Team Memory MCP: Open Source Shared Memory for Claude Code with Bayesian Confidence Scoring
Team Memory MCP is an open source (MIT licensed) shared memory solution for Claude Code that addresses the problem of AI agents forgetting team-specific patterns between sessions. The tool tracks collective confidence in patterns rather than just storing information.
Key Features
- Bayesian Confidence Scoring: Uses a Beta-Bernoulli model to rank patterns based on real-world evidence. Confirmations from engineers increase confidence; corrections decrease it.
- Temporal Decay: Knowledge that isn't re-validated gradually fades with a 90-day half-life, keeping the memory relevant.
- Transparent Scoring: The scoring is computed from real-world evidence using pure math, not expensive LLM API calls.
- Zero-Config Setup: Can be added to Claude Code in seconds with a single command.
Setup
Add Team Memory MCP to Claude Code with this command:
claude mcp add team-memory -- npx team-memory-mcpResources
The developer has published a deep dive article covering the technical implementation, the Bayesian math behind the scoring system, and a full setup guide on LinkedIn. The project is available on GitHub at github.com/gustavolira/team-memory-mcp.
This tool is designed for development teams using Claude Code who need to maintain consistent project-specific standards and patterns across AI coding sessions.
📖 Read the full source: r/ClaudeAI
👀 See Also
LLM Skirmish: A Real-Time Strategy Game Benchmark for AI Coding Agents
LLM Skirmish is a benchmark where AI agents write code to play 1v1 real-time strategy games against each other. It uses a modified Screeps API and tests in-context learning across five tournament rounds.
Claude Code Remote Control: Continue Local Sessions from Any Device
Claude Code Remote Control lets you continue local Claude Code sessions from other devices like phones or browsers while keeping everything running on your machine. It's available as a research preview on Pro and Max plans, requiring authentication and workspace trust setup.
Surgical GitHub Extraction: A Claude Skill to Fetch One Function, Not the Whole Repo
A new open-source Claude Skill named surgical-github-extraction stops Claude Code from cloning entire repos when you only want one function or pattern. It reads the README, pulls 1–3 raw source files, and lifts the smallest useful unit with a provenance comment.
SWE-CI: New Benchmark Tests AI Agents on Long-Term Code Maintenance via CI
SWE-CI is a repository-level benchmark that evaluates LLM-powered agents on maintaining codebases through continuous integration cycles, shifting focus from static bug fixing to long-term maintainability across 100 real-world tasks.