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jackpotkeywords-mcp-server

npm version MCP Registry Glama License: MIT

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).

Related MCP server: AI Patent Search

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:

License

MIT

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A
license - permissive license
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quality
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Maintenance

Maintainers
Response time
1dRelease cycle
2Releases (12mo)
Commit activity

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