{"uid":"cap_gvyPUCsJRCfL4fzkVvj1W","slug":"agentstools-dedupe-name-address-deduplication-cdde38a6","name":"AgentsTools Dedupe – Name & Address Deduplication","description":"Deduplicate a list of names or addresses into clusters of likely duplicates. Blocks by similarity key then confirms pairwise inside each block, returning clusters with a canonical representative plus a summary of input, cluster and duplicate counts. Similarity indicators, not authoritative identity resolution.","url":"https://api.agentstools.dev/match/dedupe","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"type":{"enum":["person","company","address","product","org"],"type":"string","description":"Entity type selecting the normalization pipeline (default company)"},"items":{"type":"array","items":{"type":"string"},"description":"The list of strings to deduplicate"},"min_score":{"type":"integer","description":"Optional match threshold 0-100 (default is the per-type threshold)"}}},"responseSchema":null,"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.02","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":"$0.02/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.02","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.02","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_gFvc7twlwzl5qAGOrZ1Hj","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.02","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Deduplicates a list of names or addresses into clusters of likely duplicates, returning a canonical representative per cluster plus summary statistics.","exampleAgentPrompt":"Can you deduplicate this list of company names for me — ['Acme Corp', 'Acme Corporation', 'ACME corp.', 'Widget Co', 'Widget Company Inc'] — and group the ones that are likely the same company together?","exampleUseCases":[{"title":"CRM contact list deduplication","prompt":"I have a list of customer names from our CRM that I need cleaned up — ['John Smith', 'Jon Smith', 'J. Smith', 'Jane Doe', 'Jane D.'] — can you cluster the ones that are likely the same person and tell me which is the canonical name for each group?"},{"title":"Vendor database deduplication","prompt":"We imported suppliers from three systems and now have duplicates — can you deduplicate these org names: ['Siemens AG', 'Siemens', 'SIEMENS AG', 'Bosch GmbH', 'Robert Bosch GmbH', 'Bosch'] and group the ones that refer to the same company?"},{"title":"Mailing address list cleanup","prompt":"Before we send out this mailing, can you deduplicate these addresses and flag which ones are likely the same location: ['123 Main St, Springfield IL 62701', '123 Main Street, Springfield, IL 62701', '123 Main St Springfield Illinois', '456 Oak Ave, Chicago IL 60601']?"}],"resultDescription":"Returns clusters of likely-duplicate strings, each with a canonical representative, plus a summary of total input count, number of clusters, and number of duplicates found. Similarity is probabilistic (not authoritative identity resolution).","failureModes":["Empty or single-item list returns no clusters","Highly abbreviated or truncated inputs may fail to match obvious duplicates","Very large lists may hit payload limits","min_score set too high causes under-clustering; too low causes over-clustering","Non-standard characters or mixed scripts may reduce match quality"],"whenToPreferThis":"Choose this endpoint when you have a raw list of names, addresses, or organization strings that may contain near-duplicates and you need fast probabilistic clustering without standing up your own record-linkage pipeline. Ideal for pre-processing CRM imports, mailing lists, vendor databases, or any scenario where string normalization and fuzzy matching across entity types (person, company, address, product, org) is needed in a single API call.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-09-15T01:13:44.975Z","isFirstParty":false}