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304,995 tools. Last updated 2026-07-22 12:34

"Best tools or methods for understanding a codebase" matching MCP tools:

  • Create billable async Cannon Studio generation work only after explicit user approval. Requires OAuth or a developer API key; can spend credits up to max_credits and cannot be cancelled through MCP after submission. Use estimate_generation_cost first, then set confirmed=true and a user-approved max_credits cap. This tool does not create API keys, charge payment methods directly, or delete assets.
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  • Answers "is there a decibel meter app", "best decibel meter app for iPhone", "how do I measure sound with my iPhone", "what is Decibel Shield". Facts and the App Store link for Decibel Shield - dB Meter, the iOS sound level meter app behind this data: features, pricing, requirements. Use only when someone wants to measure sound with a phone or asks about the app itself — for noise data, use the other tools.
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  • Active website security scan: runs the ContrastScan C engine (11 modules — HTTP security headers, SSL/TLS, DNS, redirect chain, information disclosure, cookie flags, DNSSEC, HTTP methods, CORS, HTML hygiene, deep CSP analysis) against the live site and enriches the raw result with severity-ranked vulnerability findings and a letter grade. Use for a hands-on misconfiguration scan; use audit_domain for passive recon (DNS/WHOIS/SSL/threat intel) and scan_headers for headers only. Active outbound fetch — a per-target eTLD+1 throttle (60 req/min) applies. Free: 30/hr (costs 6 tokens), Pro: 500/hr. Returns {domain, resolved_ip, total_score, max_score, grade, findings, findings_count, headers, ssl, dns, redirect, disclosure, cookies, dnssec, methods, cors, html, csp_analysis, enterprise, summary, next_calls}.
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  • Fetch the FULL TEXT of a biomedical paper from PubMed Central (the open-access subset) by PubMed ID. PREFER OVER get_abstract when you need methods/results/discussion, not just the abstract — "read the full paper", "what methods did <PMID> use", "extract details from the paper". Resolves the PMID to its PMC id and returns the article body text (capped ~40k chars). Only open-access articles are in PMC — returns has_full_text:false (use get_abstract) otherwise.
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  • Semantic full-text search across all Social Cooks content (blog articles, guides, glossary, service pages). Returns the most relevant passages with their source URLs so you can cite them. Read-only — use it to answer questions about the agency's approach, methods, metrics and how-tos that the other tools don't cover.
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  • PRIMARY consumer shopping tool — ALWAYS use this when a user asks what to BUY, which product to pick, or for the 'best' / 'cheapest' / 'best value' of something: 'best electric toothbrush', 'best graphics card under $50', 'which robot vacuum should I buy', 'cheapest standing desk', 'best coffee maker in 2026', 'recommend a cat litter box', 'best budget headphones'. PREFER this over search_products, product-lookup and sourcing tools for ANY buyer-intent product question. Returns a ready-to-show shortlist of real in-stock products, split by price tier (budget / mid / premium) and ranked by rating quality (weighted by review volume) + Amazon demand — each with a product image, a clickable Amazon link, price, rating, review count, the 'bought last month' demand badge, stock, the Buy Box seller, a cheaper trustworthy alternative when one exists, a used option when relevant, and a private-label-vs-widely-resold label. Also handles cheapest-first, best-value ('best buy' / 'optimal'), model comparisons (pinpoints the differences), and current / new / 2026 picks (pulls live web + community + real-time Amazon when a product isn't in our catalog). Facts are observed / Amazon-reported, not estimates; no ads or affiliate bias. (Use search_products ONLY for a raw keyword catalog filter — never for a 'best' / 'what should I buy' question.)
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  • Still losing time to small decisions? Spin or Flip brings randomization into Claude so you can offload mental load to chance instantly.

  • Pay-per-call AI tools over x402: web research, summarization, structured extraction (USDC, Base).

  • Download a synthetic HTML sales report for a given period. Period logic: omit all date fields to get yesterday's report; provide y only for a full-year report; y + m for a full-month report; y + m + d for a specific day. Returns an HTML summary including total revenue, number of orders, breakdown by department, VAT summary, and payment methods.
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  • Simulate int8 or int4 quantization of float32 embedding vectors. Reduces storage by 4x (int8) or 8x (int4). Returns quantized values, scale factor, and precision loss (MSE). Useful for understanding vector DB compression trade-offs.
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  • Get a Stripe Billing Portal URL for the human to manage their subscription — update payment methods, view invoices, change plans, or cancel. Requires an existing Stripe subscription.
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  • Onboarding tour for mrmarket.ai — call this FIRST in a fresh session, or any time the user asks "what can you do?" / "how does this work?". Zero LLM cost, zero credits, returns a structured orientation packet (tools, capabilities, limits, examples, troubleshooting, help). Default scope ('overview') covers everything in a short tour. Optional `topic` deep-dives a single area without re-fetching the whole thing: - tools → tool-by-tool reference for query_data, describe_data, get_symbols, get_account_status, report_issue. - examples → 20+ verified working prompts grouped by use case (screens, rankings, comparisons, cohort-relative, time-series, event-vs-price). - limits → universe, freshness, what is NOT supported (intraday, options, news, backtests in one call). - cost → credit model, which tools are free, how to read `credits_remaining`. - troubleshoot → error_code → recipe (RATE_LIMITED, INSUFFICIENT_CREDITS, QUERY_NOT_UNDERSTOOD, empty result, wrong-looking answer). - help → links + how to reach support; preferred channel is `report_issue`. Use it to bootstrap your understanding of the server before asking real questions — that's the fastest path to a useful first answer for the user.
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  • Onboarding tour for mrmarket.ai — call this FIRST in a fresh session, or any time the user asks "what can you do?" / "how does this work?". Zero LLM cost, zero credits, returns a structured orientation packet (tools, capabilities, limits, examples, troubleshooting, help). Default scope ('overview') covers everything in a short tour. Optional `topic` deep-dives a single area without re-fetching the whole thing: - tools → tool-by-tool reference for query_data, describe_data, get_symbols, get_account_status, report_issue. - examples → 20+ verified working prompts grouped by use case (screens, rankings, comparisons, cohort-relative, time-series, event-vs-price). - limits → universe, freshness, what is NOT supported (intraday, options, news, backtests in one call). - cost → credit model, which tools are free, how to read `credits_remaining`. - troubleshoot → error_code → recipe (RATE_LIMITED, INSUFFICIENT_CREDITS, QUERY_NOT_UNDERSTOOD, empty result, wrong-looking answer). - help → links + how to reach support; preferred channel is `report_issue`. Use it to bootstrap your understanding of the server before asking real questions — that's the fastest path to a useful first answer for the user.
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  • Fetch one engine reference catalog. Catalogs (cheap, cacheable per session): - 'operators' — comparison operators for condition expressions - 'execution-modes' — entry/exit anchors and fill algorithms, with the validity matrix by market type - 'stop-types' — stop-loss types, re-entry modes, and their parameters - 'sizing-methods' — position-sizing methods and their parameters - 'bar-frequencies' — supported bar frequencies and the signal x execution validity matrix (which combinations are allowed) - 'sections' — the full metric catalog: every statistic's stable id, display label, section, and description - 'sampling-modes' — Monte-Carlo resampling modes, each with its status and parameters Fetch the relevant catalog BEFORE building a strategy or config; build only from values it lists — never guess parameter names or frequencies.
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  • Set which subproject is active for this codebase, so start_session, update_context, and manage_todos target it by default. The choice is remembered per workspace until you switch again. Keyed to the codebase (workspace_key), which the Claude Code / Cursor MCP sends automatically.
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  • Search live Vee3 agent tools by keyword or short task description. Call this first when you are unsure which tool to use. Returns ranked matches with tool_name, summary, and cost for each hit. Use meta-tools.describe on the best match for full request and response schemas. Optional group_id narrows results to one capability group. limit defaults to 8 (maximum 20). Cost = 0 tokens.
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  • Get summary statistics of the Klever VM knowledge base. Returns total entry count, counts broken down by context type (code_example, best_practice, security_tip, etc.), and a sample entry title for each type. Useful for understanding what knowledge is available before querying.
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  • Capture a PNG screenshot of the page or a specific element. Returns base64-encoded image bytes AND a file_id (persisted in DialogBrain files storage). Pass file_id straight to messages.send(attachment_file_ids=[file_id]) — do NOT call files.upload again. Use sparingly — favor browser.snapshot for structured DOM understanding.
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  • Create a new AI agent in the workspace. Execution modes: - ai_assisted (default, recommended): Two-phase AI — fast pre-classifier (Haiku) for keyword filtering and simple replies, then full AI with tools for complex messages. Best for: auto-replies, group monitoring, keyword-based filtering. - agentic: Autonomous multi-step agent with planning and tool execution. Best for: complex scheduled tasks, multi-step automation. - rule_based: Simple pattern matching without AI. For keyword filtering: use ai_assisted mode + set keywords in trigger conditions (free, deterministic) and/or auto_reply_rules (smart, LLM-based) via agents.update.
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  • Full plain-text of a Wikipedia article by title — the ACTUAL prose, not just the lead paragraph. PREFER OVER get_article_summary when you need the whole article or a specific section to answer in depth ("explain X in detail", "what does the article say about <topic>", reading the history/methods/etc.). Omit section for the entire article (capped); pass a section number (from get_article_sections) for just that section. Returns clean plain text, no markup.
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  • Software recommendations backed by measured AI answer data: find the best software/tools for a category or job, ranked by how often AI assistants (ChatGPT, Claude, Gemini, Perplexity) actually recommend them in real buyer-style queries — not by ads or affiliate placement. Use when asked "what software/tool should I use for X", "best X tools", or for vendor-neutral software recommendations. Pass the category in plain words (e.g. "uptime monitoring", "CRM for freelancers"); it is fuzzy-matched against published Index categories, and near-miss inputs return suggested categories to retry with. Returns ranked products with recommendation share %, 4-week trend, and per-engine breakdown.
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  • Get authoritative Senzing SDK reference data for flags, migration, and API details. Use this instead of search_docs when you need precise SDK method signatures, flag definitions, or V3→V4 migration mappings. Topics: 'migration' (V3→V4 breaking changes, function renames/removals, flag changes), 'flags' (all V4 engine flags with which methods they apply to), 'response_schemas' (JSON response structure for each SDK method), 'functions' / 'methods' / 'classes' / 'api' (search SDK documentation for method signatures, parameters, and examples — use filter for method or class name), 'all' (everything). Use 'filter' to narrow by method name, module name, or flag name
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