Skip to main content
Glama
uzaysozen

imdb-mcp-server

get_most_popular_movies

Retrieve popular movies from IMDb with pagination. Specify a starting index to get 5 movies in JSON format.

Instructions

Get the most popular movies from IMDb with pagination. Args: start: The starting index (0-based) to retrieve movies from. Returns: JSON object containing 5 most popular movies starting from the specified index.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
startYes

Implementation Reference

  • The core handler function decorated with @mcp.tool() that fetches most popular movies from IMDb API endpoint, handles errors, paginates results, and returns JSON.
    @mcp.tool()
    async def get_most_popular_movies(start: int, ctx: Context) -> str:
        """Get the most popular movies from IMDb with pagination.
        Args:
            start: The starting index (0-based) to retrieve movies from.
        Returns:
            JSON object containing 5 most popular movies starting from the specified index.
        """
        most_popular_movies_url = f"{BASE_URL}/most-popular-movies"
        most_popular_movies_data = await make_imdb_request(most_popular_movies_url, {}, ctx) 
        if not most_popular_movies_data:
            return "Unable to fetch most popular movies data."
        return json.dumps(paginated_response(most_popular_movies_data, start, len(most_popular_movies_data)), indent=4)
  • Helper utility function used by the tool to format the API response into a standard paginated JSON structure with page size 5.
    def paginated_response(items, start, total_count=None):
        """Format a paginated response with a fixed page size of 5."""
        if total_count is None:
            total_count = len(items)
        
        # Validate starting index
        start = max(0, min(total_count - 1 if total_count > 0 else 0, start))
        
        # Fixed page size of 5
        page_size = 5
        end = min(start + page_size, total_count)
        
        return {
            "items": items[start:end],
            "start": start,
            "count": end - start,
            "totalCount": total_count,
            "hasMore": end < total_count,
            "nextStart": end if end < total_count else None
        }
  • Core helper function that makes HTTP requests to the IMDb RapidAPI, handles caching, API key management, and errors.
    async def make_imdb_request(url: str, querystring: dict[str, Any], ctx: Optional[Context] = None) -> Optional[Dict[str, Any]]:
        """Make a request to the IMDb API with proper error handling and caching."""
        
        # Check if it's time to clean the cache
        cache_manager.cleanup_if_needed()
        
        # Create a cache key from the URL and querystring
        cache_key = f"{url}_{str(querystring)}"
        
        # Try to get from cache first
        cached_data = cache_manager.cache.get(cache_key)
        if cached_data:
            return cached_data
        
        # Get API key from session config or fallback to environment variable
        api_key = None
        if ctx and hasattr(ctx, 'session_config') and ctx.session_config:
            api_key = ctx.session_config.rapidApiKeyImdb
        
        if not api_key:
            api_key = os.getenv("RAPID_API_KEY_IMDB")
        
        # Not in cache, make the request
        headers = {
            "x-rapidapi-key": api_key,
            "x-rapidapi-host": "imdb236.p.rapidapi.com",
        }
        
        if not api_key:
            raise ValueError("API key not found. Please set the RAPID_API_KEY_IMDB environment variable or provide rapidApiKeyImdb in the request.")
        
        try:
            response = requests.get(url, headers=headers, params=querystring, timeout=30.0)
            response.raise_for_status()
            data = response.json()
            
            # Cache the response
            cache_manager.cache.set(cache_key, data)
                
            return data
        except Exception as e:
            raise ValueError(f"Unable to fetch data from IMDb. Please try again later. Error: {e}")
  • Server creation and tool registration via register_tools(server), which defines and registers the get_most_popular_movies handler among others.
    # Create your FastMCP server as usual
    server = FastMCP("IMDb MCP Server")
    
    # Register all tools with the server
    register_tools(server)
    
    return server
  • Pydantic schema for server configuration, providing the required rapidApiKeyImdb for API requests.
    class ConfigSchema(BaseModel):
        rapidApiKeyImdb: str = Field(..., description="RapidAPI API key for accessing the IMDb API")

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/uzaysozen/imdb-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server