AI Developer Tool / MCP Server
A blog post describing ptc_runner’s MCP server and code-mode approach, where agents run short-lived untrusted programs inside a small Lisp REPL instead of Python or JavaScript.
The page clearly describes an AI-adjacent developer tool: an MCP server for agent code execution. It explains the purpose, the sandbox model, the Lisp-based execution environment, and how clients can use the server via tools like lisp_eval. There is enough visible detail to support a useful public listing.
The snapshot does not show installation steps, supported clients beyond general MCP compatibility, pricing/licensing, or a complete command/config example. The visible example also cuts off before showing the full code mode flow.
Last evaluated 97 days ago. Current rank #1605. Up 6 spots in the rankings.
A local-first Node.js utility that redacts emails, phone numbers, paths, secrets, URLs, and other identifiers from LLM prompts, then rehydrates responses locally using session-based mappings.
Self-hosted, OpenAI-compatible AI gateway for private RAG, natural-language data access, and tool-calling agents. It connects files, databases, vector stores, APIs, and MCP tools through one backend with auth, observability, and governance features.
A Claude Code skill that lets the model inspect live camera frames so it can verify hardware displays, spot wiring issues, and check physical UI behavior on real devices.
Runtime safety net for LLM agents that detects runaway token growth, classifies failure patterns, and suggests fixes without extra LLM calls. The project includes a Rust core, Python SDK, examples, benchmarks, and benchmark claims across multiple models and runs.
