Government Contract Intelligence MCP Server

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?

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 input parameters

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

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.

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

# Run a full bid intelligence score
curl -X POST "https://government-contract-intelligence-mcp.apify.actor/mcp" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_APIFY_TOKEN" \
  -d '{
    "jsonrpc": "2.0",
    "method": "tools/call",
    "params": {
      "name": "bid_intelligence_score",
      "arguments": {
        "query": "zero trust network access DoD",
        "companyName": "Leidos"
      }
    },
    "id": 1
  }'

# List available tools
curl -X POST "https://government-contract-intelligence-mcp.apify.actor/mcp" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_APIFY_TOKEN" \
  -d '{"jsonrpc":"2.0","method":"tools/list","params":{},"id":1}'

How the Government Contract Intelligence MCP Server works

Data orchestration layer

The server uses a runActorsParallel() function that fires all required Apify actors simultaneously via Promise.all(). For bid_intelligence_score — the most comprehensive tool — 9 actors run in parallel with a 120-second timeout each, called with memory: 256 and up to 50 records per source. The parallel architecture means the full 9-source assessment typically completes in 90-120 seconds. The actor client maps each source to a named actor: ryanclinton/sam-gov-contract-monitor, ryanclinton/usaspending-search, ryanclinton/grants-gov-search, ryanclinton/federal-register-search, ryanclinton/congress-bill-search, ryanclinton/senate-lobbying-search, ryanclinton/fec-campaign-finance, ryanclinton/congress-stock-tracker, and ryanclinton/company-deep-research.

Scoring engine

The four scoring models in scoring.ts each take the raw actor output and apply tiered point assignments based on record volume and content signals.

Contract Pipeline Predictor awards up to 30 points for active SAM.gov opportunity count (>10 = 30 pts, >3 = 20 pts), up to 20 points for Federal Register volume, up to 15 points each for Grants.gov and congressional bill momentum, and up to 20 points for USAspending obligations including a $1B+ threshold bonus.

Incumbent Advantage Score awards points for SAM.gov contract history depth (>20 records = 30 pts), lobbying filing density (>20 filings = 25 pts), FEC contribution volume (>10 records = 20 pts), USAspending award history (>10 awards = 15 pts), and company research presence (10 pts). Labels run from OPEN FIELD (0-14) through FORTRESS INCUMBENT (70+).

Political Wind Analysis uses a -100 to +100 scale. Positive signals: passed bills (+30 max), introduced bills (+15 max), Federal Register activity (+15 max), STOCK Act purchase majority (+20). Negative signal: STOCK Act sell majority (-20). The buy/sell signal triggers only when one direction exceeds 2x the other with at least 3 trades, filtering out noise from thin trading activity. Lobbying volume and FEC activity each add up to +10.

Agency Spending Velocity weights USAspending obligation totals most heavily (up to 30 pts for $1B+), followed by SAM.gov solicitation volume (up to 25 pts), Grants.gov pipeline (up to 20 pts), Federal Register spending notices (up to 15 pts for solicitation/RFP/RFI/funding/appropriation/award keywords), and appropriation/authorization bill presence (10 pts).

Composite score formula: (Pipeline × 0.35) + (Velocity × 0.25) + ((Wind + 100)/2 × 0.20) + ((100 - Incumbent) × 0.20). The incumbent component is inverted so high incumbent scores reduce the overall opportunity rating.

MCP transport and standby architecture

The server runs as an Express HTTP application on the Apify Standby port. It uses StreamableHTTPServerTransport with sessionIdGenerator: undefined for fully stateless operation — each POST to /mcp creates a fresh MCP server instance, processes the request, and tears it down, making it safe for concurrent calls. When not in Standby mode, the server starts briefly on port 8080 for a health check and exits after 1 second, satisfying Apify's build system cleanly.

Tips for best results

1. Start with contract_opportunity_search before committing to bid_intelligence_score. The opportunity search costs $0.045 and tells you immediately whether there are active SAM.gov listings. If there are zero active opportunities, a full bid intelligence run may not add enough value to justify the call.

2. Include a companyName in bid_intelligence_score when analyzing a known space. Providing the dominant incumbent's name enriches the FEC and company research queries, producing more specific Incumbent Advantage findings rather than generic sector-level signals.

3. Use NAICS codes in contract_opportunity_search for competitive spaces. Broad keyword queries on topics like "cloud" or "cybersecurity" return a wide but shallow result set. NAICS filtering (541512 = Computer Systems Design, 541519 = Other IT Services, 336411 = Aircraft Manufacturing) narrows to directly relevant opportunities.

4. Interpret Political Wind scores directionally, not absolutely. A score of +15 (MILD TAILWIND) in a large, well-established procurement market is more meaningful than +40 in an emerging category with thin lobbying data. Read the findings array to understand the evidence base before drawing conclusions.

5. Combine regulatory_impact_tracker with political_wind_report for compliance-driven markets. For sectors like healthcare IT, nuclear energy, or financial services where regulation directly creates procurement requirements, running both tools gives you the full picture: what is currently being regulated (tracker) and which direction policy is moving (wind report).

6. Run competitive_landscape_map before incumbent_contractor_analysis. The landscape map identifies the top contractors by award volume — this tells you which company name to investigate further with the incumbent analysis tool, rather than guessing based on general market knowledge.

7. Schedule weekly political_wind_report runs for priority sectors. Congressional activity and STOCK Act trades change week to week. A scheduled run with webhook notification lets your team react to legislative signals before competitors do.

Combine with other Apify actors

Limitations

• Federal procurement only. This server covers US federal contracts, spending, and grants via SAM.gov and USAspending. State, local, and municipal procurement (SLED) requires separate data sources not included here.
• Search-based retrieval, not comprehensive database access. Each actor query returns up to 50 records matching the search term. Very broad queries (e.g., "IT services") may return a representative sample rather than an exhaustive count. Use specific NAICS codes and keywords for accuracy.
• Scoring models are signal-based, not causal. The Bid Intelligence Score synthesizes correlated signals (lobbying density, congressional activity) into a probability estimate. It does not have access to classified procurement data, internal agency budget documents, or pre-decisional acquisition plans.
• Political Wind Analysis requires sufficient data density. For niche procurement categories with fewer than 3 congressional bills or 5 lobbying filings, the -100 to +100 score will cluster near zero due to sparse signal. The findings array will state this explicitly.
• Company research depth varies by contractor size. The company-deep-research actor returns richer profiles for large, publicly traded defense primes than for small 8(a) firms or recent set-aside awardees with limited web presence.
• No real-time SAM.gov monitoring. The server queries SAM.gov at call time. It does not maintain a watch list or push notifications when new opportunities matching your criteria are posted. Use Apify scheduling to achieve periodic monitoring.
• Congressional stock trade signals have an inherent lag. STOCK Act disclosures are filed within 30-45 days of the transaction, meaning the congressional stock signal reflects trades from the recent past rather than current positions.
• Tool calls have a 120-second timeout per underlying actor. For bid_intelligence_score running all 9 actors in parallel, the total response time is bounded by the slowest individual actor. If one source is temporarily slow, overall response time increases.

Integrations

• Zapier — trigger a procurement_pipeline_forecast run when a new keyword is added to your watchlist, push results to a Zapier table or Google Sheets BD tracker
• Make — build a Make scenario that runs political_wind_report weekly and emails a summary to your government affairs team
• Google Sheets — export bid_intelligence_score outputs to a Google Sheets opportunity tracker, one row per query with score, grade, and recommendation
• Apify API — call the MCP server programmatically from any language using HTTP POST to /mcp with an Authorization: Bearer header
• Webhooks — receive a webhook notification when a scheduled contract_opportunity_search run completes with new active listings
• LangChain / LlamaIndex — use the Apify LangChain toolkit to wire this MCP server into agentic BD research pipelines that automatically generate bid memos from bid_intelligence_score output

Troubleshooting

• Tool returns empty findings arrays despite an active procurement area — This typically means the search query is too specific or uses internal program names (e.g., a contract vehicle number) that the underlying actors cannot match. Try the plain-language procurement description (e.g., "identity and access management" rather than "HSHQDC-21-D-00001") and add NAICS code filtering for contract_opportunity_search.

• bid_intelligence_score returns a low score for a sector you know is active — Check the dataSources object in the output. If samContracts and usaSpending both return fewer than 5 records, the scoring models have insufficient data. This usually indicates a very narrow query term. Broaden to the capability area (e.g., "cybersecurity" rather than "EDR endpoint detection") and re-run.

• Political Wind score is near zero despite clear legislative activity — The political wind model requires bills with explicit status text containing "passed", "introduced", or "committee" to score. Bills captured with unusual status descriptions may not trigger scoring. Check the congressionalBills count in dataSources — if it is 0, try broadening the query or using official legislative terminology.

• Slow response times on bid_intelligence_score — The tool runs 9 actors in parallel with a 120-second per-actor timeout. On rare occasions when a data source is under load, the full response may take up to 3 minutes. If you consistently see timeouts, split your research across individual tools (contract_opportunity_search + political_wind_report + incumbent_contractor_analysis) to identify which source is slow.

• 401 Unauthorized error from the MCP endpoint — Ensure your Apify API token is included in the Authorization: Bearer YOUR_TOKEN header, not as a query parameter. The Standby endpoint requires authenticated requests.

Responsible use

• This server accesses only publicly available US government data published through official federal databases.
• All data sources — SAM.gov, USAspending, Grants.gov, Federal Register, Congress.gov, Lobbying Disclosure Act, FEC, and the STOCK Act disclosure database — are government-mandated public disclosure systems.
• Congressional stock trade data is published under the STOCK Act (Stop Trading on Congressional Knowledge Act) and is legally required to be public.
• Use extracted data in compliance with applicable regulations, including export control requirements when researching defense procurement.
• Do not use scoring outputs as the sole basis for bid/no-bid decisions without additional due diligence on specific opportunity requirements.
• For guidance on web scraping and data collection legality, see Apify's guide.

FAQ

How current is the government contract data returned by this MCP? All data is fetched live from the underlying federal databases at query time — there is no cache. SAM.gov opportunities reflect currently active and recently closed listings. USAspending awards are updated daily by the federal government. Congressional data and Federal Register entries reflect publications as of the query date.

How do I search for government contracts in a specific agency like DoD or HHS? Include the agency name or abbreviation in your query (e.g., "cybersecurity DoD", "electronic health records HHS"). For agency_spending_analysis, you can also pass an explicit agency parameter to filter USAspending results to a specific awarding agency.

Can this government contract intelligence server identify set-aside opportunities for small businesses? Yes. SAM.gov contract opportunities include set-aside type when specified: 8(a), HUBZone, SDVOSB (Service-Disabled Veteran-Owned Small Business), WOSB (Women-Owned Small Business), and SBA Total Small Business. These appear in the setAside field of each opportunity returned by contract_opportunity_search.

How accurate is the Bid Intelligence Score? The score synthesizes publicly available signals — it is not a prediction of award outcome. It indicates the strength of observable procurement activity, political tailwinds, incumbent entrenchment, and budget velocity. A score of 75+ indicates a market with strong, corroborated signals across multiple sources. Treat it as a prioritization tool, not a guarantee.

How is this different from BGov or Deltek GovWin? BGov and GovWin provide subscription-based platforms with additional features like relationship tracking and CRM integration, but cost $6,000-15,000/year per seat with annual contracts. This MCP server costs $0.045 per query with no subscription, no seat licensing, and no contract. It is designed to be called from within your AI assistant for on-demand research rather than as a standalone platform.

Does this cover state and local government contracts? No. The server focuses exclusively on US federal procurement via SAM.gov, USAspending, and related federal databases. State and local procurement (SLED market) requires separate data sources. This is a known limitation.

Can I use this government contract intelligence MCP with Claude Projects or Claude.ai? Yes, if your Claude plan supports custom MCP servers. Add the server URL and API token to your MCP configuration. Claude Projects can then call the tools inline during research conversations.

How does the incumbent analysis work if a company has multiple subsidiaries or operating divisions? The incumbent_contractor_analysis tool searches using the exact company name provided. For large primes with subsidiaries (e.g., "GDIT" vs. "General Dynamics Information Technology" vs. "General Dynamics"), you may need to run separate queries for each entity name to capture the full picture. Combine results manually or ask your AI assistant to synthesize across multiple queries.

Is it legal to use congressional stock trade data for business intelligence? Yes. Congressional members are required by the STOCK Act to publicly disclose stock transactions within 30-45 days. The disclosure database is publicly accessible at the US House and Senate financial disclosure portals. Using this data for business intelligence and political risk analysis is legal. See Apify's guide on web scraping legality.

Can I schedule this MCP server to run regular opportunity monitoring? Yes. Use Apify's scheduling feature to trigger a contract_opportunity_search or procurement_pipeline_forecast run on a daily or weekly schedule. Combine with webhooks or the Zapier/Make integration to push results to your BD team automatically when new opportunities match your criteria.

What happens if one of the 9 data sources fails during a bid_intelligence_score call? Individual actor failures are caught and return empty arrays rather than crashing the entire call. The scoring models are designed to handle missing data gracefully — a failed source contributes zero to its scoring dimension, and the dataSources count in the output will show 0 for that source, making it transparent which inputs were unavailable.

How many tool calls can I make per month on the free tier? Apify's free tier includes $5 of monthly credits. At $0.045 per tool call, that covers approximately 111 tool calls per month — enough for a meaningful evaluation of the server's capabilities across multiple procurement areas.

Help us improve

If you encounter issues, you can help us debug faster by enabling run sharing in your Apify account:

1. Go to Account Settings > Privacy
2. Enable Share runs with public Actor creators

This lets us see your run details when something goes wrong, so we can fix issues faster. Your data is only visible to the actor developer, not publicly.

Support

Found a bug or have a feature request? Open an issue in the Issues tab on this actor's page. For custom scoring models, additional data sources, or enterprise procurement research integrations, reach out through the Apify platform.