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Vibetape

🧠 Hybrid Active Memory MCP Server for AI-Driven Development | Capture, analyze & leverage build moments through semantic AI memory | Transform your dev workflow with intelligent context preservation

Installation
Run this command in your terminal to add the MCP server to Claude Code.
Run in terminal:
Command
claude mcp add --transport stdio sambaleuk-vibetape-mcp-server node /absolute/path/to/Vibetape-MCP-Server/dist/server.js \
  --env OPENAI_API_KEY="your-openai-key-here"

How to use

VibeTape is an MCP server that records development moments, coordinates multiple agents, and provides intelligent context management and handoffs compatible with any MCP-enabled client. It exposes a rich set of tools for capturing wins, failures, decisions, and notes, as well as task management, actor/agent registration, and context scoring. You can use it to build multi-agent workflows where agents share a persistent, queryable history of actions and outcomes, with smart context selection to stay within token budgets. The system is designed to integrate with LangGraph-compatible payloads and supports RETEX-style prescriptive insights for improving future work.

How to install

Prerequisites:

  • Node.js and npm installed on the host
  • Git available to clone the repository
  1. Clone the repository:
git clone https://github.com/sambaleuk/Vibetape-MCP-Server.git
cd Vibetape-MCP-Server
  1. Install dependencies:
npm install
  1. Build the project (if applicable):
npm run build
  1. Run the server locally (example):
# Ensure environment variables are set as needed
OPENAI_API_KEY=your-key-here npm start
  1. Verify the server is running and accessible via your MCP client by adding the server entry (see mcp_config) and testing basic MCP commands like mark_moment, register_actor, and create_task.

Additional notes

Tips and common considerations:

  • Set OPENAI_API_KEY (and any other required API keys) in your environment or in your MCP client configuration.
  • Update the cwd and paths in mcp_config to point to your actual deployment location.
  • The server supports LangGraph-compatible handoffs and RETEX generation; ensure your MCP client can send and receive these payloads.
  • Watch for token budget limits when selecting context; use context_relevance_score and evaluate_context_window tooling when available.
  • If you see connection issues, verify that the server process has started successfully and that the client is configured with the correct command, args, and working directory.

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