Government Contract Intelligence MCP Server

> View on ApifyForge | Use on Apify Store

---

Quick Start

Add to your MCP client (Claude Desktop, Cursor, Windsurf):

{
  "mcpServers": {
    "government-contract-intelligence-mcp": {
      "url": "https://ryanclinton--government-contract-intelligence-mcp.apify.actor/mcp"
    }
  }
}

---

Government contract intelligence at your AI assistant's fingertips: this MCP server connects Claude, Cursor, Windsurf, and any MCP-compatible client to 9 federal data sources for live procurement research. It is built for defense contractors, GovTech companies, lobbyists, and government affairs teams who need authoritative bid decisions faster than traditional research allows.

The server dispatches parallel queries across SAM.gov, USAspending, Grants.gov, the Federal Register, congressional records, lobbying disclosures, FEC filings, the STOCK Act database, and company intelligence — then runs four proprietary scoring models to produce a composite Bid Intelligence Score. Manual research across these 9 databases takes 6-8 hours per opportunity. This server returns structured intelligence in under 3 minutes, per query, with no subscription fee.

What federal procurement data can you access?

| Data Point | Source | Example |
|---|---|---|
| 📋 Active contract opportunities | SAM.gov | "Cybersecurity Operations Support — DoD — NAICS 541512" |
| 💰 Agency spending obligations | USAspending | "CISA: $2.3B obligated — 847 awards" |
| 🏛️ Grant funding opportunities | Grants.gov | "NIH SBIR Phase II — $1.5M ceiling — closes 2026-05-31" |
| 📜 Federal Register entries | Federal Register | "Proposed Rule: CMMC 2.0 implementation — DoD — 2026-02-14" |
| 📊 Congressional bill status | Congress Bills | "S.1842 — Strengthening Cyber Resilience Act — Passed Committee" |
| 🗣️ Lobbying filings | Lobbying Disclosure Act | "Booz Allen Hamilton — 14 filings — $4.2M — Defense IT" |
| 🗳️ Political contributions | FEC Campaign Finance | "Leidos Holdings PAC — $890K — Armed Services Committee" |
| 📈 Congressional stock trades | STOCK Act Disclosures | "Sen. J. Smith — Purchase — Palantir — $50K-100K — 2026-01-15" |
| 🏢 Contractor background | Company Deep Research | "General Dynamics IT — $8.2B revenue — DoD prime contractor" |
| 🎯 Bid Intelligence Score | Composite model | "Score: 72/100 — STRONG OPPORTUNITY — pursue aggressively" |

Why use Government Contract Intelligence MCP Server?

Researching a federal bid opportunity manually means logging into SAM.gov, cross-referencing USAspending for spending history, pulling Federal Register notices, checking Congress.gov for relevant legislation, reviewing lobbying disclosures, and then trying to synthesize what it all means for your bid strategy. A thorough analyst spends a full day on each opportunity. A typical GovTech BD team pays $20,000-40,000/year for commercial platforms like BGov, Deltek, or GovWin that still require manual interpretation.

This server automates the entire research workflow inside your AI assistant. Ask Claude "What is the procurement landscape for DoD identity management?" and receive a scored, structured intelligence report with source-level findings across all 9 data streams — in one prompt, for $0.045.

Beyond procurement research, the Apify platform adds:

- Scheduling — run daily SAM.gov opportunity monitors and weekly political wind reports on a cron schedule
- API access — call any tool programmatically from Python, JavaScript, or any HTTP client
- Monitoring — receive Slack or email alerts when runs fail or return unexpected results
- Integrations — push intelligence to Google Sheets, Zapier, Make, HubSpot, or webhooks
- Cost controls — set a per-session spending limit so research costs never exceed your budget

Features

- 8 specialized MCP tools covering every phase of the federal business development lifecycle, from opportunity discovery through bid/no-bid scoring
- 9 parallel data sources queried simultaneously — SAM.gov, USAspending, Grants.gov, Federal Register, Congress Bills, Lobbying Disclosure, FEC Campaign Finance, Congressional Stock Tracker, and Company Deep Research
- Contract Pipeline Predictor (0-100) scores upcoming procurement probability from active SAM.gov opportunities (up to 50 per query), Federal Register solicitation notices, Grants.gov funding pipeline, and congressional appropriations signals
- Incumbent Advantage Score (0-100) quantifies recompete difficulty using past contract volume, USAspending award concentration, lobbying filing density, and FEC contribution depth — with labels from OPEN FIELD to FORTRESS INCUMBENT
- Political Wind Analysis (-100 to +100) synthesizes congressional bill progress (introduced vs. passed), congressional member stock trade direction (buy/sell ratio), lobbying expenditure volume, FEC contribution patterns, and Federal Register regulatory intensity
- Agency Spending Velocity Score (0-100) detects budget execution pace from USAspending obligation totals, active SAM.gov solicitation volume, Grants.gov pipeline size, and Federal Register appropriation notices — with labels from DORMANT to RAPID EXECUTION
- Composite Bid Intelligence Score (0-100) weights all four models: Pipeline 35%, Spending Velocity 25%, Political Wind 20%, Inverse Incumbent 20% — produces grades from WEAK OPPORTUNITY to PRIME OPPORTUNITY with an actionable recommendation
- NAICS code filtering for contract_opportunity_search to narrow results to specific industry classifications
- Agency-level spending analysis — agency_spending_analysis aggregates USAspending awards by awarding agency, surfaces top 10 agencies by total obligations, and lists recent award recipients
- Competitive landscape mapping — competitive_landscape_map extracts unique contractors from USAspending, ranks them by total awarded amount, and surfaces the top lobbying firms active in the space
- Regulatory change tracking — regulatory_impact_tracker categorizes Federal Register entries into final rules, proposed rules, and notices, then cross-references congressional bills by status
- Stateless MCP architecture using StreamableHTTPServerTransport — each request creates and tears down a fresh server instance; no session state, no cleanup required
- Pay-per-event billing with Actor.charge() — spending limit checks are enforced per tool call so you never exceed your budget mid-run
- Runs in Apify Standby mode — the server stays warm and responds immediately; no cold-start latency on tool calls

Use cases for government contract intelligence

Defense contractor bid/no-bid decisions

BD directors at defense primes and sub-contractors need to decide within 72 hours of a SAM.gov posting whether to pursue a bid. Running bid_intelligence_score for the opportunity keyword produces a scored report across all 9 data sources: active pipeline depth, entrenched incumbents, political tailwinds from congressional appropriations, and agency spending velocity. A score of 70+ triggers aggressive pursuit; below 35 means monitor only. What previously took a BD analyst two days now takes one AI prompt.

GovTech market entry and segment selection

Technology companies entering the federal market need to identify which agencies are spending, on what, and how fast. The agency_spending_analysis tool surfaces total obligation volumes and top award recipients for any search term, while procurement_pipeline_forecast shows whether a market segment is heating up or cooling down based on legislative and regulatory signals. Teams use this to prioritize their IDIQ pursuit strategy before investing in capture management.

Recompete competitive intelligence

Winning a recompete requires understanding exactly how entrenched the incumbent is. incumbent_contractor_analysis pulls the target company's full contract history from SAM.gov and USAspending, counts their lobbying filings and political contributions, and produces an Incumbent Advantage Score with specific findings: "14 lobbying records — established political relationships" or "FORTRESS INCUMBENT — deep political giving, 20+ contract records." This tells a challenger whether to compete directly, seek a teaming arrangement, or walk away.

Political risk and regulatory impact assessment

Government affairs teams and lobbyists use political_wind_report to track whether a sector's political environment is expanding or contracting. The tool monitors congressional member stock trades for buy/sell signals, tracks bills from introduction through committee to the floor, measures lobbying expenditure density, and correlates FEC contribution patterns — then distills this into a directional score from STRONG HEADWIND to STRONG TAILWIND with specific findings attached.

Lobby strategy and coalition building

competitive_landscape_map identifies all lobbying firms active in a procurement space, ranked by filing volume. Advocacy teams use this to see who is already shaping policy, which firms are concentrated around specific agencies, and where gaps in political coverage exist. Combined with FEC contribution data from political_wind_report, this builds a complete picture of how influence flows in a given procurement area.

Grant and SBIR opportunity pipeline

Research institutions, universities, and small businesses targeting federal R&D funding use contract_opportunity_search to surface active Grants.gov listings alongside SAM.gov opportunities in a single call. The tool returns funding ceiling, close date, and agency for each grant — structured data that feeds directly into grant pipeline management workflows.

How to use government contract intelligence with your AI assistant

1. Connect the MCP server — add the server URL https://government-contract-intelligence-mcp.apify.actor/mcp to your MCP client config with your Apify API token as the Authorization: Bearer header. See the connection examples below.
2. Choose your research query — use a procurement area (e.g., "zero trust network access DoD"), a company name (e.g., "Leidos"), or a combined query (e.g., "cloud migration federal civilian agencies").
3. Call the right tool — start with contract_opportunity_search for active listings, bid_intelligence_score for a full assessment, or political_wind_report for sector-level political analysis. Most tools return results in 60-120 seconds.
4. Review the structured output — each tool returns a JSON response with scored findings, source record counts, and specific observations. Ask your AI assistant to summarize, compare, or generate a BD memo from the output.

MCP tools

| Tool | Price | Data sources queried | Description |
|------|-------|----------------------|-------------|
| contract_opportunity_search | $0.045 | SAM.gov, Grants.gov | Active federal contract opportunities and grant funding with optional NAICS code filtering |
| agency_spending_analysis | $0.045 | USAspending | Agency obligation totals, top awarding agencies, recent award recipients |
| procurement_pipeline_forecast | $0.045 | SAM.gov, Federal Register, Grants.gov, Congress Bills | Pipeline probability score with Contract Pipeline Predictor model |
| incumbent_contractor_analysis | $0.045 | SAM.gov, USAspending, Lobbying Disclosure, FEC, Company Research | Incumbent Advantage Score (0-100) with labeled assessment |
| political_wind_report | $0.045 | Congress Bills, Congressional Stock Tracker, Lobbying Disclosure, FEC, Federal Register | Political Wind score (-100 to +100) with directional label |
| competitive_landscape_map | $0.045 | SAM.gov, USAspending, Lobbying Disclosure | Top contractors by award volume, top lobbying firms by filing count |
| regulatory_impact_tracker | $0.045 | Federal Register, Congress Bills | Final rules, proposed rules, notices, and bill status by topic |
| bid_intelligence_score | $0.045 | All 9 sources | Composite Bid Intelligence Score (0-100) with grade, four sub-scores, and recommendation |

Tool input parameters

| Tool | Parameter | Type | Required | Description |
|------|-----------|------|----------|-------------|
| contract_opportunity_search | query | string | Yes | Procurement keyword or topic |
| contract_opportunity_search | naicsCode | string | No | NAICS code to filter results (e.g., "541512") |
| agency_spending_analysis | query | string | Yes | Keyword for spending search |
| agency_spending_analysis | agency | string | No | Specific agency name to filter awards |
| procurement_pipeline_forecast | query | string | Yes | Procurement area to forecast |
| incumbent_contractor_analysis | companyName | string | Yes | Name of the contractor to analyze |
| incumbent_contractor_analysis | query | string | No | Contract space query if different from company name |
| political_wind_report | query | string | Yes | Sector or topic for political analysis |
| competitive_landscape_map | query | string | Yes | Procurement space to map |
| regulatory_impact_tracker | query | string | Yes | Topic or keyword for regulatory search |
| bid_intelligence_score | query | string | Yes | Procurement area keyword |
| bid_intelligence_score | companyName | string | No | Incumbent or competitor company name for enhanced analysis |

Example tool calls

Search for active DoD cybersecurity contracts with NAICS filtering:

{

  "tool": "contract_opportunity_search",

  "arguments": {

    "query": "zero trust network access",

    "naicsCode": "541512"

  }

}

Full bid intelligence score for a defense IT opportunity:

{

  "tool": "bid_intelligence_score",

  "arguments": {

    "query": "identity and access management DoD",

    "companyName": "Leidos"

  }

}

Political wind assessment for healthcare IT procurement:

{

  "tool": "political_wind_report",

  "arguments": {

    "query": "electronic health records VA HHS"

  }

}

Output example

{
  "query": "zero trust network access DoD",
  "bidIntelligenceScore": 72,
  "grade": "STRONG OPPORTUNITY",
  "models": {
    "contractPipeline": {
      "score": 82,
      "label": "HOT PIPELINE",
      "findings": [
        "14 active SAM.gov opportunities — hot market",
        "18 Federal Register entries — significant regulatory activity",
        "7 Grants.gov opportunities — strong funding pipeline",
        "8 relevant bills in Congress — legislative momentum",
        "43 USAspending records — proven federal spending area",
        "$1.4B in historical obligations — massive market"
      ]
    },
    "incumbentAdvantage": {
      "score": 61,
      "label": "STRONG INCUMBENT",
      "findings": [
        "22 SAM.gov contract records — deeply entrenched incumbents",
        "18 lobbying records — established political relationships",
        "12 FEC contribution records — deep political giving",
        "43 USAspending awards — proven delivery track record",
        "Company research data confirms market presence"
      ]
    },
    "politicalWind": {
      "score": 38,
      "direction": "STRONG TAILWIND",
      "findings": [
        "2 passed bills — some legislative support",
        "11 introduced bills — high legislative interest",
        "18 Federal Register entries — active regulatory attention",
        "Congressional stock signal BULLISH: 7 buys vs 2 sells — lawmakers betting on growth",
        "18 lobbying filings — industry actively shaping policy",
        "12 FEC contributions — political finance activity"
      ]
    },
    "spendingVelocity": {
      "score": 75,
      "label": "RAPID EXECUTION",
      "findings": [
        "22 SAM.gov records — high procurement velocity",
        "$1.4B obligated — massive spending velocity",
        "7 grant opportunities",
        "4 spending-related Federal Register notices",
        "3 appropriation/authorization bill(s) — budget pipeline active"
      ]
    }
  },
  "recommendation": "Moderate opportunity. Some procurement activity detected. Conduct targeted BD before bidding.",
  "dataSources": {
    "samContracts": 22,
    "usaSpending": 43,
    "grants": 7,
    "federalRegister": 18,
    "congressBills": 11,
    "lobbying": 18,
    "fecContributions": 12,
    "congressStockTrades": 9,
    "companyResearch": 3
  }
}

Output fields

| Field | Type | Description |
|-------|------|-------------|
| query | string | The search query used |
| bidIntelligenceScore | number | Composite score 0-100 |
| grade | string | WEAK / MODERATE / STRONG / PRIME OPPORTUNITY |
| recommendation | string | Actionable bid strategy guidance |
| models.contractPipeline.score | number | Pipeline Predictor score 0-100 |
| models.contractPipeline.label | string | COLD / MODERATE / ACTIVE / HOT PIPELINE |
| models.contractPipeline.findings | string[] | Specific data-backed evidence items |
| models.incumbentAdvantage.score | number | Incumbent Advantage score 0-100 |
| models.incumbentAdvantage.label | string | OPEN FIELD / MODERATE / STRONG / FORTRESS INCUMBENT |
| models.incumbentAdvantage.findings | string[] | Specific evidence of incumbent entrenchment |
| models.politicalWind.score | number | Political Wind score -100 to +100 |
| models.politicalWind.direction | string | STRONG HEADWIND / MILD HEADWIND / NEUTRAL / MILD TAILWIND / STRONG TAILWIND |
| models.politicalWind.findings | string[] | Political signal observations |
| models.spendingVelocity.score | number | Agency Spending Velocity score 0-100 |
| models.spendingVelocity.label | string | DORMANT / SLOW BURN / STEADY SPENDING / RAPID EXECUTION |
| models.spendingVelocity.findings | string[] | Budget execution evidence items |
| dataSources.* | number | Record count returned from each of the 9 data sources |

For individual tools: contract_opportunity_search returns samGov.opportunities[] and grantsGov.opportunities[]; competitive_landscape_map returns topContractors[] and topLobbyists[]; regulatory_impact_tracker returns federalRegister.finalRules, .proposedRules, .notices, and congressionalBills.bills[].

How much does it cost to use this government contract intelligence MCP?

This MCP server uses pay-per-event pricing — you pay $0.045 per tool call. Platform compute costs are included. There is no subscription fee, no monthly minimum, and no charge for idle time while the server is in Standby.

| Scenario | Tool calls | Cost per call | Total cost |
|----------|-----------|---------------|------------|
| Quick opportunity check | 1 | $0.045 | $0.045 |
| Bid/no-bid workflow | 3 | $0.045 | $0.135 |
| Weekly BD pipeline review | 10 | $0.045 | $0.45 |
| Monthly capture management | 50 | $0.045 | $2.25 |
| Enterprise BD team (daily use) | 200 | $0.045 | $9.00 |

You can set a maximum spending limit per session in your MCP client or Apify actor run configuration. The server enforces this limit per tool call via Actor.charge() and returns a structured error rather than silently over-charging.

Compare this to BGov at $8,000-15,000/year, Deltek GovWin at $6,000-12,000/year, or Bloomberg Government at $6,000+/year. Most users running 200-500 tool calls per month spend under $25/month with no subscription commitment and no seat licensing.

The Apify Free plan includes $5 of monthly platform credits — enough for 100+ tool calls to explore the server before committing to paid usage.

Connect to this government contract intelligence MCP server

Claude Desktop

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "government-contract-intelligence": {
      "url": "https://government-contract-intelligence-mcp.apify.actor/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_APIFY_TOKEN"
      }
    }
  }
}

Then ask Claude: "Search for active zero trust network access contracts in DoD" or "Run a full bid intelligence score for cloud migration at federal civilian agencies."

Cursor / Windsurf / Cline

Add the same URL and token to your editor's MCP server configuration. The server is stateless — each tool call is independent, so it works correctly in all MCP clients that use the Streamable HTTP transport.

Python

import httpx
import json
APIFY_TOKEN = "YOUR_APIFY_TOKEN"

MCP_URL = "https://government-contract-intelligence-mcp.apify.actor/mcp"
payload = {

    "jsonrpc": "2.0",

    "method": "tools/call",

    "params": {

        "name": "bid_intelligence_score",

        "arguments": {

            "query": "zero trust network access DoD",

            "companyName": "Leidos"

        }

    },

    "id": 1

}
response = httpx.post(

    MCP_URL,

    json=payload,

    headers={"Authorization": f"Bearer {APIFY_TOKEN}"}

)

result = response.json()

data = json.loads(result["result"]["content"][0]["text"])
print(f"Bid Intelligence Score: {data['bidIntelligenceScore']}/100 — {data['grade']}")

print(f"Recommendation: {data['recommendation']}")

print(f"Pipeline: {data['models']['contractPipeline']['label']} ({data['models']['contractPipeline']['score']})")

print(f"Incumbent: {data['models']['incumbentAdvantage']['label']} ({data['models']['incumbentAdvantage']['score']})")

print(f"Political Wind: {data['models']['politicalWind']['direction']} ({data['models']['politicalWind']['score']})")

JavaScript

const APIFY_TOKEN = "YOUR_APIFY_TOKEN";
const MCP_URL = "https://government-contract-intelligence-mcp.apify.actor/mcp";
const response = await fetch(MCP_URL, {

  method: "POST",

  headers: {

    "Content-Type": "application/json",

    "Authorization": Bearer ${APIFY_TOKEN},

  },

  body: JSON.stringify({

    jsonrpc: "2.0",

    method: "tools/call",

    params: {

      name: "bid_intelligence_score",

      arguments: {

        query: "zero trust network access DoD",

        companyName: "Leidos",

      },

    },

    id: 1,

  }),

});
const result = await response.json();

const data = JSON.parse(result.result.content[0].text);
console.log(Score: ${data.bidIntelligenceScore}/100 — ${data.grade});

console.log(Recommendation: ${data.recommendation});

console.log(Data sources queried: SAM.gov (${data.dataSources.samContracts}), USAspending (${data.dataSources.usaSpending}), Lobbying (${data.dataSources.lobbying}));

cURL

```bash