Asana and HTTP Request integration

📊 Description Automate short-term trading research by generating high-quality trade ideas using MCP (Market Context Protocol) signals and AI-powered analysis. 📈🤖 This workflow evaluates market context, catalysts, momentum, and risk factors to produce structured trade ideas with clear reasoning, confidence scores, and execution notes. Designed for fast-moving markets, it helps traders and analysts spot actionable opportunities consistently—without manual screening or emotional bias. Perfect for systematic traders, research teams, and AI-driven trading desks. ⚡📊 🔁 What This Template Does 1️⃣ Ingests market context and asset data from MCP inputs. 📥 2️⃣ Normalizes symbols, sectors, and time horizons for analysis. 🧾 3️⃣ Evaluates short-term momentum and catalyst strength. 🚀 4️⃣ Analyzes risk, volatility, and downside exposure. ⚠️ 5️⃣ Uses AI to generate a structured trade thesis. 🤖 6️⃣ Assigns a confidence score and risk level to each idea. 📊 7️⃣ Produces clear entry logic, rationale, and trade direction. 🧠 8️⃣ Filters out low-quality or low-conviction setups. 🚫 9️⃣ Outputs clean JSON-ready trade ideas for downstream systems. 🔁 ⭐ Key Benefits ✅ Automates short-term trade idea generation ✅ Reduces emotional bias with AI-based scoring ✅ Combines market context, catalysts, and momentum ✅ Produces structured, repeatable trade logic ✅ Saves hours of manual chart and news analysis ✅ Ideal for fast-paced trading environments 🧩 Features MCP (Market Context Protocol) data ingestion AI-powered trade thesis generation Confidence and risk scoring logic Short-term momentum and catalyst analysis Strict structured output for automation reliability Easy integration into dashboards or execution systems 🔐 Requirements MCP-compatible market data source OpenAI API credentials (GPT-4o or GPT-4o-mini recommended) n8n instance with AI nodes enabled Defined schema for trade idea output 🎯 Target Audience Short-term and swing traders Quant and discretionary trading teams Market research analysts Fintech platforms generating trade signals Automation engineers building trading workflows

What is This? This automation simulates Scrum Master role on daily meetings. Essentially it is an AI Scrum Master using different sources of data. As intelligent support system for Scrum Masters that leverages data from Asana, Slack, and direct developer responses for comprehensive sprint status analysis and identification of areas requiring intervention. As such it is usable for Scrum Masters (of course) but Scrum Team aswell, Product Owner and possibly Business Owner. Who is it For? This automation is designed for Agile teams to support the Scrum Master role by collecting and analyzing data from various sources to identify potential impediments and support the team in sprint delivery. How Does It Work? The workflow has four main data entry points, that are launched either on-click or on workdays. First is collecting project section information from Asana. The automation retrieves project structure, available sections, and their organization, allowing the AI to understand the team's work context. Second is getting recently modified tasks in the Asana project. The system tracks changes in tasks, their status, assignments, and updates to detect potential delays or issues. Third is obtaining communication in the team's Slack channel. The flow collects data about recent conversations, discussion threads, and team communication to identify warning signals or areas requiring attention. Fourth is directly collecting responses from developers about the current sprint - their progress, impediments, concerns, and support needs. All collected data is passed to an AI model that analyzes it within the Scrum methodology context and identifies: Potential impediments in sprint delivery Areas requiring Scrum Master intervention Recommendations for team support Warning signals regarding Sprint Goal achievement Output is being pushed to Slack channel so it can be potentially used by another iteration of same flow itself via Slack channel history. Requirements You need Asana oAuth credentials You need OpenAI / alternative AI for processing data You need to have Slack app with proper permissions channels:history chat:write groups:history im:history mpim:history users.profile:write users:write Configuration Set up node "Asana Project and Slack Channel". Provide Asana project ID and Slack Channel ID (optional) Set up node "Get Scrum Master Answers". There are daily questions/answers that are being sent to channel. Alternative use You can get rid of the whole "Ask Users Daily ScrumMaster Questions" part if you don't want to do it simirarly as "daily Scrum standups". In such case whole flow is essentially changed to static analyzer of project status based on Slack and Asana. Extensions and Customizations There are many possibilities to extend this automation depending on team needs. For example, you can add integration with additional project management tools, implement different notification schemes based on detected issue criticality, or adjust data collection frequency to match the team's work rhythm. Disclaimers and Notes Whole automation has one important assumption: project is run on single Slack channel and on single Asana board. Of cource this can be extended, but is beyond currently designed scope. Adding new sources for AI to analyze should be fairly easy - just add another branch of data and push it to AI prompt. This automation represents a proof-of-concept and should not replace an actual Scrum Master. The Scrum Master role extends far beyond data collection and analysis - it requires deep understanding of team dynamics, business context, and interpersonal skills. As Scrum.org emphasizes, the Scrum Master doesn't need to be present during Daily Scrum, and their role is to ensure the meeting happens, but developers are responsible for conducting the meeting. Mindlessly executing daily questions without proper context analysis can lead to situations where the Scrum Master becomes a team manager instead of a self-organization facilitator. A real Scrum Master analyzes much more data than what's collected by automation - they observe team dynamics, understand business context, identify deeper root causes of problems, and support the team in developing self-organization skills. AI can be a valuable support tool, but it cannot replace the human intuition, empathy, and experience essential in this role. The automation should be treated as a tool supporting the Teams's work, providing additional insights and helping identify areas requiring attention, but always under the supervision and interpretation of an experienced Scrum practitioner.

📊 Description Automate your inbound lead qualification pipeline by enriching raw lead data, scoring it with AI, and instantly creating follow-up tasks for your sales team. 🎯🤖 This workflow receives new leads via webhook, enriches them using RocketReach to fetch verified emails and contact details, applies confidence-based filtering, and uses GPT-4o-mini to score each lead based on seniority, company fit, and data quality. High-quality leads automatically generate Asana tasks and Slack notifications, while low-quality leads are safely filtered out — ensuring your team focuses only on the best opportunities. 🚀📋 🔁 What This Template Does 1️⃣ Receives inbound lead data via webhook (name, company, job title, LinkedIn URL). 🌐 2️⃣ Normalizes incoming data into a clean, structured format. 🧾 3️⃣ Enriches lead profiles using RocketReach to fetch emails and phone numbers. 📇 4️⃣ Calculates email confidence scores based on quality grades (A–D). 📊 5️⃣ Filters out low-confidence leads automatically. 🚫 6️⃣ Uses AI (GPT-4o-mini) to score qualified leads from 1–10. 🤖 7️⃣ Assigns priority levels (High / Medium / Low) with reasoning. 🧠 8️⃣ Creates an Asana task for leads scoring above the threshold. ✅ 9️⃣ Sends Slack notifications for both qualified and disqualified leads. 💬 🔟 Returns a structured webhook response with scoring results. 🔁 1️⃣1️⃣ Sends Gmail alerts automatically if any workflow error occurs. 🚨 ⭐ Key Benefits ✅ Eliminates manual lead enrichment and qualification ✅ Uses verified contact data from RocketReach ✅ AI scoring ensures consistent, unbiased lead evaluation ✅ Automatically routes high-quality leads to sales via Asana ✅ Keeps teams informed with real-time Slack notifications ✅ Prevents sales effort from being wasted on low-quality leads 🧩 Features Webhook-based inbound lead intake RocketReach profile enrichment Email confidence scoring logic AI lead scoring with strict JSON output Configurable quality and score thresholds Automatic Asana task creation Slack alerts for qualified and disqualified leads Gmail-based error handling Frontend-ready webhook responses 🔐 Requirements RocketReach API key OpenAI API key (GPT-4o-mini recommended) Asana OAuth2 credentials Slack API credentials Gmail OAuth2 credentials (for error alerts) Webhook client sending lead details (first_name, last_name, company, job_title, linkedin_url) 🎯 Target Audience B2B sales teams handling inbound leads Revenue operations (RevOps) teams SaaS companies optimizing lead qualification Lead generation agencies Automation teams building AI-driven sales pipelines

📊 Description Streamline and standardize your entire client onboarding process with a single end-to-end automation. 🚀📋 This workflow captures detailed client intake data via webhook, automatically creates a fully structured Asana onboarding project, generates a personalized service contract from a Google Docs template, emails the agreement to the client, and logs all information in Google Sheets. It also creates a dedicated Slack channel for internal collaboration, ensuring every new client is onboarded consistently, professionally, and without manual effort. Perfect for service businesses scaling operations while maintaining quality and clarity. ✨📄🤝 🔁 What This Template Does 1️⃣ Receives detailed client intake form data via webhook. 📥 2️⃣ Parses and normalizes 70+ client, business, and technical fields. 🧾 3️⃣ Creates a new client-specific onboarding project in Asana. 📋 4️⃣ Copies sections and tasks from a predefined Asana template project. 🔄 5️⃣ Assigns all tasks into the new project with proper structure. ✅ 6️⃣ Retrieves a Google Docs contract template. 📄 7️⃣ Replaces placeholders with client-specific details (name, fees, dates). ✍️ 8️⃣ Downloads the personalized contract as a PDF. 📑 9️⃣ Sends a welcome email to the client with the contract attached. 📧 🔟 Resets the contract template for the next onboarding. 🔁 1️⃣1️⃣ Logs all client data into Google Sheets for tracking and reporting. 📊 1️⃣2️⃣ Creates a dedicated Slack channel for internal client communication. 💬 ⭐ Key Benefits ✅ Eliminates manual onboarding setup and repetitive admin work ✅ Ensures consistent project structure for every client ✅ Generates error-free, personalized contracts automatically ✅ Improves client experience with instant, professional communication ✅ Centralizes client data for operations and reporting ✅ Scales onboarding without adding operational overhead 🧩 Features Webhook-based client intake form processing Advanced data parsing for large intake payloads Asana project creation with template-based sections and tasks Google Docs dynamic contract generation Automated PDF download and email delivery Google Sheets client tracking with append/update logic Automatic Slack channel creation for internal teams Clean reset logic for reusable document templates 🔐 Requirements Asana OAuth2 credentials Google Docs OAuth2 credentials Google Drive OAuth2 credentials Google Sheets OAuth2 credentials Gmail OAuth2 credentials Slack API credentials Asana template project ID Google Docs contract template ID Google Sheets tracking document ID 🎯 Target Audience Service-based businesses onboarding new clients Agencies managing multi-step client engagements Operations and delivery teams SaaS or healthcare service providers with complex intake forms Automation teams building scalable onboarding systems

How It Works Automates sales data analysis and strategic insight generation for sales managers and strategists needing actionable intelligence. Fetches multi-source data from sales, marketing, and financial systems, validates data quality to prevent errors, applies advanced AI analysis via OpenAI to identify market trends and patterns, calculates comprehensive KPIs for performance measurement, generates prioritized recommendations, and automatically distributes detailed insights via Gmail alerts and Google Sheets dashboards—eliminating time-consuming manual analysis overhead. Setup Instructions OpenAI API: Add key via credentials Gmail: Authorize account for email delivery Google Sheets: Connect for dashboard logging Schedule: Set monthly trigger timing Modify data sources: Replace fetch nodes with your APIs Prerequisites OpenAI API key, Gmail account with send permissions, Google Sheets access, n8n instance, source data APIs (sales, marketing, financial systems). Use Cases E-commerce platforms analyzing sales trends; SaaS companies generating strategy reports; multi-channel retailers routing recommendations; Customization Add data sources via fetch nodes; swap OpenAI for Claude or Gemini; modify routing logic for different priority thresholds; Benefits Reduces analysis time from hours to minutes. Eliminates manual report crea