{"uid":"cap_s2VbK7FGIrXAFK8GeTGv2","slug":"semantic-html-pruner-583aa531","name":"Semantic HTML Pruner","description":"Deterministic B2A/A2A/MCP/x402/MPP/L402 execution and intelligence node at https://mcp-gateway.agentdiet.dev settling in USDC on Base.","url":"https://mcp-gateway.agentdiet.dev/v1/semantic-html-pruner?utm_source=zero.xyz","method":"GET","headers":{},"bodySchema":{"type":"object","$schema":"https://json-schema.org/draft/2020-12/schema","required":["input"],"properties":{"input":{"type":"object","required":["type","method"],"properties":{"type":{"type":"string","const":"http"},"method":{"enum":["GET","POST"],"type":"string"},"queryParams":{"type":"object","properties":{"url":{"type":"string"},"mode":{"type":"string"}}}},"additionalProperties":false},"output":{"type":"object","required":["type"],"properties":{"type":{"type":"string"},"example":{"type":"object"}}}}},"responseSchema":{"type":"json","example":{"data":{},"status":"ok","roi_proof":{"compression_ratio_pct":91.4}}},"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.001","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":"$0.001/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.001","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.001","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_crDIMFHiEICCQ13hcQmEy","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.001","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Fetches a web page URL and strips it down to semantically meaningful HTML, achieving ~91% compression ratio for LLM-ready content extraction.","exampleAgentPrompt":"Can you fetch https://example.com/article and return only the semantically meaningful HTML, stripping out all the navigation, ads, and boilerplate so I can feed it to my LLM without wasting tokens?","exampleUseCases":[{"title":"LLM context injection from article","prompt":"Grab https://techcrunch.com/2024/05/01/openai-news/ and strip it down to just the meaningful content HTML — I want to inject it into my prompt without burning through my context window."},{"title":"Competitive pricing page extraction","prompt":"Fetch https://competitor.com/pricing and prune the HTML to only the semantic parts so I can compare their pricing tiers without all the junk markup."},{"title":"Research summary preparation","prompt":"Pull down https://research.org/papers/llm-scaling and return a compressed, semantically cleaned HTML version — I need the key content for my summarization pipeline."}],"resultDescription":"A JSON response containing a `data` field with the pruned HTML content, a `status` field indicating success, and an `roi_proof` object showing the compression ratio achieved (e.g. 91.4%). The compressed HTML retains semantic meaning while removing boilerplate, ads, navigation, and structural noise.","failureModes":["Invalid or unreachable URL returns an error status","URL behind authentication or paywalls may return empty or partial content","Very large pages may time out or return truncated results","URLs returning non-HTML content (PDFs, images) may fail to parse","Missing required `input` field returns a schema validation error"],"whenToPreferThis":"Choose this endpoint when you need to reduce HTML token footprint before feeding web content to an LLM, particularly when working with token-limited contexts. It is purpose-built for AI pipelines that need clean, semantic HTML rather than raw scraped content. Prefer it over general-purpose scrapers when compression ratio and LLM-readiness matter more than full fidelity.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-22T12:43:39.154Z","isFirstParty":false,"canonicalSlug":"semantic-html-pruner-583aa531"}