About pagerankcafe
pagerankcafe-mcp connects AI agents to the PageRankCafe marketing API. It supports reading campaign and account performance data, while paid memberships unlock tools for creating and posting ads and articles.
Key features
- 01List link, banner, and YouTube ads
- 02Read press releases and placement performance
- 03Check credits and referral statistics
- 04Create and post ads and articles
- 05Retrieve platform-wide ad insights
Use cases
- 01Review active ad campaigns
- 02Check per-placement campaign performance
- 03Publish a link or banner ad
- 04Compare platform ad performance
MCP support
The MCP server exposes PageRankCafe API operations as tools for AI agents, including campaign reads, account statistics, and paid-tier writing and insights operations. It requires an API key configured through `PAGERANKCAFE_API_KEY`.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
npx -y pagerankcafe-mcpPAGERANKCAFE_API_KEYSecretYour PageRankCafe API key, generated at https://pagerankcafe.com/apiKeys after creating an account at https://pagerankcafe.com.PAGERANKCAFE_BASE_URLAPI base URL. Override only for testing against a non-production environment.Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.
Tools
19Saved tool list · updated 2w ago
This tool takes no parameters.
Details
From the project READMEpagerankcafe-mcp
The marketing platform for your AI agents.
An MCP (Model Context Protocol) server for the PageRankCafe API. It gives an AI agent tools to read and post link ads, banner ads, YouTube video ads, and press releases/blog articles on PageRankCafe, check credit and referral balances, read per-placement performance, and (on paid tiers) pull platform-wide ad performance insights.
Getting a key
- Create a PageRankCafe account at https://pagerankcafe.com.
- Upgrade to a paid membership (Bronze/Silver/Gold) at https://pagerankcafe.com/membership-info if you want to use the write and insights tools. Read tools work on a free account too.
- Generate an API key at https://pagerankcafe.com/apiKeys.
Account creation and key generation are both manual, human steps on the website — there is no programmatic signup.
Configuration
The server reads its configuration from environment variables:
| Variable | Required | Default | Description |
|---|---|---|---|
PAGERANKCAFE_API_KEY | Yes | — | Your API key from /apiKeys. The server exits immediately with an error if this is not set. |
PAGERANKCAFE_BASE_URL | No | https://pagerankcafe.com | API base URL. Override only for testing against a non-production environment. |
Install
Claude Desktop
Add to your claude_desktop_config.json:
{
"mcpServers": {
"pagerankcafe": {
"command": "npx",
"args": ["-y", "pagerankcafe-mcp"],
"env": {
"PAGERANKCAFE_API_KEY": "your-api-key-here"
}
}
}
}
Claude Code
claude mcp add pagerankcafe --env PAGERANKCAFE_API_KEY=your-api-key-here -- npx -y pagerankcafe-mcp
Cursor
Add to your Cursor MCP settings (~/.cursor/mcp.json or the project's .cursor/mcp.json):
{
"mcpServers": {
"pagerankcafe": {
"command": "npx",
"args": ["-y", "pagerankcafe-mcp"],
"env": {
"PAGERANKCAFE_API_KEY": "your-api-key-here"
}
}
}
}
Tools
Every write tool and the insights tool require a paid membership (Bronze/Silver/Gold); the API returns an error for free accounts. Read tools work on any valid key, including free accounts.
| Tool | Membership | Description |
|---|---|---|
health | Free | Checks API connectivity and returns the authenticated user's username and membership status. |
list_links | Free | Lists your active link ads. |
list_banners | Free | Lists your active banner ads. |
list_youtube_ads | Free | Lists your active YouTube video ads. |
list_press_releases | Free | Lists your active press releases / blog articles. |
get_credits | Free | Returns your credit balance, available post slots, links viewed, and links remaining. |
get_referral_stats | Free | Returns your referral counts (today, 7 day, 30 day, all time). |
list_posts | Free | Returns per-placement performance for link, banner, YouTube, or press-release ads. |
upload_image | Paid | Uploads an image (local file path or base64) and returns a hosted HTTPS URL. |
create_banner | Paid | Creates a new banner ad. |
post_banner | Paid | Posts an existing banner into rotation using credits. |
create_youtube_ad | Paid | Creates a new YouTube video ad. |
update_youtube_ad | Paid | Partially updates an existing YouTube ad you own. |
create_press_release | Paid | Creates a new press release / blog article. |
update_press_release | Paid | Partially updates an existing press release you own. |
post_press_release | Paid | Posts an existing press release to the home-page widget using credits. |
create_link | Paid | Creates a new link ad. |
post_link | Paid | Posts an existing link ad into rotation using credits (free/credit posts only: ad_days must be 0; view_time/view_credits are derived server-side from icon/bold/double_time, not accepted as input). Returns status: "active" when the post goes live immediately, or status: "pending" (with an explanatory message) when the posting user needs approval first. |
get_platform_insights | Paid | Trailing-30-day platform performance aggregates by ad type and option, plus current prices. |
Full request/response detail for each underlying endpoint is in the OpenAPI spec at https://pagerankcafe.com/api/spec (rendered at https://pagerankcafe.com/api/docs).
Error handling
Every tool returns the API's JSON response as the tool result on success. On a non-2xx API response, the tool returns an MCP tool error (isError: true) carrying the API's error message. There are no retries and no silent fallbacks — a failed call always surfaces as a failed tool call.
Development
npm install
npm run build # compiles src/ to dist/ with tsc
npm test # builds, then runs the stdio smoke test (no network required)
The test starts the built server as a subprocess over stdio (using StdioClientTransport from @modelcontextprotocol/sdk), lists its tools, and checks the full tool list is present — no real API key or network access is used.
Comments
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An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.