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619,919 tools. Updated 2026-09-28 19:52

"Search engine optimization information and resources" matching MCP tools:

  • Maps only stable Tier1 finding identifiers to approved Tier1 services and public resources. Call after a Tier1 score or email-domain check. Do not submit prose, URLs, customer information, or invented identifiers. This tool performs no arbitrary fetching, makes no contact request, changes nothing, and stores nothing.
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  • Reference text on supply-chain simulation — how a discrete-event model of a network behaves through time. Covers event-driven execution (future-event list, the consume / check-inventory / place-order / fill / ship / deliver vocabulary), why inventory POSITION rather than on-hand stock drives reordering, which KPIs the engine reports versus which this site derives from the raw order and shipment records, when to reach for simulation, for optimization, and for both together, and the honest limitations of these runs (single deterministic replication, cached results, warm-up inside the reported window, fixed sample parameters). Pure static text — no engine call, deterministic output. Use this when the user asks a conceptual 'how does the simulation work', 'why did this DC stock out', or 'should I simulate or optimize' question rather than asking for a number; call run_simulation when they want actual figures.
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  • The FULL ReefAPI catalog — EVERY engine with its one-line title, grouped by category. This is the whole menu (≈ a few thousand tokens); SCAN IT AND PICK THE BEST ENGINE YOURSELF. You are an LLM, so you match the user's intent semantically — across ANY language, typo, or phrasing — far better than a keyword search can. Use this whenever search_engines didn't surface the right engine (or to be sure you didn't miss a better one). After you pick: get_engine_schema(engine) -> get_action_schema -> call_engine.
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  • Get Reddit subreddit by name with its posts. FAST (default, omit responseType or responseType="fast"): Returns subreddit data with up to 300 posts directly (use limit param to reduce). Auto API fallback for fresh data. PAGING (responseType="paging"): Async paginated results (100 posts per page), returns operationId for polling via checkOperationStatus. Supports pageNumber/tableName for subsequent pages. RESPONSE STRUCTURE: Returns { results: { subreddit: {...}, posts: [...] }, pagination: {...} }. FIELD SELECTION: Use subredditFields for subreddit data optimization, postFields for post data optimization. First searches database for both subreddit and posts, then external API if data is stale or missing. This is a safe, read-only tool for analyzing searchable information.
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  • Get the precomputed result for one scenario of an optimization demo. Returns the verbatim engine output JSON (AMOS for tariff/coffee, SSO output for sso-basic) including the optimal sourcing/production/transport decisions, costs, and any open/close facility variables. ANTI-FABRICATION: every numeric result is verbatim from the optimization engine that ran offline — quote them in your reply, do not round or recompute. Call describe_opt_demo first to learn valid scenario_key formats for each demo.
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  • Get integration details for public endpoints and MCPs from `search` results. Provide a `task` describing what you want to accomplish and up to 10 `resources` — each with an `id` and `type` taken from the matching search result's `resourceType`. Returns a task brief covering authentication, base URLs, request steps, parameters, expected responses, dependencies between steps, and other important considerations.
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Matching MCP Servers

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    Provides nine specialized production-ready solvers for advanced resource allocation, network flow, and multi-objective optimization with native Monte Carlo integration. It enables users to perform constraint-based decision-making and performance analysis directly through Claude Code.
    MIT
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    Enables searching documentation from GitHub repositories and web pages via MCP tools, with in-memory indexing and caching for fast retrieval.
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Matching MCP Connectors

  • Search 30,000+ decided U.S. security-clearance (DOHA) decisions: cases, outcomes, statistics, and timelines, with a citable link for every answer. CASE is the searchable public record of DOHA industrial security-clearance decisions from 1996 to the present, refreshed nightly.

  • Search, navigate, and explore the Quran through 8 MCP tools — verses, surahs, lemmas, roots, and morphology. Hosted at mcp.quran.us.kg.

  • Reference text on supply-chain network optimization — mixed-integer programming (MIP), the structure of decision variables and constraints, the objective function for landed-cost minimization, and the common problem classes (facility selection, sourcing, flow constraints, multi-period, BOM/production, multi-objective). Also covers when to reach for optimization vs simulation. Pure static text — no engine call, deterministic output. Use this when the user asks a conceptual 'how does network optimization work' question. ChiAha's AMOS optimizer (open-source, Odin, GLOP/CBC via OR-Tools) powers the Tariff and Coffee Co-pack demos on the sandbox.
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  • Get comprehensive usage guide for FundingLandscape tools. Call this FIRST to understand optimal workflows, parameter usage, and best practices. Returns detailed documentation for search tools, filters, and token optimization strategies. Does not count toward your monthly searches.
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  • Keyword search across ALL ChangeGamer content (resources and editorial guides) with server-side ranking: term hits in title weigh most, then tags, then description. Returns ranked rows with type, slug, title and .md URL (no body content). Use get_resource/get_article to fetch winners.
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  • Keyword search across ALL ChangeGamer content (resources and editorial guides) with server-side ranking: term hits in title weigh most, then tags, then description. Returns ranked rows with type, slug, title and .md URL (no body content). Use get_resource/get_article to fetch winners.
    ConnectorNo auth
  • Sends one prompt to 1 to 4 search assistants (Perplexity, OpenAI, Anthropic, Gemini) and reports whether each cites your target domains: cited status, citation count, cited domains, model, and a structured error per engine. Started concurrently; a failed engine returns `cited: null` and does not block the others (PD7). Paid, $0.75/call; read-only and safe to retry.
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  • Search and rank African food records by relevance across names, aliases, categories, countries, regions, descriptions, uses, and nutrition information.
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  • Audits content for Answer Engine Optimization (AEO): Evaluates concise 40-60 word direct answer definition blocks, question-based H2/H3 subheadings (What/How/Why), FAQ schema alignment, and citation readiness for Google AI Overviews and Perplexity. USAGE GUIDELINES: - Use when optimizing content to win conversational AI search citations, direct answers, and Perplexity summaries. - Do NOT use for brand knowledge-graph entity reconciliation; use 'seo_audit_geo' instead. - Do NOT use for standard on-page metadata; use 'seo_audit_onpage' instead. BEHAVIORAL TRANSPARENCY: - Safe, read-only diagnostic evaluation. No file modifications.
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  • Audits Generative Engine Optimization (GEO): Evaluates brand and organization entities, Schema.org Organization/Person definitions, sameAs knowledge graph reconciliation (Wikidata, LinkedIn, Crunchbase), and Author E-E-A-T credentials. USAGE GUIDELINES: - Use to evaluate how LLM-based search engines (ChatGPT Search, Claude, Gemini) comprehend brand identity and authority. - Do NOT use for local map pack NAP consistency; use 'seo_audit_local' instead. - Do NOT use for direct answer snippet definitions; use 'seo_audit_aeo' instead. BEHAVIORAL TRANSPARENCY: - Safe, read-only diagnostic evaluation. No file modifications.
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  • Tests a live website or local endpoint for Web MCP enablement: Checks Streamable HTTP (/mcp), Legacy SSE (/sse), discovery manifests (/.well-known/mcp/server-card.json, llms.txt), CORS headers, and provides copy-paste implementation blueprints in 11 programming languages. USAGE GUIDELINES: - Use to test if a web application exposes an agent-accessible Model Context Protocol interface. - Do NOT use for regular HTML search engine optimization; use 'seo_audit_technical' or 'seo_audit_onpage' instead. BEHAVIORAL TRANSPARENCY: - Safe, read-only protocol diagnostic probe. Makes HTTP GET/HEAD requests to standard discovery endpoints. Modifies no files.
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  • Creates a screenshot of an existing web page at content.url. Rendering loads the page and its resources in a browser and executes its JavaScript. Set content.full_screen for the entire scrollable page, or content.selector to capture a particular element. Returns asset ID, URL, and format information in item; include_image_data requests an eager inline preview. Use create_image when supplying HTML/CSS directly, or create_templated_image when rendering a saved template.
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  • Execute live web searches using multi-engine chain (TinyFish, DuckDuckGo, Jina) without monthly API subscriptions. Returns fresh source URLs, titles, and snippets. Requires x402 micropayment (0.005 USDC on Base). When to use: Real-time web browsing and information retrieval for AI agents. When NOT to use: Do NOT use for deep recursive crawling of entire sites. Parameters: - `query` (string, required): Search query (3-300 chars). - `limit` (integer, optional, default 5): Maximum number of search results to return (1-10).
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  • Universal search tool supporting all SerpApi engines and result types. When to use: - Any query needing live, structured SERP data: web results, news, product listings, job postings, local businesses, flight/hotel prices, video results, images, stock/weather cards, knowledge graph entities. Engine discovery via MCP resources: - serpapi://engines lists all engines supported by this tool. - serpapi://engines/<engine> provides engine-specific parameters and supported options. - Example: serpapi://engines/google_news Input schema: params: JSON object containing SerpApi engine parameters. Common parameters: - q: Search query. Required for most engines. - engine: SerpApi engine name. Defaults to "google_light". - location: Optional geographic location for localized results. - output: Optional response format. Omit for JSON (default), or set to "md" for Markdown. Engine-specific parameters are available via MCP resources: - serpapi://engines lists all supported engines. - serpapi://engines/<engine> provides parameters and options for one engine. mode: Response mode. Defaults to "complete". - "complete": Return the full SerpApi response. - "compact": Remove metadata fields from JSON responses. Markdown is returned unchanged. Output schema: structuredContent.result contains the response string: serialized JSON or unchanged Markdown. The same string is included in text content. Tool failures preserve this wrapper and set isError to true. Guided search: Searches can request missing engine parameters from supporting clients using the engine catalog and engine-specific rules. Flights collect airports and dates, hotels collect the destination and stay dates, and directions collect missing endpoints. Other clients receive a missing-parameter error. Cancellation does not run a search. Examples: Weather: {"params": {"q": "weather in London", "engine": "google"}, "mode": "complete"} Stock: {"params": {"q": "AAPL stock", "engine": "google"}, "mode": "complete"} General: {"params": {"q": "coffee shops", "engine": "google_light", "location": "Austin, TX"}, "mode": "complete"} Compact: {"params": {"q": "news"}, "mode": "compact"} Markdown: {"params": {"q": "news", "output": "md"}} Supported engines include (not limited to): - google - google_light - google_flights - google_hotels - google_images - google_news - google_local - google_shopping - google_jobs - bing - yahoo - duckduckgo - youtube_search - baidu - ebay
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  • Search ARCO variables by name for a dataset. As with get_arco_variables, a "reference" (kerchunk) match is often listed once per variant — always pick the "-osdf" variant's URL (reachable from anywhere), and open it with xr.open_dataset(url, engine="kerchunk", storage_options={"remote_protocol": "https", "lazy": True}). A "zarr" match needs no variant picking — its URL already routes through the OSDF director (rewritten automatically); open it directly with xr.open_dataset(url, engine="zarr"). Args: dsid: Dataset ID (dNNNNNN), e.g. d083002 query: Search text to match against variable names
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  • Execute live web searches using multi-engine chain (TinyFish, DuckDuckGo, Jina) without monthly API subscriptions. Returns fresh source URLs, titles, and snippets. Requires x402 micropayment (0.005 USDC on Base). When to use: Real-time web browsing and information retrieval for AI agents. When NOT to use: Do NOT use for deep recursive crawling of entire sites. Parameters: - `query` (string, required): Search query (3-300 chars). - `limit` (integer, optional, default 5): Maximum number of search results to return (1-10).
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  • Score content quality on a 0-100 scale before publishing. Evaluates 5 factors (20 points each): 1. Text length optimization for target platforms 2. Hashtag count optimization 3. Posting time alignment with best engagement windows 4. Media presence (images/videos) 5. Content patterns (CTA, hooks, formatting, emoji) Returns overall score, per-factor breakdown, and improvement suggestions.
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