dataforseo-mcp
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- AlicenseDqualityDmaintenanceEnables LLMs to interact with DataForSEO and other SEO APIs through natural language, allowing for keyword research, SERP analysis, backlink analysis, and local SEO tasks.1009,164 npm82MIT
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- FlicenseBqualityCmaintenanceEnables SEO analysis and data retrieval through DataForSEO API, including keyword research, backlinks, competitor analysis, and on-page audits.24-
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- -licenseCqualityNot gradedmaintenanceEnables AI assistants to access comprehensive SEO data through DataForSEO APIs, including SERP results, keyword research, backlink analysis, on-page metrics, and domain analytics. Supports real-time search engine data from Google, Bing, and Yahoo with customizable filtering and multiple deployment options.36-
TDQS
Scored across 224 tools
With 224 tools and no descriptions, many tools have unclear boundaries—especially the labs_google_* keyword research family (keywords_for_site, related_keywords, keyword_suggestions, keyword_ideas) and multiple backlinks bulk endpoints. Platform prefixes help, but within categories multiple tools appear to overlap in purpose.
Names consistently use lowercase snake_case with domain prefixes, but the action placement varies (live suffix vs task_post/task_ready/task_get triads vs bare resource names). Some names are confusingly repetitive, like domain_analytics_technologies_domain_technologies, and granularity differs (merchant_google_products vs merchant_google_product_info).
224 tools is an extreme mismatch for an agent-facing MCP server. While DataForSEO is a broad API, exposing this many endpoints creates overwhelming selection pressure and exceeds any reasonable scope for a coherent tool set.
For a data-gathering API, the tool surface is very comprehensive, covering SERPs, keyword research, backlinks, on-page, business listings, reviews, app store data, and AI model responses. Minor inconsistencies exist—some providers have full task_post/ready/get flows while others only have live endpoints—but no major domain area is missing.