Fictional Cats MCP Documentation

Overview

The Fictional Cats MCP (Model Context Protocol) provides AI models with the ability to access and retrieve fictional cat data. This MCP allows models to either get a random cat or retrieve a specified number of cats from the Fictional Cats API.

Installation

To use this MCP in your application, you'll need to integrate it with an MCP-compatible client. The MCP is defined in a JSON file that follows the Model Context Protocol specification.

Features

This MCP provides two main functions:

1. get_random_cat: Retrieves a single random cat

2. get_cats: Retrieves a specified number of cats

Usage Examples

Using get_random_cat

This function retrieves a single random cat from the database. It doesn't require any parameters.

// Example client code
const result = await client.call('get_random_cat');
console.log(result);

Example response:

{
  "uuid": "f60dd86b-6061-448a-9a25-16774f5acdea",
  "name": "Zoey",
  "description": "A sock thief with a hidden collection under the bed. Enjoys playing with toys. Fur is fluffy and siamese.",
  "image": "https://i.ibb.co/PZFbJ7J2/5.png",
  "date_created": "2024-10-11T23:52:07+00:00"
}

Using get_cats

This function retrieves multiple cats from the database. It requires a parameter n to specify how many cats to retrieve.

// Example client code
const result = await client.call('get_cats', { n: 3 });
console.log(result);

Example response:

[
  {
    "uuid": "835a97e8-0238-4705-81a0-ef5cb8edb88f",
    "name": "Winston",
    "description": "A social butterfly who greets all visitors with a friendly meow. Enjoys watching birds. Fur is smooth and tabby.",
    "image": "https://i.ibb.co/4n13WPTM/10.png",
    "date_created": "2024-10-19T23:52:07+00:00"
  },
  {
    "uuid": "c4b781d0-1e52-47dd-b72e-bbf9b5220147",
    "name": "Whiskers",
    "description": "A vertical explorer who scales the tallest furniture. Has gentle gold eyes. Enjoys napping in sunbeams.",
    "image": "https://i.ibb.co/Z12FSs1g/1.png",
    "date_created": "2024-09-17T23:52:07+00:00"
  },
  {
    "uuid": "fde8f5af-90f8-4f23-8c14-60cc5d7b5a9a",
    "name": "Winston",
    "description": "A vocal feline who talks all day long about everything and nothing. Enjoys watching birds. Personality is friendly.",
    "image": "https://i.ibb.co/Z12FSs1g/1.png",
    "date_created": "2024-05-24T23:52:07+00:00"
  }
]

Function Reference

get_random_cat

Retrieves a random cat from the Fictional Cats API.

Parameters: None

Returns: A cat object with the following properties:

• uuid (string): Unique identifier for the cat

• name (string): The cat's name

• description (string): Text description of the cat's characteristics and personality

• image (string): URL to the cat's image

• date_created (string): Timestamp when the cat was created in ISO 8601 format

get_cats

Retrieves a specified number of cats from the Fictional Cats API.

Parameters:

• n (integer, required): The number of cats to retrieve

Returns: An array of cat objects, each with the following properties:

• uuid (string): Unique identifier for the cat

• name (string): The cat's name

• description (string): Text description of the cat's characteristics and personality

• image (string): URL to the cat's image

• date_created (string): Timestamp when the cat was created in ISO 8601 format

Error Handling

The MCP handles the following error scenarios:

1. API Connection Errors: If the Fictional Cats API is unavailable, the MCP will return an appropriate error message.

2. Invalid Parameters: If invalid parameters are provided (e.g., a negative number for n), the MCP will return an error.

Implementation Details

This MCP is implemented as a JSON file following the Model Context Protocol specification. It defines the server information, tool definitions, and API endpoint configurations.

The MCP connects to the Fictional Cats API at:

• Base URL: https://fictionalcats.netlify.app/.netlify/functions/api

• Random cat endpoint: /cats/random

• Multiple cats endpoint: /cats?n={n}

Publishing

This MCP can be published to MCP registries like smithery.ai to make it available to AI models and applications that support the Model Context Protocol.