nikhil-sprintly is a personal AI-powered productivity and knowledge management system designed to manage tasks, sprints, learning notes, AI tools, saved links, dashboard summaries, morning digests, and evening reminders through Telegram.
Friction across disconnected tools
Traditional task management requires manual updates across many tools. The project solves:
Lack of unified system for tasks, sprints, notes, learnings, and AI tools
Manual effort in tracking overdue and due-today tasks
No conversational productivity interface
No automated morning or evening planning assistant
Limited visibility into personal project progress
Three engineered layers
Frontend & Backend Portal
Built with Lovable and Supabase to manage epics, stories, tasks, sprints, notes, learnings, AI tools, saved links, dashboard data, and user settings.
MCP Tool Layer
n8n exposes portal APIs as MCP tools so agents consume a standardized interface instead of calling individual APIs directly.
Agent & Automation Layer
Telegram assistant enables real-time interaction, while Microsoft AI Foundry agents generate morning digests and evening reminders.
How requests flow
Interactive (Telegram)
Scheduled Agents
What the agent can do
Add tasks through natural language
Retrieve tasks due today
List overdue tasks
Mark tasks as completed
Update story status
View current sprint progress
Save AI tools
Save notes
Save learnings
Save links
Generate dashboard summaries
Send morning digest
Send evening reminders
Standardized agent tool interface
task_addtask_mark_donetask_get_due_todaytask_get_overduesprint_get_currentstory_update_statusdashboard_get_summaryknowledge_add_ai_toolknowledge_add_noteknowledge_add_learningknowledge_add_linkmorning_digest_get_datamorning_digest_log_deliveryAutomated daily planning
morning_digest_get_datatask_get_overduetask_get_due_todayMorning Digest includes
- Good morning message
- Overdue tasks
- Tasks due today
- Latest news from topics of interest
- Suggested focus for the day
Automated evening review
The applied AI stack
Agentic AI
AI agents reason over requests, select tools, call APIs, and return structured responses.
MCP-Based Tool Calling
MCP standardizes backend capability access and improves tool reuse, maintainability, scalability, and separation of concerns.
AI Orchestration
n8n coordinates Telegram, Microsoft AI Foundry, MCP tools, Lovable APIs, and Supabase.
Prompt Engineering
Prompts control routing, morning digest generation, evening reminders, tool usage, safety, and output formatting.
Web Search Grounding
Morning digest uses web search for current topic updates.
Human-in-the-Loop Design
Ambiguous state-changing actions ask clarification before execution.
API-First AI Integration
Backend APIs are designed for agent consumption.
Secure by design
API key validation using x-api-key
Telegram user mapping before data access
No direct database access from AI agents
MCP tools call secured backend APIs only
Sensitive details not exposed
Agent tool usage logged
Measurable outcomes
Reduced manual effort in task tracking
Improved visibility of overdue and due-today work
Created daily planning habit through morning digest
Created evening review habit through reminders
Centralized learning, links, notes, and AI tools
Demonstrated practical MCP and Agentic AI implementation
Proved how agents can interact with structured systems through secure APIs