Built to catch when AI agents get stuck in repetitive loops during task execution. This runs as a Cloudflare Worker and exposes both REST and MCP interfaces over streamable HTTP, so you can integrate loop detection into your agent workflows without spinning up your own infrastructure. Reach for this when you're building autonomous agents that might spiral into the same actions repeatedly and you want an external service to flag the pattern. The MCP interface means Claude can directly call it during conversations to check if it's repeating itself across tool calls or reasoning steps.
Cloudflare Workers MCP server: agent-loop-detector. REST + MCP (JSON-RPC 2.0). Live: api.lazy-mac.com/agent-loop-detector
io.github.ericm1018/skillfm-llm-cost-optimizer-openai-anthropic-usage
io.github.mikerawsonnz/llm-orchestration-agent
io.github.mikerawsonnz/authenticated-llm-agent
labforgedev/copilot-memory-mcp
csoai-org/agent-prompt-injection-firewall-mcp
io.github.mikerawsonnz/authenticated-multi-llm-agent