{"uid":"cap_qLSQVriKwpzpYZx645zF8","slug":"context-window-optimizer-mcp-f8a8900c","name":"Context Window Optimizer 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/context-window-optimizer-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":"0.05","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":"$0.05/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.05","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.05","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_aWxWX2ni4tceDbSDaiTNw","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.05","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Optimizes and compresses content to fit within LLM context windows by processing input text data","exampleAgentPrompt":"Can you optimize this large block of text so it fits within a context window without losing the key information: [paste text here]?","exampleUseCases":[{"title":"Compressing long document for LLM","prompt":"I have this 50-page research paper I need to feed into an LLM but it's way too long — can you compress it to fit within the context window while keeping the important parts?"},{"title":"Trimming conversation history for agent","prompt":"My agent's conversation history has grown too large to fit in the model's context — can you optimize it so we stay within the token limit?"},{"title":"Fitting multiple documents into prompt","prompt":"I need to combine these three articles into a single prompt for my AI model but they're too long together — can you shrink them to fit in the context window?"}],"resultDescription":"Returns processed, optimized text content that has been compressed or restructured to fit within LLM context window constraints, preserving the most relevant information from the input data.","failureModes":["Empty or missing 'data' field returns a validation error","Input text that is already within optimal size may be returned unchanged","Extremely large inputs may time out or be truncated beyond usefulness","Malformed JSON input results in a 400 bad request response"],"whenToPreferThis":"Choose this endpoint when you need to programmatically reduce token usage or fit large text content into a constrained LLM context window, especially in agentic pipelines where context management is automated and requires a pay-per-call model.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-12T12:51:32.920Z","isFirstParty":false,"canonicalSlug":"context-window-optimizer-mcp-f8a8900c"}