc in cache["documents"].items():
    content = doc.get("last_viewed_panel", {})
    # ProseMirror content needs text extraction
    text = json.dumps(content)  # simplified — parse nodes for production
    actions = extract_action_items(text)
    for action in actions:
        print(f"[{action['assignee']}] {action['task']}")

Step 4 — Sync Meeting Outcomes to Project Docs

#!/bin/bash
set -euo pipefail
# Sync latest Granola meeting notes to project documentation

NOTES_DIR="$HOME/dev/meeting-notes"
mkdir -p "$NOTES_DIR"

# Extract recent meeting titles and dates using Python
python3 -c "
import json
from pathlib import Path

cache_path = Path.home() / 'Library/Application Support/Granola/cache-v3.json'
if cache_path.exists():
    raw = json.loads(cache_path.read_text())
    state = json.loads(raw) if isinstance(raw, str) else raw
    data = state.get('state', state)
    docs = data.get('documents', {})
    for doc_id, doc in sorted(docs.items(),
                              key=lambda x: x[1].get('updated_at', ''),
                              reverse=True)[:5]:
        title = doc.get('title', 'Untitled').replace(' ', '-').lower()
        date = doc.get('created_at', 'unknown')[:10]
        print(f'{date}_{title}')
"

Step 5 — Git Integration Pattern

Reference Granola meetings in commits and PRs:

# Reference meeting in commit message
git commit -m "feat: implement user onboarding flow

Per meeting 2026-03-22 'Sprint Planning Q1':
- Agreed on 3-step wizard approach
- Sarah approved the design mockups
- Due by April 15

Action items from Granola note: [link]"

Output

• Local cache accessible for offline meeting data reads
• MCP server connected for AI-assisted meeting context
• Action item extraction pipeline ready
• Meeting-to-dev-tools sync established

Error Handling

Resources

• Granola MCP Announcement
• GranolaMCP (cache-based)
• Reverse-Engineered API Docs
• Granola Enterprise API

Next Steps

Proceed to granola-sdk-patterns for Zapier automation workflows.