Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@fast_award_screener_mcp Screen RFQ SPE5E124Q0001 for viability"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
DK Elite AI Solutions — DIBBS Fast Award Screener
Screens DIBBS RFQs for micro-purchase viability against your Net30 + sub-$1K + 1–2 business day threshold. Zero LLM calls in the pipeline — pure deterministic logic.
screen_rfq / screen_rfq_batch
│
▼
┌─────────────────────────────────────┐
│ Node 1: parse_rfq │ ← PDF fetch + regex extraction
│ Node 2: check_flags │ ← QPL/Berry/CMMC/ITAR/CAI/HAZMAT
│ Node 3: score_opportunity │ ← 0–100 score across 5 dimensions
│ Node 4: lookup_grainger │ ← Price + margin (skipped if disq'd)
└─────────────────────────────────────┘
│
▼
HITL Summary → Zapier → Gmail/Slack → You approve → DIBBS Fast TrakRelated MCP server: GovCon
Tool | Description |
| Full pipeline for one RFQ |
| Parallel screen up to 10 RFQs, ranked by score |
| Reference: what each disqualifying flag means |
cd fast_award_screener_mcp
pip install -r requirements.txt
python -m py_compile server.py && echo "✅ Syntax OK"Add to ~/Library/Application Support/Claude/claude_desktop_config.json:
{
"mcpServers": {
"fast_award_screener": {
"command": "python",
"args": ["/path/to/fast_award_screener_mcp/server.py"],
"env": {}
}
}
}python server.py --transport streamable_http --port 8001
# Then expose via ngrok:
ngrok http 8001Zapier webhook → POST to ngrok URL → tool screen_rfq_batch → parse summary → Gmail HITL alert
Dimension | Max | Notes |
Delivery window | 30 | ≤1 day = 30pts, ≤2 day = 22pts |
Total value | 25 | $50–$500 sweet spot |
Set-aside match | 20 | WOSB = 20pts, SB = 14pts |
Quantity | 15 | ≤10 units = 15pts |
Price clarity | 10 | Known price = 10pts |
Thresholds: BID ≥ 65 | REVIEW 40–64 | SKIP < 40
fast_award_screener_mcp/
├── server.py ← FastMCP server + 3 tools
├── state.py ← Single RFQState TypedDict (consolidated)
├── requirements.txt
├── nodes/
│ ├── __init__.py
│ ├── parse_rfq.py ← Node 1: PDF parsing
│ ├── check_flags.py ← Node 2: Disqualifying clauses
│ ├── score_opportunity.py ← Node 3: Viability scoring
│ └── lookup_grainger.py ← Node 4: Grainger price lookup
└── README.mdThis server cannot be deployed
Federal+SLED govcon MCP: SAM, USASpending, recompete, hearings, policy intel, search. Private AI.
U.S. federal contract opportunities from SAM.gov. Daily updates. Public Domain.
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