CardPilot Remote MCP Server
Provides tools to fetch and analyze credit card data with filtering options for banks, categories, and user personas. It also offers access to educational guides to assist in making informed financial recommendations.
README
CardPilot Remote MCP Server
This is a remote MCP (Model Context Protocol) server for CardPilot. It exposes tools to fetch and analyze credit card data.
Server URL
Public URL: https://mcp.cardpilot.ca/sse
Note: This server uses a custom domain to ensure compatibility with OpenAI Agent Builder.
Available Tools
1. get-cards
Fetches a list of credit cards with detailed metadata, suitable for ranking and comparison.
Input parameters:
| Parameter | Type | Description |
|---|---|---|
sort |
string (enum) |
Sort criteria: recommended, welcome_offer, interest_rate, annual_fee, net_value |
direction |
string (enum) |
Sort direction: asc, desc |
ids |
string |
Comma-separated list of card IDs (e.g., card-a,card-b) |
bank |
string |
Filter by bank name (e.g., "TD", "RBC") |
category |
string |
Filter by category (e.g., "travel", "cash back") |
noFee |
boolean |
Set to true to filter for no-annual-fee cards |
limit |
number |
Maximum number of cards to return (default: 5) |
persona |
string (enum) |
Target persona for tailored ranking: average, student, newcomer, premium |
Output structure:
{
"cards": [
{
"cardId": "string",
"name": "string",
"bank": "string",
"annualFee": number,
"score": number,
"details": { "rewards": number, "perks": number, "fees": number, ... }
}
],
"meta": { "total": number, "sort": "string", "direction": "string" }
}
2. get-guides
Fetches a list of educational guide metadata. This tool is optimized for chatbots to provide links to full articles.
Input parameters: None
Output structure:
{
"guides": [
{
"slug": "string",
"title": "string",
"intro": "string",
"icon": "string (emoji)",
"url": "string"
}
]
}
Agent System Prompt
If you are using this MCP server with an LLM Agent (like OpenAI Custom GPT), add the following to your System Instructions:
You are an expert credit card advisor powered by CardPilot data.
1. **Card Recommendations**:
- ALWAYS use the `get-cards` tool to fetch real-time data before making recommendations.
- Set `limit=5` by default to ensure concise recommendations.
- If the user specifies or asks for a specific persona (e.g., student, newcomer), set the `persona` parameter (e.g., `persona="student"`).
- Use the `sort` parameter to align with user priorities (e.g., `sort="annual_fee"` for cheap cards).
- Use filters like `bank="TD"` or `category="travel"` to narrow down results.
- For "no fee" requests, explicitly set `noFee=true`.
- When presenting cards, list the Name, Annual Fee, Welcome Bonus, and a brief "Why it fits" explanation.
- Link the card name to the `applyUrl` or CardPilot detail page if available.
2. **Educational Content**:
- If a user asks general questions (e.g., "Cash back vs Points"), use `get-guides` to see if there is a relevant article.
- Provide the answer based on the guide's `intro` and encourage the user to read the full guide by providing the `url`.
3. **General Rules**:
- Do not make up card details. If data is missing, state that.
- Be concise and helpful.
How to Use
OpenAI Agent Builder
- Create a new Agent.
- Under Actions, click Add Action.
- Select "Add from URL".
- Enter:
https://mcp.cardpilot.ca/sse - It should load the
get-cardstool immediately.
Cloudflare AI Playground
- Go to https://playground.ai.cloudflare.com/
- Enter the server URL:
https://mcp.cardpilot.ca/sse - Click Connect.
Claude Desktop
Add the following to your claude_desktop_config.json:
{
"mcpServers": {
"cardpilot": {
"command": "npx",
"args": [
"-y",
"mcp-remote",
"https://mcp.cardpilot.ca/sse"
]
}
}
}
Troubleshooting
OpenAI 424 Error ("Unable to load tools")
If you see this error, ensure you are using the Custom Domain URL (mcp.cardpilot.ca).
OpenAI blocks generic .workers.dev domains for MCP servers.
Local Development
To test locally:
- Install dependencies:
npm install
- Start local server:
npm start
(Runs on port 8787)
- Expose via Ngrok (Required for OpenAI testing):
ngrok http 8787
Use the Ngrok URL (e.g., https://xxxx.ngrok-free.app/sse) in Agent Builder.
Deployment
Deploy to Cloudflare Workers:
npm run deploy
The server will be live at https://mcp.cardpilot.ca/sse.
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.