{"uid":"cap_FELKUQqLhX4stP8gV54RD","slug":"point-cloud-denoiser-mcp-35366d07","name":"Point Cloud Denoiser MCP","description":"The premier global index of 1,069 monetized MCP nodes across 205 specialized subdomains. Gasless USDC runtime settlements via x402 V2 Spec on Base L2. Save 95% token context.","url":"https://api.m2mcent.com/point-cloud-denoiser-mcp/api/process","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"payload":{"type":"string"}}},"responseSchema":{"type":"json","example":{"success":true}},"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.35","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"probe","requiresHandshake":false,"reviewCount":0,"rating":{"score":"0.00","successRate":"0.00","reviews":0,"stars":null,"state":"unrated"},"availabilityStatus":"unknown","priceObserved":null,"sessionDeposit":null,"pricing":{"kind":"static","summary":"$0.35/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.35","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.35","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_f9WUzbMW9Ge9kn-7SYp1r","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.35","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Removes noise from 3D point cloud data to produce cleaner, more accurate spatial datasets","exampleAgentPrompt":"Can you clean up this noisy LiDAR point cloud data I have — it has a lot of outlier points and scan artifacts that need to be removed before I process it further?","exampleUseCases":[{"title":"LiDAR scan artifact removal","prompt":"I have raw LiDAR scan data from a drone survey and it's full of noise and outlier points — can you run it through the point cloud denoiser to clean it up before I use it for terrain modeling?"},{"title":"Photogrammetry output cleanup","prompt":"My photogrammetry software generated a point cloud from these photos but there's a ton of scattered noise points around the edges. Can you denoise this point cloud data so I get a cleaner mesh?"},{"title":"3D sensor data preprocessing","prompt":"I'm getting noisy depth sensor readings from my robot's 3D camera and need to clean the point cloud data before running object detection on it — can you filter out the noise?"}],"resultDescription":"A processed, denoised point cloud with noise points and outliers removed, returned as cleaned spatial data ready for downstream 3D processing, reconstruction, or analysis tasks.","failureModes":["Malformed or invalid point cloud data format returns an error","Data string too large may cause timeout or processing failure","Empty data field results in no output or error response","Unsupported point cloud encoding or format may not be processed correctly"],"whenToPreferThis":"Choose this endpoint when you need to preprocess noisy 3D scan data (LiDAR, photogrammetry, depth sensors) before downstream tasks like mesh reconstruction, object detection, or spatial analysis. Useful when raw sensor data contains outliers, artifacts, or statistical noise that would degrade model accuracy.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-09-15T07:12:44.848Z","isFirstParty":false}