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wnbhr/being

by Various

Personality Runtime — persistent memory, identity, and relationships for AI agents that work across multiple LLM platforms via MCP

MCP

wnbhr/being

Added 7 June 2026

#ai-agent #mcp #mcp-server #memory #personality #soul #typescript

Overview

A runtime for AI agents that maintains persistent memory, identity, and relationship data across different LLM platforms. It uses the Model Context Protocol (MCP) to enable cross-platform agent continuity.

Best for

Best for
Developers building cross-platform AI agents that need consistent personality and memory

Use cases

  • Building agents with long-term memory across sessions
  • Creating agents that maintain consistent identity across multiple LLM providers
  • Developing multi-platform agent systems with shared relationship data

How to use

Install

npm start

Tools exposed

  • Node.js 22+
  • Supabase
  • Anthropic API key
  • OpenAI API key
  • Google API key

Example client config

{\n  "mcpServers": {\n    "my-being": {\n      "url": "https://being.ruddia.com/mcp/<being_id>",\n      "headers": {\n        "Authorization": "Bearer brt_your_token_here"\n      }\n    }\n  }\n}

Notes

A runtime for AI agents that maintains persistent memory, identity, and relationship data across different LLM platforms. It uses the Model Context Protocol (MCP) to enable cross-platform agent continuity.

0 stars on GitHub. Last updated 2026-05-28.

Use cases

  • Building agents with long-term memory across sessions
  • Creating agents that maintain consistent identity across multiple LLM providers
  • Developing multi-platform agent systems with shared relationship data

Pros

  • Persistent memory and identity across LLM providers via MCP
  • Standardized integration through the Model Context Protocol
  • Written in TypeScript for broad compatibility with JavaScript/TypeScript stacks

Cons

  • Very early stage with zero GitHub stars, indicating minimal adoption or testing
  • Requires MCP-compatible LLM platforms, which may limit usability
  • Likely limited documentation and community support due to low popularity

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Persistent memory and identity across LLM providers via MCP
  • Standardized integration through the Model Context Protocol
  • Written in TypeScript for broad compatibility with JavaScript/TypeScript stacks

Cons

  • Very early stage with zero GitHub stars, indicating minimal adoption or testing
  • Requires MCP-compatible LLM platforms, which may limit usability
  • Likely limited documentation and community support due to low popularity
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