Team Brain: A Shared Memory Plugin for Claude Code That Stores Team Knowledge in Git

Team Brain is a Claude Code plugin that addresses the problem of AI coding assistants starting from zero each session by creating a shared memory system stored in Git. Instead of each team member's Claude having no knowledge of previous debugging sessions, decisions, or conventions, Team Brain stores this information in a .team-brain/ folder within your repository.
How It Works
Team members record knowledge as they work using specific commands:
/team-brain learn stripe webhooks retry 3x with exponential backoff/team-brain decide use REST over GraphQL for public API/team-brain convention always use async/await never .then()
Each entry saves as an individual markdown file in the .team-brain/ directory. The plugin automatically generates a BRAIN.md file that's capped at 180 lines, based on the observation that Claude applies instructions at 92% accuracy under 200 lines but drops to 71% above 400 lines.
Setup and Features
Installation requires cloning the repository to the Claude plugins directory:
git clone https://github.com/Manavarya09/team-brain.git ~/.claude/plugins/team-brainThen run /team-brain init in your project. On every session start, a hook checks for changes and loads the team brain automatically without manual configuration.
The cross-tool functionality generates .cursorrules for Cursor users and AGENTS.md for Copilot, ensuring team conventions apply regardless of which AI coding tool team members use.
The /team-brain onboard command reads everything and generates an onboarding document. According to the source, this allowed a new developer to become productive in 20 minutes instead of requiring a 2-hour walkthrough.
Technical Implementation
The system uses only files in Git with no servers, cloud services, or accounts required. Individual markdown files enable clean merging—two people can add knowledge on different branches without conflicts. This approach makes team knowledge persistent, version-controlled, and automatically available to all team members' Claude instances.
📖 Read the full source: r/ClaudeAI
👀 See Also

GPT-5.5 Codex vs Claude Opus 4.7: Real-world coding agent benchmarks
A developer pitted GPT-5.5 Codex against Claude Opus 4.7 on two real tasks: a PR triage bot and a real-time code review UI. Claude shipped cleaner with zero errors; Codex was 18% cheaper but needed a patch pass.

LocalSynapse MCP Server Enables Claude to Search Local Documents Offline
LocalSynapse is an MCP server that indexes and searches inside local documents (Word, Excel, PowerPoint, PDF) using hybrid BM25 + AI semantic search. Everything runs locally with no cloud or API keys required.

OpenClaw Setup on Ubuntu UTM VM with LLM API and Ollama Access
A user successfully configured OpenClaw in a sandboxed Ubuntu VM on an M3 Mac, with access to both local Ollama on macOS and external LLM APIs like Gemini, Claude, and DeepSeek. Sample configuration files and troubleshooting notes are available on GitHub.

MuninnDB adds Dream Engine for LLM memory consolidation with vault isolation
MuninnDB, a Go-based cognitive memory database, now includes a Dream Engine that performs LLM-driven memory consolidation between sessions using deduplication thresholds and semantic review. The system features vault trust tiers for data isolation and runs locally with Ollama.