{"uid":"cap_8DeYhyTByY5LR5ODr7haU","slug":"ghost-embedding-cleaner-mcp-ed898569","name":"Ghost Embedding Cleaner 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/ghost-embedding-cleaner-mcp/api/process?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":null,"responseSchema":{"type":"json","example":{"success":true}},"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.08","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":"$0.08/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.08","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.08","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_OtTMkeIvUQhAFxU-9XIpg","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.08","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Detects and removes ghost embeddings (invisible or residual vector artifacts) from data payloads submitted as strings.","exampleAgentPrompt":"Can you clean this text of any ghost embeddings or hidden vector artifacts? Here's the data: 'The quick brown fox...[embedded content]...'","exampleUseCases":[{"title":"Sanitize AI-generated document output","prompt":"I've got this AI-generated document and I'm worried it contains ghost embeddings or hidden vector artifacts from the model. Can you clean it so the output is a pure, artifact-free string?"},{"title":"Strip residual embeddings from scraped content","prompt":"I scraped this web content and it seems to have invisible embedding artifacts embedded in it — can you run it through the ghost embedding cleaner and give me back the sanitized version?"},{"title":"Validate training data before model ingestion","prompt":"Before I feed this text chunk into my training pipeline, I need to make sure it has no ghost embeddings or leftover vector metadata. Can you clean it and confirm it's clear?"}],"resultDescription":"Returns a cleaned version of the submitted data string with ghost embeddings and residual vector artifacts removed, along with any metadata about what was detected and stripped.","failureModes":["Empty or null data field returns a validation error","Malformed JSON body results in a 400 bad request","Oversized payloads may be rejected or time out","Service may return an error if embedding detection is inconclusive","Payment failure (x402) blocks processing if USDC authorization is missing"],"whenToPreferThis":"Choose this endpoint when you need to sanitize text or data strings that may contain invisible or residual embedding artifacts, particularly in agentic or MCP pipeline contexts where ghost vectors could corrupt downstream processing. Useful as a preprocessing step before model ingestion, content publication, or data storage.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-12T00:42:24.382Z","isFirstParty":false,"canonicalSlug":"ghost-embedding-cleaner-mcp-ed898569"}