MCP Replay vs WurldCam

MCP Replay is a trace viewer for the Model Context Protocol, the open standard AI agents use to call tools. Record a session with the free mcp-tape command line tool, then open it on your phone: every request, response, error, and latency, organized and searchable. WHAT YOU CAN DO - Open .jsonl traces from Files, AirDrop, or any share sheet - Follow a replay link someone sent you, or paste a bare share ID - Watch a live session streaming from mcp-tape on your own network - See paired tool calls with latencies, and per-tool stats (count, errors, avg, p95) - Filter the timeline by tool or method - Share a trace as a link that expires after 30 days, with a delete token so you stay in control BUILT FOR PRIVACY Traces stay on your phone. Nothing is uploaded unless you explicitly share a trace, and there are no accounts, no analytics, and no tracking. Live mode connects directly to your own computer; the stream never touches a server. FOR ANYONE BUILDING WITH AGENTS If you use Claude, ChatGPT, or any MCP-compatible agent framework and have ever asked "what did it actually do?", this is the answer. Record with one command: npx mcp-tape -- your-mcp-server-command Then open the trace here or at mcpreplay.dev. MCP Replay is open source and independent. It works with any tool that emits the open mcp-tape trace format.

WurldCam turns an iPhone Pro into a posed RGBD capture rig. Every recording contains the colour video, the LiDAR depth map, the camera's position and orientation for each frame, and per-pixel depth confidence — written together into a single file as you record, not stitched together afterwards. Depth is stored losslessly, so the millimetres your sensor measured are the millimetres you get back. Built for people who need the geometry, not just the picture: 3D reconstruction, robotics datasets, SLAM evaluation, NeRF and Gaussian-splat capture, photogrammetry research. • Records to the open wurld format (Matroska/WebM container) or Record3D .r3d • Lossless 16-bit depth, per-frame poses in metres with quaternion rotations • Files stay on your device — no account, no cloud, no analytics • Retrieve captures via the share sheet or the Files app • Read them with the open-source Python and JavaScript tools Requires a LiDAR-equipped iPhone. The support page covers device requirements, retrieving captures via Files, reading the format, why frames get skipped, and where to file issues — so it answers the questions review may probe rather than being a placeholder.