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Tentra — Memory for AI Coding Agents

Official

by rdanieli · TypeScript

Memory for AI coding agents. Call graphs + refactor safety + persistent code context. 35 MCP tools.

Memory for AI coding agents. Call graphs + refactor safety + persistent code context. 35 MCP tools.

🛠️ Key Features

  • Memory for AI coding agents with a persistent code context
  • MCP-native architecture: integrates model-context protocol tooling
  • Call graphs and refactor safety to maintain code structure over time
  • Generates AI-made architecture diagrams from code
  • Works across MCP-enabled environments: Cursor, Claude Code, Codex, Winds
  • 35 MCP tools designed for model-context management

🚀 Use Cases

  • Maintain long-running AI coding sessions with persistent context
  • Safe refactoring with up-to-date call graphs
  • Visualize software architecture while coding
  • Optimize token usage via persistent context and tooling
  • Integrate with multiple AI coding agents in one project

⚡ Developer Benefits

  • Clear MCP-native workflow for model-context management
  • Reusable tooling and diagrams for team collaboration
  • Reduced context switching with persistent code graphs
  • Broad compatibility with major AI coding assistants

⚠️ Limitations

  • Specifics about tool primitives and runtime requirements are determined by MCP tooling updates
  • Dependency on MCP ecosystem compatibility and agent environments

Topics

agent-memoryaiclaude-codecode-graphcodexcursormcpmodel-context-protocolpersistent-contextsoftware-architecturetoken-optimizationtree-sittertypescriptwindsurftentra
Tentra — Memory for AI Coding Agents - agentage MCP Catalog