TeamContext is our youngest product. It exists because halfway through 2025, our own engineering team hit a wall that no existing tool was solving.
Everyone had gone AI-native. Some of us used Claude Code. Others used Cursor. A couple used Windsurf. Each of those tools remembers the context of its own sessions, but none of them shared state with the others, and none of them shared state with the wider team.
The symptom: three engineers trying the same refactor in parallel because nobody knew the other two had already tried it and backed out.
What MCP made possible
The Model Context Protocol, which Anthropic published in late 2024, was the key that unlocked the product. Suddenly there was a standard way for coding agents to publish and subscribe to shared state. We built TeamContext as an MCP server that every major AI coding tool can connect to.
What flows through the server:
- Session metadata (what file, what intent, what outcome)
- Decisions and trade-offs the agent walked through
- Conflicts — “someone else is editing this, with this reason”
- Summaries the team can skim at 9am on Monday
What doesn’t flow: raw source. TeamContext is metadata-only by design. Your code never leaves your repo.
What we learned shipping it
- MCP-native beats dashboards. Engineers don’t want to open another tab. TeamContext lives inside their existing AI coding tool.
- Zero-config wins. Setup is one CLI command. If it’s two, adoption halves.
- The team likes transparency more than we expected. Nobody asked to turn off the activity feed.
A year ago we were looking for a tool like this. Now we operate it for 600+ engineering teams.