jackpotkeywords-mcp-server

MCP (Model Context Protocol) server for JackpotKeywords — AI-powered keyword research, SEO audits, and AI-visibility scanning. Lets Claude Code, Claude Desktop, Cursor, Windsurf, and other MCP-compatible clients call JackpotKeywords directly.

Five tools available: jackpotkeywords_credit_balance, jackpotkeywords_recommend, jackpotkeywords_recommend_deep, jackpotkeywords_audit, jackpotkeywords_aeo_scan.

Prerequisites

1. A JackpotKeywords API key — generate one at https://jackpotkeywords.web.app/developers (instant, self-serve, $2 starter credit, no card required).
2. Node.js 18 or newer (only if installing locally; npx doesn't require a local Node.js if your MCP client bundles one).

Configure in Claude Code

Recommended — use the CLI:

claude mcp add -s user jackpotkeywords \
  -e JACKPOTKEYWORDS_API_KEY=jk_live_... \
  -- npx -y jackpotkeywords-mcp-server

That writes the server to your user-scope config (~/.claude.json) so it's available in every Claude Code session, in every project. Verify with claude mcp list.

Or hand-edit ~/.claude.json (user scope) or .mcp.json in the project root (project scope), adding to the mcpServers object:

{
  "mcpServers": {
    "jackpotkeywords": {
      "command": "npx",
      "args": ["-y", "jackpotkeywords-mcp-server"],
      "env": {
        "JACKPOTKEYWORDS_API_KEY": "jk_live_..."
      }
    }
  }
}

Important: Claude Code does not read ~/.claude/mcp.json (with the slash). The real user-scope path is ~/.claude.json (with the dot). Use the CLI to avoid this trap.

Restart any open Claude Code session to pick up the new tools — MCP servers load at session start, not dynamically.

Configure in Claude Desktop

Edit ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows):

{
  "mcpServers": {
    "jackpotkeywords": {
      "command": "npx",
      "args": ["-y", "jackpotkeywords-mcp-server"],
      "env": {
        "JACKPOTKEYWORDS_API_KEY": "jk_live_..."
      }
    }
  }
}

Configure in Cursor

Cursor uses the same JSON shape. Settings → MCP → Add Server:

{
  "mcpServers": {
    "jackpotkeywords": {
      "command": "npx",
      "args": ["-y", "jackpotkeywords-mcp-server"],
      "env": { "JACKPOTKEYWORDS_API_KEY": "jk_live_..." }
    }
  }
}

Tools

jackpotkeywords_credit_balance

Returns the current credit balance for your API account.

No arguments. Use it to verify your key works and to check credits before calling the paid tools.

jackpotkeywords_recommend

Runs the full keyword research pipeline for a product and returns ranked recommendations by composite Jackpot Score (volume, CPC, competition, trend, cluster strength, AI relevance). Backed by real Google Ads Keyword Planner data.

Cost: $0.10 per call (flat — regardless of limit). Refunded on pipeline failure. Latency ~60–180s.

| Argument | Type | Required | Description | |---|---|---|---| | url | string | one-of | Product URL to extract context from | | description | string | one-of | Plain-English product description | | limit | number | no | Max recommendations to return. Default 50, max 200. | | budget | number | no | Daily ad budget in USD (influences AI scoring) | | location | string | no | Location for local-intent boosting |

Returns: top 25 recommendations as a readable table in content, with the full ranked list in structuredContent.recommendations.

Example prompt (in Claude Code):

Use jackpotkeywords_recommend on https://bulklistingpro.com — find keywords I should target for SEO and Google Ads for an eBay bulk listing tool. Limit 50.

jackpotkeywords_recommend_deep

Same inputs as jackpotkeywords_recommend, with two server-side additions: competitor discovery runs in parallel with autocomplete (broadens the keyword set with competitor-derived seeds), and the response surfaces the cluster + category + competitor-brand aggregates that the standard recommend tool discards.

Cost: $0.30 per call (flat — regardless of limit). Refunded on pipeline failure. Latency ~75–200s.

| Argument | Type | Required | Description | |---|---|---|---| | url | string | one-of | Product URL to extract context from | | description | string | one-of | Plain-English product description | | limit | number | no | Max recommendations to return. Default 50, max 200. Clusters/categories/competitors not truncated. | | budget | number | no | Daily ad budget in USD (influences AI scoring) | | location | string | no | Location for local-intent boosting |

Returns: top 25 recommendations + top 8 clusters + category distribution + competitor brands in content, with full data in structuredContent.

Example prompt:

Use jackpotkeywords_recommend_deep on https://markitup.app — show me the keyword clusters and competitor brands.

jackpotkeywords_audit

Runs an SEO audit on a URL. Crawls the primary page plus up to 8 priority secondary pages, runs deterministic checks across technical / content / crawlability / structured data / local / social-sharing categories, and uses Gemini for keyword-gap identification + prioritized recommendations. AEO data is not bundled — use jackpotkeywords_aeo_scan for that.

Cost: $0.50 per audit (refunded on failure). Latency ~20–60s.

| Argument | Type | Required | Description | |---|---|---|---| | url | string | yes | URL to audit |

Returns: overall score + per-category scores + top failing/warning checks + top keyword gaps + top recommendations in content. Full check list, per-page results, and all gaps/recs in structuredContent.

Example prompt:

Run jackpotkeywords_audit on https://markitup.app and tell me the top 3 things I should fix.

jackpotkeywords_aeo_scan

Runs an AI-visibility scan. Asks 10 buyer-intent queries about your product through Gemini's grounded search and reports, per query: whether the URL was cited as a source, mentioned in the answer text, or absent — plus the top sources the AI did cite.

Cost: $1.00 per scan (refunded on failure). Latency ~30–120s.

| Argument | Type | Required | Description | |---|---|---|---| | url | string | yes | Product URL to scan | | productContext | object | no | Pre-extracted product context (skip extraction step) |

Returns: visibility score + per-query results in content, full structured data in structuredContent.queries.

Example prompt:

Run jackpotkeywords_aeo_scan on https://markitup.app and tell me which queries we're missing from.

Environment variables

| Var | Required | Description | |---|---|---| | JACKPOTKEYWORDS_API_KEY | yes | API key from https://jackpotkeywords.web.app/developers | | JACKPOTKEYWORDS_API_BASE | no | Override the API base URL. Default: https://jackpotkeywords.web.app/api/v1. Useful for testing against staging. |

Pricing reference

• $2 starter credit on signup (no card, no expiration)
• /v1/recommend — $0.10/call
• /v1/recommend-deep — $0.30/call (adds clusters + categories + competitors)
• /v1/audit — $0.50/audit (SEO only; pair with /v1/aeo-scan for AI-visibility)
• /v1/aeo-scan — $1.00/scan
• Topup via Stripe checkout (POST /v1/topup) in $5 / $25 / $100 / $500 packs or custom ≥ $5
• Rate limit: 60 requests/min, 1000/hr per key

Local development

git clone https://github.com/smythmyke/jackpotkeywords-mcp-server.git
cd jackpotkeywords-mcp-server
npm install
npm run build

# Point your MCP client config at the local build:
{
  "command": "node",
  "args": ["/absolute/path/to/jackpotkeywords-mcp-server/dist/index.js"],
  "env": { "JACKPOTKEYWORDS_API_KEY": "jk_live_..." }
}

Security

• Never commit JACKPOTKEYWORDS_API_KEY to source control.
• If you accidentally expose a key, revoke it at https://jackpotkeywords.web.app/developers and create a new one (POST /v1/keys + DELETE /v1/keys/:keyId).
• Keys are SHA-256 hashed on the server; the raw key is shown only once at creation.

Errors

The server surfaces clean human-readable errors for the common cases:

• Invalid or missing JACKPOTKEYWORDS_API_KEY — set or rotate the key.
• Insufficient balance — top up at https://jackpotkeywords.web.app/developers.
• Rate limit exceeded — wait briefly and retry.

License

MIT