Syntra.ai

Landing Page
dashboard-2
dashboard

Inspiration

Engineering teams waste massive time—standups, Slack threads, triaging help requests, and jumping between GitHub, Jira, and Linear. We wanted to eliminate that operational overhead and ask: what if a team could coordinate itself? The release of the MCP (Model Context Protocol) inspired us: finally, AI could act as an agentic brain for organizations, not just a chat assistant.

What it does

Syntra.ai is an autonomous coordination engine for engineering teams. It: Automatically collects async standups and AI-parses tasks/blockers Learns expertise from GitHub/Jira/Linear activity Routes help to the right expert instantly Detects blockers and incidents before humans notice Surfaces real-time team intelligence via a beautiful dashboard Result: ~3 hours saved per team per day + 40% faster problem resolution.

How we built it

We implemented an MCP-based Agentic Brain that syncs GitHub, Linear, Jira, and Slack data. The agent uses retrieval + skill inference to build a live expertise graph for the entire team. We built a help routing engine that performs semantic task/task matching to pick the right expert. Standups are collected through a Slack MCP client, parsed using structured LLM outputs. The dashboard (Python + lightweight frontend) visualizes blockers, dependencies, and work patterns in real time. The whole system runs fully containerized and deployed on DigitalOcean Gradient.

Challenges we ran into

Getting MCP agents to run continuously and maintain long-term context. Stitching together GitHub, Linear, and Slack data in a clean, unified structure. Building expertise detection without hallucinations required several iterations. Ensuring real-time responsiveness while controlling API rate limits. Making the standup parser robust to messy human language.

Accomplishments that we're proud of

Built a fully working autonomous team coordination agent in under 48 hours. Successfully reduced coordination noise—no more Slack chaos during the demo. Created a clean, manager-friendly dashboard that feels like a real product. Achieved accurate expertise detection from real GitHub repositories. Proved that MCP agents can meaningfully replace daily standup meetings.

What we learned

MCP unlocks agentic workflows that were previously impossible with traditional APIs. Expertise modeling + routing is extremely powerful for reducing team friction. Async communication is drastically more efficient when orchestrated by an intelligent agent. Good UX matters: dashboards influence trust in the AI.

What's next for Syntra.ai

Expand into advanced incident prediction using temporal patterns in GitHub/Jira data. Add SOC2-ready audit logging for enterprise teams. Create a workspace-wide coordination graph connecting tasks, people, blockers, and incidents. Integrate with DigitalOcean Spaces + more MCP tools. Move toward a fully autonomous engineering manager that handles planning, sprint analysis, and retros.