Ai-powered local event finder with multi-tool search

Summary This n8n workflow implements an AI-powered "Local Event Finder" agent. It takes user criteria (like event type, city, date, and interests), uses a suite of search tools (Brave Web Search, Brave Local Search, Google Gemini Search) and a web scraper (Jina AI) to find relevant events, and returns formatted details. The entire agent is exposed as a single, easy-to-use MCP (Multi-Capability Peer) tool, making it simple to integrate into other workflows or applications. This template cleverly combines the MCP server endpoint and the AI agent logic into a single n8n workflow file for ease of import and management. Key Features Intelligent Multi-Tool Search: Dynamically utilizes web search, precise local search, and advanced Gemini semantic search to find events. Detailed Information via Web Scraping: Employs Jina AI to extract comprehensive details directly from event web pages. Simplified MCP Tool Exposure: Makes the complex event-finding logic available as a single, callable tool for other MCP-compatible clients (e.g., Roo Code, Cline, other n8n workflows). Customizable AI Behavior: The core AI agent's behavior, tool usage strategy, and output formatting can be tailored by modifying its System Prompt. Modular Design: Uses distinct nodes for LLM, memory, and each external tool, allowing for easier modification or extension. Benefits Simplifies Client-Side Integration: Offloads the complexity of event searching and data extraction from client applications. Provides Richer Event Data: Goes beyond simple search links to extract and format key event details. Flexible & Adaptable: Can be adjusted to various event search needs and can incorporate new tools or data sources. Efficient Processing: Leverages specialized tools for different aspects of the search process. Nodes Used MCP Trigger Tool Workflow Execute Workflow Trigger AI Agent Google Gemini Chat Model (ChatGoogleGenerativeAI) Simple Memory (Window Buffer Memory) MCP Client (for Brave Search tools via Smithery) Google Gemini Search Tool Jina AI Tool Prerequisites An active n8n instance. Google AI API Key: For the Gemini LLM (Google Gemini Chat Model node) and the Google Gemini Search Tool. Ensure your key is enabled for these services. Jina AI API Key: For the jinaaiwebpagescraper node. A free tier is often available. Access to a Brave Search MCP Provider (Optional but Recommended): This template uses MCP Client nodes configured for Brave Search via a provider like Smithery. You'll need an account/API key for your chosen Brave Search MCP provider to configure the smithery brave search credential. Alternatively, you could adapt these to call Brave Search API directly if you manage your own access, or replace them with other search tools. Setup Instructions 1. Import Workflow: Download the JSON file for this template and import it into your n8n instance. 2. Configure Credentials: Google Gemini LLM: Locate the Google Gemini Chat Model node. Select or create a "Google Gemini API" credential (named Google Gemini Context7 in the template) using your Google AI API Key. Google Gemini Search Tool: Locate the googlegeminieventsearch node. Select or create a "Gemini API" credential (named Gemini Credentials account in the template) using your Google AI API Key (ensure it's enabled for Search/Vertex AI). Jina AI Web Scraper: Locate the jinaaiwebpagescraper node. Select or create a "Jina AI API" credential (named Jina AI account in the template) using your Jina AI API Key. Brave Search (via MCP): You'll need an MCP Client HTTP API credential to connect to your Brave Search MCP provider (e.g., Smithery). Create a new "MCP Client HTTP API" credential in n8n. Name it, for example, smithery brave search. Configure it with the Base URL and any required authentication (e.g., API key in headers) for your Brave Search MCP provider. Locate the bravewebsearch and bravelocalsearch MCP Client nodes in the workflow. Assign the smithery brave search (or your named credential) to both of these nodes. 3. Activate Workflow: Ensure the workflow is active. 4. Note MCP Trigger Path: Locate the localeventfinder (MCP Trigger) node. The Path field (e.g., 0ca88864-ec0a-4c27-a7ec-e28c5a900697) combined with your n8n webhook base URL forms the endpoint for client calls. Example Endpoint: YOURN8NINSTANCEURL/webhooks/PATH-TO-MCP-SERVER Customization AI Behavior: Modify the "System Message" parameter within the eventfinderagent node to change the AI's persona, its strategy for using tools, or the desired output format. LLM Model: Swap the Google Gemini Chat Model node with another compatible LLM node (e.g., OpenAI Chat Model) if desired. You'll need to adjust credentials and potentially the system prompt. Tools: Add, remove, or replace tool nodes (e.g., use a different search provider, add a weather API tool) and update the eventfinderagent's system prompt and tool configuration accordingly. Scraping Depth: Be mindful of the jinaaiwebpagescraper's usage due to potential timeouts. The system prompt already guides the LLM on this, but you can adjust its usage instructions.