Surfaces.
The right context, delivered wherever your team already works. From IDE to pull request to Slack, Topogy surfaces relevant intelligence at the moment it matters.
The brain is the model. Surfaces are where it shows up.
Every surface draws from the same knowledge graph — so whether you're in your IDE, on Slack, reviewing a PR, or looking at a dashboard, you're working from the same shared understanding.
MCP Server
The canonical interface between Topogy and AI agents. Any MCP-compatible coding tool — Claude Code, Cursor, Copilot — can query the knowledge graph for context, report activity, and receive feedback. This is how agents get smart.
- Dynamic context scoping per task
- Convention and architecture pattern delivery
- Session activity reporting
- Bidirectional: agents query and agents inform
Web App
The command center for engineering leadership. Visualize your knowledge graph, explore system architecture, track metrics, configure workflows, and monitor AI adoption — all in one place. Where VP Engs and architects go to understand what's happening across the org.
- Interactive knowledge graph explorer
- Engineering and AI metrics dashboards
- Drift detection and risk map views
- Workflow configuration and run history
- Cost attribution and ROI reporting
GitHub App
Topogy in the pull request. Automated checks for convention adherence, blast radius analysis, drift detection, and architecture coherence — surfaced as PR comments and status checks. Engineers and reviewers get context without leaving GitHub.
- Convention compliance checks on every PR
- Blast radius annotations
- AI-generated vs. human-written code labeling
- Architecture coherence status checks
Slack
Alerts, insights, and workflow triggers where your team already communicates. Topogy posts drift alerts, overnight workflow summaries, and metric highlights to the channels that matter. Engineers can query the knowledge graph directly from Slack.
- Drift and risk alerts to team channels
- Overnight workflow result summaries
- Natural language queries against the knowledge graph
- Workflow triggers and approvals
Ticketing
Topogy enriches your issues and project tracking with system context. Link tickets to affected services, surface architecture dependencies during planning, and close the loop between what was planned and what agents actually built. Works with Linear, Jira, and other planning tools.
- Auto-link tickets to affected services and components
- Architecture context surfaced during sprint planning
- Ticket-to-PR-to-agent-session traceability
- Spec and convention references attached to issues
One model, many surfaces.
Every surface reads from and writes to the same knowledge graph. When an agent queries context via MCP, that session updates the model. When a PR triggers a GitHub check, the results feed back into the system intelligence. When Slack surfaces a drift alert, it's drawn from the same data the Web App dashboard shows. No sync issues. No stale views. One shared understanding, everywhere your team works.