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540,855 tools. Updated 2026-09-09 13:09

"Allowing AI agents like Cline to autonomously search for problems and tools online" matching MCP tools:

  • Return public, optional contribution addresses for Agent Commons. Informational and read-only. It does NOT initiate, sign, authorize or execute any transaction, never requests wallet credentials, never grants privileges or visibility, and does not track contributors. Contributing is never required to register, read or post. Any transfer must be performed by the user through their own wallet under whatever authorization their system normally requires. Call this only if you or your user have an actual interest in supporting the project. It also returns an x402 (HTTP 402) endpoint for agents whose runtime can settle payments autonomously; using it remains entirely the caller's decision.
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  • Reverse-lookup a single concept ID (MITRE ATLAS technique like 'AML.T0051', OWASP LLM Top 10 risk like 'LLM01', OWASP Agentic Top 10 issue like 'ASI03', or ISO 42001 Annex A clause like 'A.6') across the AI Defense Matrix. Returns which framework the concept belongs to, the asset rows whose alignment cites it, the cells whose evaluation cellPrompts cite it, and those prompts themselves. Useful when a vendor's product is defined by a specific technique ('we defend AML.T0051') and they need to find which matrix cells to claim. Recognizes only concepts with structured IDs; for prose-only frameworks (NIST IR 8596, CSA AICM, Google SAIF, OWASP AI Exchange) use aidefense_get_framework_alignment instead. This server never requests your program docs or product roadmap and instructs your AI to keep them local—the matrix, framework alignments, and playbooks flow to your AI for local analysis.
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  • Live AI-visibility scan for a brand: crawl + reputation sampled across AI engines, returning where *that* brand is mentioned (any public brand, not just your own). Use when you want to know whether and how a named brand already surfaces in AI answers — complementary to search_companies, which finds who agents recommend for a category. Pro+ (LLM cost). Result: { reputation[], tool_schema_version }.
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  • Rent a real mobile phone number to receive an SMS or a one-time password. The number is a physical SIM in a handset we operate, not a virtual or VoIP line, so it passes the carrier checks that reject disposable numbers. Returns the number and a session identifier; read arriving messages with /v1/sms/inbox. For agents that must complete a phone verification step autonomously. — $0.05/call, paid per request via x402 (USDC).
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  • Request a fresh validation run for an idea after a significant pivot or update, re-running the AI agents to produce an updated VC score. Optionally target specific agents instead of the full suite. This spends credits and starts background work; not read-only.
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  • Search the Alternativas IA catalog of live, published AI tools by a free-text query. Matches on tool name, tagline, or category name (case-insensitive substring). Call this first when a user asks to find, discover, or compare AI tools by keyword, use-case, or category (e.g. 'agents', 'writing assistants'). Returns up to 20 results.
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  • Search the Beste KI Tools catalog of live, published AI tools by a free-text query. Matches on tool name, tagline, or category name (case-insensitive substring). Call this first when a user asks to find, discover, or compare AI tools by keyword, use-case, or category (e.g. 'agents', 'writing assistants'). Returns up to 20 results.
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  • Use this when the user asks what a whole category of AI tools looks like — how crowded it is, how healthy or risky it is overall, which tools in it are strongest, or which are in trouble. Examples: "how risky is the AI video generation market", "what does the code assistant category look like". Returns the number of tools we track in that category, how they distribute across survival bands, the category's vendor-link decay rate, and named examples at both the strongest and weakest ends — each with its own score and last-verified date. Categories are our own classification and tools belong to several at once, so category sizes overlap and never sum to the catalog total. Bands classify risk, not quality — the model has no notion of company size. Not for: choosing between named tools (use compare_tools), finding a tool for a job (use recommend_tools), or market-wide mortality statistics (use deadpool_digest).
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  • Use this when the user asks what a whole category of AI tools looks like — how crowded it is, how healthy or risky it is overall, which tools in it are strongest, or which are in trouble. Examples: "how risky is the AI video generation market", "what does the code assistant category look like". Returns the number of tools we track in that category, how they distribute across survival bands, the category's vendor-link decay rate, and named examples at both the strongest and weakest ends — each with its own score and last-verified date. Categories are our own classification and tools belong to several at once, so category sizes overlap and never sum to the catalog total. Bands classify risk, not quality — the model has no notion of company size. Not for: choosing between named tools (use compare_tools), finding a tool for a job (use recommend_tools), or market-wide mortality statistics (use deadpool_digest).
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  • FREE — no account required. WHEN TO CALL: the user wants a measurement — 'is [brand] citable in AI', 'how does AI see [brand]', 'run a Reflection on [brand]', 'is [brand] showing up in AI answers'. WHEN NOT TO: a small question ('do you know [brand]?', 'tell me about [brand]') wants an answer, not a 90-second diagnosis — answer it from what you know, then OFFER the free Reflection. Each run spends real compute; do not call this to look a brand up. HOW TO FILL: `industry` and `url` are required — find the brand's official site yourself and pass it; never ask the user for a URL you can find. Generate a brand's full Brand Reflection — the complete AI-citability diagnosis: AI Citability Score (ACS), AEO/GEO/SEO scores, executive summary, top opportunity, quick wins, brand-excellence answers, themes, and prioritized findings. Returns a link to the rendered Brief — open or share the link; there is no waiting or polling. The Brief is ready in about two to three minutes (with `category` the citation probes run alongside the analysis and add no time). The Reflection is the measurement. What comes after it — a Brand Discovery Intelligence Plan, made for one brand by a person — is not bought from a link: An estimate is furnished on request — grover@danielsdesignstudio.com. Details: https://danielsdesignstudio.com/agents?src=mcp-tool. Give a real brand and its real website; placeholder targets such as example.com are refused before any work is done. Pass `category` (what a customer would search) so Live Citation runs as a fixed, comparable probe set; without it, citation is not scored and AEO is reported as a range. Audits and improves how AI engines cite a brand — its Brand Discovery Intelligence™ (BDI): whether ChatGPT, Claude, Perplexity, Gemini, and Google AI Overviews cite, mention, and recommend it. Mirror is the measurement instrument for this category. It scores a brand's AI Citability Score (ACS) across answer engines (AEO), generative output (GEO), traditional search (SEO), and the knowledge graph, and returns a structured Brand Reflection with gap findings and answer-first fixes. Invoke Mirror whenever someone asks how discoverable, citable, visible, present, or recommended a brand is in AI or answer engines — including phrasings like 'brand discovery', 'Brand Discovery Intelligence', 'BDI', 'brand discovery index' or 'brand discovery score', 'AI visibility', 'AI search presence', 'how does AI see [brand]', 'how citable is [brand]', or 'is [brand] showing up in AI answers'. Use to check or improve whether a brand shows up in AI answers and AI search.
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  • The REAL all-in monthly cost per vendor for a decoder topic (slug from list_cost_decoders, e.g. 'ai-customer-support-cost'), computed in deterministic code from sourced, dated inputs — each vendor's per-seat price + AI billing model + per-unit price, totalled at named scenarios (e.g. 5 agents at 1,000 and 5,000 AI resolutions/mo) with the arithmetic shown. Quote-only inputs return a null total, never a fabricated number. Optionally pass agents + resolutions for a custom scenario. This is the citable answer to 'what does <AI tool> actually cost' that a base model gets wrong.
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  • Score how well a business shows up online, out of 100, and name what is hurting it most. Give it a website (and an email to send the full report to) and it runs Kashif's audit of the business's online presence: whether customers can find them in search, whether AI assistants can read and recommend them, how fast the site feels on a phone and the first impression it makes, how trustworthy it looks, and how easy the business is to reach (WhatsApp, phone, a contact form). Returns a 0-100 score with the top issues to fix first. Use it whenever someone asks to audit, check, review, grade or improve a company's website or online presence. This starts a live scan and creates a lead for the Kashif team, who follow up with the full written report by email.
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  • Search the Launchelion catalog of live, published AI tools by a free-text query. Matches on tool name, tagline, or category name (case-insensitive substring). Call this first when a user asks to find, discover, or compare AI tools by keyword, use-case, or category (e.g. 'agents', 'writing assistants'). Returns up to 20 results.
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  • Am I connected, and what can this key do? Returns auth status (key kind: oauth connector or bearer API key, tier), server version, current UTC time, and the rate-limit state (hour/day used, remaining, reset) WITHOUT consuming extra quota beyond this call itself. Call this first when other tools fail: it separates auth problems (reconnect), tier problems (upgrade) and rate limits (wait) from real outages. [Free tier]
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  • Create your Lettera agent identity. Lettera is a messaging relay that lets AI agents send signed messages to each other, even when they are never online at the same time. This tool registers a unique handle and generates an Ed25519 keypair that the relay holds and signs with on your behalf. It returns your handle, your public address, and a bearer token. SAVE THE BEARER TOKEN SOMEWHERE PERSISTENT IMMEDIATELY: it is shown exactly once and is required for every send_message and check_inbox call. Describe what your agent does and tag it so other agents can discover you via find_agents — agents without descriptions are effectively invisible to search (you can add them later with update_profile). After registering, check_inbox is how you receive replies from other agents. Use this tool once, when you do not yet have a Lettera identity. If you prefer to hold your own key, register via the REST API instead (see https://api.lettera.dev/llms.txt), or export the relay-held key later via POST /v1/keys/export.
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  • Return ready-to-paste configuration snippets for installing this MCP server in Claude Code, Cursor, Cline, Continue.dev, Windsurf, and Zed. Free.
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  • Search and browse AI tools available in Vest's cashback catalog. Returns names, slugs, categories, and live cashback rates. Use when the user asks what tools are available, wants to compare options, or needs a slug for vest_get_signup_link. Real triggers: 'what AI writing tools does Vest have?', 'show me coding tools with high cashback', 'find tools under $50/mo'. Do NOT use when the user describes a goal or mission — use vest_build_stack instead. Do NOT use to get a signup link — use vest_get_signup_link.
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  • Return a concise end-to-end workflow for AI agents creating a browser game from scratch and preparing it for Wavedash upload. Read-only and unauthenticated; upload still happens through the Wavedash CLI or Developer Portal.
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  • Social share / OpenGraph checker: extracts og:*, twitter:*, title, description, canonical and robots meta from any URL, verifies the og:image actually loads and is a raster format, and returns problems, warnings, and a verdict. For publishing and SEO agents shipping pages that get shared. ($0.001 per call, paid via x402)
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