AgentBnB: P2P Network for OpenClaw Agents to Rent Skills
AgentBnB is a peer-to-peer network that enables OpenClaw agents to rent specialized skills from other agents. Instead of burning tokens on tasks they're not optimized for, agents can access capabilities that are already dialed in with the right environment, API keys, and prompts.
How It Works
Agents discover, rent, and pay for each other's capabilities using credits. The system handles discovery, execution, and payment automatically with no human in the loop.
Examples from the Source
- Coding task: An agent needed a Python scraper. It found a Claude Code Opus agent on AgentBnB, rented it for 33 credits, and received a production-ready script. The renting agent doesn't even have a Claude subscription.
- Stock analysis: An agent was asked to compare MSFT vs GOOGL. It found a deep-stock-analyst agent with Alpha Vantage integration, rented it for 30 credits, and got a full comparison report.
Technical Stack
The project is built with TypeScript, Fastify, and SQLite, and is deployed on Fly.io. The repository is available under an MIT license at github.com/Xiaoher-C/agentbnb.
📖 Read the full source: r/openclaw
👀 See Also
ClawRelay: macOS-native OpenAI-compatible LLM proxy with automatic failover
ClawRelay runs an OpenAI-compatible HTTP server on macOS 15+ with automatic failover between LLM providers. It supports OpenAI, Groq, Nvidia NIMs, Ollama, and any service with a /v1/chat/completions endpoint.
Open Source MCP Server Connects Claude to Brazilian Central Bank Economic Data
Sidney Bissoli created bcb-br-mcp, an MIT-licensed MCP server that provides Claude access to 18,000+ time series from Brazil's Central Bank (SGS/BCB). The server includes 8 tools covering interest rates, inflation, exchange rates, GDP, employment, and credit data.
Bullshit Benchmark Tests LLM Resistance to Nonsensical Prompts
The Bullshit Benchmark evaluates whether AI models identify and push back on obvious nonsense prompts instead of confidently generating incorrect answers. Results show Claude models perform significantly better than Gemini models at detecting nonsensical questions.
Gemma 4 E2B Tested as Multi-Agent Coordinator in TypeScript Framework
A developer tested Gemma 4 E2B as a coordinator in a multi-agent setup using the open-multi-agent TypeScript framework. The model successfully decomposed tasks into JSON, assigned agents, called tools like bash and file operations, and synthesized results.