product-hunt-mcp

""" Topic-related tools for the Product Hunt MCP server. """ import logging from typing import Any, Dict from product_hunt_mcp.api.client import execute_graphql_query from product_hunt_mcp.api.queries import TOPIC_QUERY, TOPICS_QUERY from product_hunt_mcp.schemas.validation import TOPIC_SCHEMA, TOPICS_SCHEMA from product_hunt_mcp.utils.common import ( add_id_or_slug, apply_pagination_defaults, execute_and_check_query, extract_pagination, format_response, handle_errors, require_token, ) from product_hunt_mcp.utils.validation import validate_with_schema logger = logging.getLogger("ph_mcp") def register_topic_tools(mcp): """Register topic-related tools with the MCP server.""" @mcp.tool() @require_token @handle_errors @validate_with_schema(TOPIC_SCHEMA) def get_topic(id: str = None, slug: str = None) -> Dict[str, Any]: """ Retrieve detailed information about a specific topic by ID or slug. Parameters: - id (str, optional): The topic's unique ID. - slug (str, optional): The topic's slug (e.g., "artificial-intelligence"). At least one of `id` or `slug` must be provided. Returns: - success (bool) - data (dict): If successful, contains topic details: - id, name, description, follower_count, posts, etc. - error (dict, optional) - rate_limits (dict) Notes: - Returns an error if neither `id` nor `slug` is provided, or if the topic is not found. """ params = {k: v for k, v in {"id": id, "slug": slug}.items() if v is not None} logger.info("topics.get_topic called", extra=params) variables = {} add_id_or_slug(variables, id, slug) # Execute the query and check if topic exists id_or_slug = id or slug topic_data, rate_limits, error = execute_and_check_query( TOPIC_QUERY, variables, "topic", id_or_slug ) if error: return format_response(False, error=error, rate_limits=rate_limits) return format_response(True, data=topic_data, rate_limits=rate_limits) @mcp.tool() @require_token @handle_errors @validate_with_schema(TOPICS_SCHEMA) def search_topics( query: str = None, followed_by_user_id: str = None, order: str = "FOLLOWERS_COUNT", count: int = 10, after: str = None, ) -> Dict[str, Any]: """ Search for topics by name or filter by user following, with optional sorting and pagination. Parameters: - query (str, optional): Search term to find topics by name. - followed_by_user_id (str, optional): Only topics followed by this user ID. - order (str, optional): Sorting order. Valid values: FOLLOWERS_COUNT (default), NAME, NEWEST. - count (int, optional): Number of topics to return (default: 10, max: 20). - after (str, optional): Pagination cursor for next page. Returns: - success (bool) - data (dict): If successful, contains: - topics (list): List of topic objects (id, name, etc.) - pagination (dict): { end_cursor, has_next_page } - error (dict, optional) - rate_limits (dict) Notes: - If no topics match, `topics` will be an empty list. """ params = { k: v for k, v in { "query": query, "followed_by_user_id": followed_by_user_id, "order": order, "count": count, "after": after, }.items() if v is not None } logger.info("topics.search_topics called", extra=params) # Apply pagination defaults variables = apply_pagination_defaults(count, after) # Add order parameter variables["order"] = order # Add optional filters if query: variables["query"] = query if followed_by_user_id: variables["followedByUserId"] = followed_by_user_id result, rate_limits, error = execute_graphql_query(TOPICS_QUERY, variables) if error: return format_response(False, error=error, rate_limits=rate_limits) # Extract topics topics_data = result["data"]["topics"] return format_response( True, data={ "topics": topics_data["edges"], "pagination": extract_pagination(topics_data["pageInfo"]), }, rate_limits=rate_limits, )