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Flowtion Intelligence MCP Server

An MCP server that monitors 12 Australian SMB intelligence sources to analyze market signals and provide structured data for content strategy agents. It enables users to track regulatory changes, AI trends, and business data through automated signal grading and Slack integration.

glama
Updated
Mar 8, 2026

Flowtion Intelligence MCP Server

A Claude-native Model Context Protocol (MCP) plugin that monitors 12 Australian SMB intelligence sources, analyzes signals for content relevance, and provides structured output for downstream content strategy agents.

🔗 Repository: https://github.com/lovishdhillon21-design/flowtion-mcp


Project Structure

flowtion-mcp/
├── src/
│   └── flowtion/
│       ├── __init__.py           # Package initialization
│       └── server.py             # Main MCP server (10 tools, 1000+ lines)
├── scripts/
│   ├── run_daily.py              # Daily ingestion from 6 sources
│   ├── test_weekly.py            # Weekly ingestion test (all 12 sources)
│   ├── analyze_and_digest.py     # Signal analysis & Slack integration
│   └── send_digest.py            # Standalone digest sender
├── config/
│   ├── .env.example              # Template for API credentials
│   └── .env.local                # (gitignored) Your actual secrets
├── output/
│   ├── weekly_fetch_result.json  # (gitignored) Weekly ingestion output
│   └── weekly_digest.txt         # (gitignored) Generated digest
├── docs/
│   └── README.md                 # Full documentation
├── requirements.txt              # Python dependencies
├── .gitignore                    # Excludes secrets & test outputs
└── README.md                     # This file

Quick Start

1. Install Dependencies

pip install -r requirements.txt

2. Configure API Credentials

Copy the example config:

cp config/.env.example config/.env.local

Edit config/.env.local with your API keys:

3. Run Daily Ingestion

python scripts/run_daily.py

Fetches from 6 high-frequency sources (SmartCompany, The Rundown AI, Reddit, etc.) and returns top content opportunities.


Scripts

ScriptPurposeRun From
scripts/run_daily.pyFetch 6 daily sources, grade signals, show recommendationsRoot directory
scripts/test_weekly.pyFetch all 12 sources, save to output/Root directory
scripts/analyze_and_digest.pyAnalyze results, archive signals, send Slack alertRoot directory
scripts/send_digest.pySend saved digest to SlackRoot directory

Example workflow:

# Run daily
python scripts/run_daily.py

# Or weekly:
python scripts/test_weekly.py
python scripts/analyze_and_digest.py

12 Monitored Sources

Government & Policy (Authority 25-29)

  • S01: DISR / NAIC / CSIRO (29/30)
  • S04: Productivity Commission (27/30)
  • S09: Deloitte Access Economics AU (27/30)
  • S10: ASBFEO (25/30)

SMB-Focused (Authority 24-28)

  • S02: MYOB (28/30)
  • S03: SmartCompany (25/30)
  • S06: QLD AI Hub (24/30)

AI & Automation (Authority 21-23)

  • S07: The Rundown AI (22/30)
  • S08: n8n Blog (23/30)
  • S12: Zapier Blog (21/30)

Community & Content

  • S05: Reddit (r/AusFinance, r/australia) (24/30)
  • S11: LinkedIn Creators (18/30)

Signal Grades

  • Platinum (P) — AU SMB data, regulatory change, breakthrough tools → Act immediately
  • Gold (G) — Strong AU relevance or high SMB utility → Content within 48hrs
  • Silver (S) — Useful background, supports themes → Reference/archive
  • Bronze (B) — Tangentially relevant → File for reference
  • Noise (N) — Not relevant → Discard

Automatic Platinum Triggers

  • DISR Tracker quarterly data
  • Productivity Commission new report
  • Deloitte new AU SMB research
  • MYOB Business Monitor / AI product
  • New government AI grant programs

Full Documentation

See docs/README.md for:

  • Complete architecture & design
  • All 10 MCP tools
  • Signal envelope schema
  • Grading rules & examples
  • Integration patterns

Using as MCP Plugin

To use in Claude / other MCP clients:

{
  "mcpServers": {
    "flowtion": {
      "command": "python",
      "args": ["src/flowtion/server.py"],
      "env": {
        "FIRECRAWL_API_KEY": "...",
        "REDDIT_CLIENT_ID": "...",
        "REDDIT_CLIENT_SECRET": "...",
        "SLACK_BOT_TOKEN": "..."
      }
    }
  }
}

Development

Python Version

3.8+

Key Dependencies

  • httpx — async HTTP requests
  • feedparser — RSS parsing
  • pydantic — input validation
  • mcp — Model Context Protocol

Running Tests

python scripts/test_weekly.py
python scripts/analyze_and_digest.py

License

MIT


Built by: Lovish Dhillon For: Australian SMB content strategy & market intelligence

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