AI Prompt Optimize: Improve your AI prompts for better output.
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753,313 tools. Updated 2026-11-06 20:29
"A server for generating better prompts for medical AI agents" matching MCP tools:
- AI Prompt Optimize: Improve your AI prompts for better output.ConnectorNo auth
- Get the current user's available AI tokens Returns the number of AI tokens available to the authenticated user. These tokens fund EVERY AI feature in SERPmantics — meta, outline, intent, internal-links, EEAT, EEAT competitors, score, AND the AISSistant prompts. The endpoint lives under /aissistant for historical reasons but the balance is shared across all AI features. Do NOT confuse with guide-creation credits (see /api/v1/credits). For a combined view (credits + tokens) prefer /api/v1/credits.ConnectorNo auth
- Check the build status of an EXISTING artifact (from artifact-create). Read-only. Generation is asynchronous, so this is how you find out it finished. Call it with { sessionId, wait: true } and it WAITS for you: the call returns as soon as status is 'ready' or 'failed', or after about 45 seconds still 'generating'. Then, you can call it again. This tool is meant to be called right after artifact-create, before replying to the user, and keep getting called until status is no longer 'generating'. ONLY when you want an instant snapshot, this tool can be called without wait (or false); the idea is to never spin on wait: false. Requires sessionId — the id returned by artifact-create (or the last path segment of an artifact URL like https://app.agentgrid.io/artifacts/<sessionId> or https://dev.animaapp.com/chat/<sessionId>). **Returns:** { success, sessionId, status: 'generating' | 'ready' | 'failed', progress (0–100, while generating), name, artifactUrl (generating/ready only), playgroundUrl (app and knowledge artifacts only, generating/ready only), previewUrl (app, knowledge and markdown artifacts only, generating/ready only), error (when failed), nextStep (when a wait returned still generating) }ConnectorOAuth
- Score how likely Amazon's AI (Rufus, COSMO) is to recommend a listing. Free, deterministic, rule-based check on pasted listing copy (title, bullets, description). Returns a compliance health score, an AI-readability score, and a combined AI Recommendation Readiness Score (compliance * 0.55 + readability * 0.45) with actionable suggestions. Use this as a fast baseline BEFORE generating or editing a listing. Do NOT use it for a full compliance report - use compliance_scan for the deep knowledge-base audit. Free, read-only, no API key required, no credits deducted. Args: text: raw listing title + bullets + description (required). marketplace: marketplace code, US/DE/ES/FR/IT/JP/AE/SA/UK (default US). lang: zh or en (default en). email: optional lead email for a confirmation message and lead capture.ConnectorNo auth
- Return the persisted markers + AI analysis (Summary, KeyFindings, Recommendations, DetailedExplanation) for a specific medical-test the authenticated patient owns. Use after mediora__get_patient_history surfaces a test id the user wants to discuss. Bearer token must be a Mediora patient-scope JWT. Proxies https://api.mediora.ai/api/medical-tests/{id} with the user's token forwarded as Authorization: Bearer.ConnectorNo auth
Matching MCP Servers
- AlicenseAqualityDmaintenanceEnables AI agents to search, watch, summarize, clip, and extract transcripts from YouTube videos, all without needing an API key or leaving the chat.927 npm61Apache 2.0
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Matching MCP Connectors
Message board where AI agents ask and answer each other. Sign the guestbook in one call.
- Ethics for AI MCPOAuth
A deterministic daily ethics feed for AI agents, from a four-module curriculum.
- Start generating hero image variants for an idea's ad. Runs in the background. Args: - ideaId (string) - prompt (string, optional): defaults to the idea's saved image prompt Returns: { job: { id, status, prompt, variantCount, results }, note }. Poll idealaunch_get_image_job until status is 'succeeded', then choose one with idealaunch_apply_hero_image. Consumes one of the idea's AI generation turns. Costs no Ad Run credit.ConnectorOAuth
- Estimate the water (mL) and energy (Wh) used by chat-style AI prompts (ChatGPT, Claude, Gemini etc.). queries_per_day: prompts per day. usage: 'simple' (text chat, ~0.34 Wh/prompt), 'mixed' (~1 Wh), 'intensive' (image generation / deep reasoning, ~3 Wh). boundary: 'onsite' (data-centre cooling only, as vendors report) or 'comprehensive' (adds water used to generate the electricity – the wider boundary most researchers use). days: number of days to total over (e.g. 250 workdays, 365). Returns per-prompt, per-day and total figures with everyday equivalents, assumptions and a source link. For agentic/coding sessions use estimate_session_footprint instead.ConnectorNo auth
- Estimate the water (mL) and energy (Wh) used by chat-style AI prompts (ChatGPT, Claude, Gemini etc.). queries_per_day: prompts per day. usage: 'simple' (text chat, ~0.34 Wh/prompt), 'mixed' (~1 Wh), 'intensive' (image generation / deep reasoning, ~3 Wh). boundary: 'onsite' (data-centre cooling only, as vendors report) or 'comprehensive' (adds water used to generate the electricity – the wider boundary most researchers use). days: number of days to total over (e.g. 250 workdays, 365). Returns per-prompt, per-day and total figures with everyday equivalents, assumptions and a source link. For agentic/coding sessions use estimate_session_footprint instead.ConnectorNo auth
- AI drafts of a project's tracked prompts in another market's language, the first step of adding a market: each prompt rephrased the way people in the new market ask it, with brand and product names kept as written. Read-only: nothing is saved; the drafts are meant for review, and the final texts go to add_market as `prompts`. It spends AI (one or two model calls on the workspace's own key or Managed AI) and counts toward the workspace's 20 assistant-started scans, briefs and suggestions a day.ConnectorOAuth
- Check whether AI agents can read, understand and act on any website (bots allowed, readable pages, product data, checkout, help). Reads up to 3 public pages; results are kept for 24 hours and public at requstory.com/ai-readiness/<domain>/. Faster and narrower than map_website. If status is "queued" or "running", call again with start=false.ConnectorNo auth
- Delete ONE AI package resource of a video in one language (eBook, mind map or quiz) — cannot be undone: its content, PDF, images and the published file are removed, also for legacy resources. Same as the dashboard's Remove. Refused while it is still generating (checked before deleting; if that check fails nothing is deleted). Other languages and resources stay. To remove a failed generation card use panda_delete_ai_workflow.ConnectorDestructiveNo auth
- Answers "are we showing up in AI search for X" from the visibility results Hi, Moose has stored for a project: the prompts the brand tracks, run on AI engines (ChatGPT, Perplexity, Gemini and others) and scored for brand mention and citation. Pass the user's question or topic in their own words; Hi, Moose matches it to the tracked prompts, in any language. Returns, per engine, whether the brand was mentioned or cited in the latest run and in an earlier run so the change is visible, the mention and citation rates over the window, a short excerpt from the latest answer where the brand appeared, the prompts matched, and other brands seen in those answers. Each excerpt carries an answer id; call visibility_get_answer with it when the user wants the full text of that answer. Results cover the tracked prompts on the tracked engines only, never the whole of AI search; state the window and sample size plainly and never claim causation. When no tracked prompt matches, the result lists the topics the project tracks; tell the user and suggest adding a prompt on the Visibility screen in Hi, Moose. Reads stored results only, it does not run new checks. Takes a few seconds.ConnectorOAuth
- Returns written insights about how the reader's reading has been changing: genres they are exploring, authors they return to, their pace, and how their themes are shifting. When none are current, ReadingRate generates them first: it sends the reader's past year of finished books (titles, authors, genres, themes, ratings and dates) to its AI provider, stores the new insights in the reader's account for seven days in place of the earlier ones, and counts the generation against the reader's ReadingRate AI usage. Generating takes several seconds and happens at most once a day. Use when the reader asks about their reading patterns, trends or trajectory. For numbers such as pace and genres, use get_reading_stats.ConnectorDestructiveNo auth
- Edit the DISPLAY metadata of YOUR OWN PUBLISHED agent — title, tagline, description, example output, category (+ subcategories), tags, and the Tech Domain / Language facets (software agents). Pass the agent slug + only the fields you want to change. This does NOT change what the agent can DO: its tools/actions/credentials/prompts are unchanged (those re-version through your agent's own flow + admin review — findagent_bump_version for an agent built here, findagent_repull for an agent built from a code or skills repo, findagent_reintrospect_mcp for an external MCP listing), so a metadata edit goes live immediately without re-review. Owner-only. Existing buyers are unaffected. Use findagent_list_categories for valid category slugs.ConnectorOAuth
- What AI engines answer for a prompt, with the brands they mention and the sources they cite. Slow: returns a task_id, then read the result with get_task. Use when: "does ChatGPT recommend us for X", "who do AI engines cite for X", an AI visibility baseline for a brand across engines. Not for: which prompts people ask, use aeo_search_prompts. Google's ten blue links, use seo_get_serp (ai_overview: true adds the overview to it at 1 credit). Whether a site is ready for AI crawlers, use aeo_get_site_readiness. Returns: Task. task_id now; get_task returns rows[] per prompt and engine (answer, mentions[] (brand, mentioned, position, cited), citations[] (position, url, domain, title), search_results[] (pages retrieved, cited or not), search_queries[] (the web searches the engine ran), named_brands[] (brands ChatGPT tagged in the answer, not only yours)) and errors[] for cells that failed. answer null = the engine showed no AI answer. search_results[] and named_brands[] are filled for chatgpt only, search_queries[] for chatgpt and claude. named_brands[] drops a tag ChatGPT gives as a description instead of the brand, so it can miss brands; read the answer for a full list. chatgpt and gemini are what their apps show a person, model chosen by the app; claude and perplexity come from their model APIs. Answers are live and non-deterministic; results are kept 30 days and never cached. Cost: per prompt, 15 credits for claude, 6 for perplexity, 2 each for chatgpt, gemini, ai_overview and ai_mode. Default 1 prompt on the five default engines = 27 credits. A cell that fails is not charged. Example: {"prompts": ["best crm for startups"], "brands": ["HubSpot", "pipedrive.com"]}ConnectorAPI key
- Prompts people ask an AI engine (ChatGPT or Google AI Overview) about a topic or brand, from the provider's index of observed answers. Not keywords. Use when: "what do people ask ChatGPT about X", "which prompts mention our brand", building an AI visibility baseline. Not for: Google keywords and volumes, use seo_search_keywords. What the AI engines answer right now, use aeo_run_ai_answers. Returns: List. rows[]: prompt, ai_search_volume (a People Also Ask proxy, not query logs), engines[], mentions_brand (a domain input is cited, a keyword input appears in the answer), cited_domains[], retrieved_domains[] (read while answering but not cited), search_queries[] (the web searches the engine ran), named_brands[], answer_preview, first_seen, last_seen. Give exactly one of keyword or domain. Cost: 31 + 31 per 100 rows. Default 50 rows = 47 credits. Cached 7 days. Example: {"domain": "example.com", "limit": 50}ConnectorAPI key
- Ask up to 25 questions of AI answer engines now and measure the brand's and each competitor's share: URL cited among the sources, and brand named. Saved as a citation audit. Billing: 5–12¢ per engine check, per answered prompt × engine — Perplexity 5¢, ChatGPT 7¢, AI Overviews 9¢, Gemini 12¢ (33¢ a prompt on the four defaults), AI Mode 10¢ if asked. Then the fix-it playbook get_fix_plan plans from (playbook: false skips it): at most 12¢ per answered check that didn't cite the brand, plus about 45¢ for a rollup when 2+ questions were lost. E.g. 10 prompts, default engines: 330¢ + about 525¢ playbook if nothing cites the brand. dry_run: true quotes it free. Engines get ~4 min; unfinished checks are skipped unbilled (partial, timed_out): split runs past ~15 prompts. When to call: share of voice across many buyer questions, fresh. One question: check_brand_citation; an audit that already ran: get_audit (free). Returns { audit_id, report_url (public), tracked: [{domain, is_brand, cite_count, share_pct, mention_count, mention_share_pct}], total_cites, total_mentions, sample: {answered_checks, prompts, confidence, note}, suggested_competitor_domains, suggested_sources, completed, total, partial, timed_out, out_of_credits, charged_cents, charged_breakdown_cents }. Relay sample.note (confidence low = few answers). suggested_competitor_domains: untracked hosts winning lost answers (confirm before add_site); suggested_sources: places to earn mentions. Past ~45 s: { audit_id, status: "running" }; read it with get_audit.ConnectorOAuth
- PRO+ AI scheduling tool for agents. Proposes a new schedule for a project that fits all tasks before a target deadline while respecting dependencies. Designed for multi-turn agent workflows: call with mode="preview" to generate and present the proposal to the user, then call with mode="apply" once the user confirms. APPLY captures a "Before AI Schedule Proposal" baseline and commits all proposed dates in one atomic operation (requires project Owner or Manager role). Optionally levels resources to avoid overallocation. Cap: 100 tasks. Feature: aiAdvanced (PRO+).ConnectorDestructiveOAuth
- Suggest new AI-visibility tracking prompts for a project, in two steps. Without count it returns plan — how many prompts to add to this project and why, from its active prompts, engines, runs per prompt and trial allowance — and spends nothing; the user picks the number. With count it drafts that many buyer questions grounded in the brand, its competitors, product type, its own scan data (topics where competitors out-rank it) and, with Search Console connected, real Google queries of the last 90 days (sourceQuery, sourceImpressions). approach method (default) follows the CrunchJunkie prompt method: one open question per buyer intent across the buying stages, naming no brand, each with stage, intent and tags; broad is the older mix with competitor and brand questions. Deduped against the tracked prompts. Read-only: add_tracking_prompt adds chosen ones. Not measured AI prompt volume. It spends AI only when it drafts — with count, or with approach broad (one model call on the workspace's own key or Managed AI), counts toward 20 assistant-started scans, briefs and suggestions per workspace per day, and runs without a preview on a paid plan because it changes nothing.ConnectorOAuth
- Page the project's tracked prompts, the buyer-style questions DevTune asks AI platforms. Each has its id, the exact promptText, topicId and topicName, isActive (the prompt's own switch), topicActive, namesBrand (the prompt text names the project's own brand or one of its brand terms, retired ones included), pack (navigational for a prompt in the navigational pack, which does not count toward the prompt allowance; null otherwise) and, when recorded, disabledReason (manual, plan_limit or quota_exceeded) and disabledAt. Pass a prompt id as promptId to devtune_create_prompt_action, devtune_get_prompt_actions or devtune_list_visibility_response_history. By default only prompts that are on and whose topic is on are listed; includeInactive adds the others. Deleted prompts are never listed. The plan's prompt allowance can still hold back an active prompt; devtune_get_project_usage reports active prompts. Filter by topicId from devtune_list_topics. Ordered by id, default 50 and maximum 100 per page. Pass nextCursor back as cursor with the filters unchanged. This is a live listing, not a snapshot: prompts added or changed while you page can be missed or appear.ConnectorAPI key