Agoragentic: pip-installable agent marketplace for buying and selling capabilities
Agoragentic is an agent-to-agent marketplace where AI agents can discover and invoke capabilities from other agents. Think of it as an app store for agent skills - your agent can search for capabilities like "summarize research papers," find one that costs $0.003 per call, invoke it, and get results back.
Installation and tools
The integration is available via pip:
pip install agoragenticAfter installation, agents get four tools:
register- get API key and free creditssearch- browse capabilities in the marketplaceinvoke- call a capabilityvault- check owned items
Technical details
The marketplace runs on USDC (Base L2) for payments with a 3% platform fee. New agents receive $0.50 in free test credits to try the system. The integration also works as an MCP server for users of Claude Desktop or VS Code.
This type of marketplace could be particularly useful for capabilities that are expensive to build but widely useful, allowing agents to extend their functionality beyond their local skills without developing everything in-house.
📖 Read the full source: r/clawdbot
👀 See Also
One-Command Docker Setup for OpenClaw with Full-Disk Encryption and Monitoring
A Docker setup for OpenClaw that provides full-disk encryption guides, Tini as PID 1, built-in monitoring tools, and data stored as plain files on the host. Deployment requires just two commands: git clone and ./shell.
Developer Builds Tool for Realistic Relational Database Generation
A developer built a tool that generates fully loaded relational databases with realistic data, solving the problem of creating test databases with intact foreign key relationships and cross-table consistency.
ClaudeMeter: Open-Source macOS Menu Bar App for Real-Time Claude Usage Tracking
ClaudeMeter is a free, open-source macOS menu bar app for Claude Max subscribers that displays session and weekly usage percentages, reset timers, and pace indicators without interrupting workflow. The entire app was built using Claude (Claude Code/Opus) for Swift code, Supabase backend, and Edge Functions.
Bodega Inference Engine: Optimizing LLM Inference for Apple Silicon's Unified Memory
Bodega is an inference engine built specifically for Apple Silicon's unified memory architecture, addressing throughput limitations by redesigning continuous batching and KV cache management for MLX. The developer reports working on it for 2.5 years with optimizations close to the Metal layer.