I built an AI agent that searches the entire Cursor community forum (http://forum.cursor.com/) and answers questions grounded in real forum discussions.
The problem: Cursor's forum has tons of valuable content - feature discussions, troubleshooting threads, tips from power users - but it's hard to search. Traditional forum search is keyword-based and misses a lot of context.
The solution: I indexed the entire forum using Nia (a knowledge indexing service) and connected it to an AI agent with multiple search tools:
- Semantic search - finds relevant posts even when wording differs
- Pattern search (grep) - exact matching for error messages, usernames, specific terms
- Full thread reading - AI can dive deep into specific discussions
- Web search fallback - for questions the forum doesn't cover
The problem: Cursor's forum has tons of valuable content - feature discussions, troubleshooting threads, tips from power users - but it's hard to search. Traditional forum search is keyword-based and misses a lot of context.
The solution: I indexed the entire forum using Nia (a knowledge indexing service) and connected it to an AI agent with multiple search tools:
- Semantic search - finds relevant posts even when wording differs - Pattern search (grep) - exact matching for error messages, usernames, specific terms - Full thread reading - AI can dive deep into specific discussions - Web search fallback - for questions the forum doesn't cover
GitHub: https://github.com/nozomio-labs/nia-cursor-forum-search
Would love feedback on the approach!