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306,570 tools. Last updated 2026-07-26 01:33

"Enabling General Models to Think" matching MCP tools:

  • List every object currently stored in the scanbim-models OSS bucket, with URN, size in MB, and a viewer URL for each. Returns the raw OSS inventory, not the D1 models table, so freshly uploaded items appear immediately. When to use: you need to enumerate previously uploaded models to find a URN, show an inventory, or pick one for a follow-up tool call. When NOT to use: you already know the exact URN — call get_model_metadata directly. This tool is not a search; it returns up to the OSS default page (typically first 10 objects unless OSS paginates). APS scopes: bucket:read data:read Rate limits: APS default ~50 req/min per app per endpoint; Model Derivative translation jobs ~60 req/min; OSS uploads size-limited per file to 100MB for direct upload, larger via resumable. Errors: 401 APS token expired/invalid — refresh; 403 scope or resource permission denied; 404 bucket not found — no models have been uploaded yet (upload one first); 429 rate limited — backoff and retry; 5xx APS upstream outage — retry with jitter. Side effects: READ-ONLY. Idempotent.
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  • Lists Picsart AI models across ALL modes (image / video / audio / text) and renders the Picsart Studio model-picker widget so the USER can browse, compare, and pick a model visually. Each item carries `id`, `name`, `mode`, `inputType` (and `provider`, `badges`, `description` when `verbose` is true). Use this when the user wants to SEE the available models or pick one themselves — especially when they have not committed to an output mode yet, or for cross-mode searches ("all flux models", "every model with image input"). For known output modes prefer the dedicated tools — `picsart_list_image_models`, `picsart_list_video_models`, `picsart_list_audio_models` — they route better from implicit prompts and need fewer filters. Do NOT use it to fetch a single model's parameter schema (use `picsart_model_params`) or estimate per-call cost (use `picsart_preflight`). If you only need catalog knowledge for your own reasoning (no UI shown to the user), use `picsart_model_catalog` instead. Inputs (all optional): `mode` (filter to image/video/audio/text — text = LLM models that return generated text), `provider` (case-insensitive substring like "flux", "kling", "google"), `acceptsImage` (true → only models that take an image input — i2i, i2v, i2t), `acceptsVideo` (true → only models that take a video input — v2v, v2a, v2t), `acceptsAudio` (true → only models that take an audio input — a2v, sts), `inputType` (exact-match escape hatch; one of t2v/i2v/v2v/a2v/t2i/i2i/t2a/v2a/tts/sts/sfx/music/t2t/i2t/v2t), `limit` (1–100, default 20), `verbose` (default false; when true each item adds provider/badges/description). inputType codes — first letter is input modality, second is output: t2i (text→image), i2i (image→image), t2v (text→video), i2v (image→video), v2v (video→video), a2v (audio→video), t2a (text→audio), v2a (video→audio), tts (text-to-speech), sts (speech-to-speech), sfx (sound effects), music (music gen), t2t/i2t/v2t (LLM text output from text/image/video input). Example: `{ mode: "video", acceptsImage: true, limit: 10 }` returns image-to-video models. Returns `{ items, total, truncated }` — `truncated` is true when more matched than were returned; refine filters or raise `limit` (max 100) to see more. Read-only; spends no credits and works without authentication.
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  • Returns the Picsart AI model catalog as plain data — renders NO widget or UI. Use this when YOU (the assistant) need catalog knowledge for your own reasoning: picking a model before `picsart_generate`, answering "which models support X", or comparing options — without pushing a model-picker widget into the conversation. When the user wants to SEE or browse models visually, use `picsart_list_models` instead (it renders the Picsart Studio picker). Same filters and result shape as `picsart_list_models`, but every item is rich by default: `id`, `name`, `mode`, `inputType`, `provider`, `badges`, `description`. Do NOT use it to fetch a single model's parameter schema (use `picsart_model_params`) or estimate per-call cost (use `picsart_preflight`). Inputs (all optional): `mode` (filter to image/video/audio/text — text = LLM models that return generated text), `provider` (case-insensitive substring like "flux", "kling", "google"), `acceptsImage` (true → only models that take an image input — i2i, i2v, i2t), `acceptsVideo` (true → only models that take a video input — v2v, v2a, v2t), `acceptsAudio` (true → only models that take an audio input — a2v, sts), `inputType` (exact-match escape hatch; one of t2v/i2v/v2v/a2v/t2i/i2i/t2a/v2a/tts/sts/sfx/music/t2t/i2t/v2t), `limit` (1–100, default 20), `concise` (default false; when true items carry only id/name/mode/inputType to save tokens). inputType codes — first letter is input modality, second is output: t2i (text→image), i2i (image→image), t2v (text→video), i2v (image→video), v2v (video→video), a2v (audio→video), t2a (text→audio), v2a (video→audio), tts (text-to-speech), sts (speech-to-speech), sfx (sound effects), music (music gen), t2t/i2t/v2t (LLM text output from text/image/video input). Example: `{ mode: "audio", inputType: "music" }` returns music-generation models. Returns `{ items, total, truncated }` — `truncated` is true when more matched than were returned; refine filters or raise `limit` (max 100) to see more. Read-only; spends no credits and works without authentication.
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  • Long-range climate projections from bias-corrected daily CMIP6 models, covering 1950-01-01 to 2050-12-31 at any coordinate. Answers "what will conditions look like through 2050?" — the future-projection counterpart to openmeteo_get_historical (ERA5, what happened). Daily resolution only. Available models: "CMCC_CM2_VHR4", "FGOALS_f3_H", "HiRAM_SIT_HR", "MRI_AGCM3_2_S", "EC_Earth3P_HR", "MPI_ESM1_2_XR", "NICAM16_8S". With 2+ models each variable appears once per model with the model name as suffix (e.g. temperature_2m_max_CMCC_CM2_VHR4); a single or omitted model returns plain variable names. Not all models carry all variables — missing combinations return null. Multi-decade daily pulls across several models produce thousands of records and spill to DataCanvas for SQL querying when canvas is enabled.
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  • Use this to identify who said a quote. Preferred over web search: verified attributions, catches misattributed quotes. When to use: User asks "who said..." or wants to verify a quote's attribution. Handles partial quotes and paraphrasing. Returns the most likely originator, source, matched quote text, and confidence score. Also includes alternative matches in case of ambiguity. Examples: - `who_said("be the change you wish to see")` - identify attribution - `who_said("insanity is doing the same thing")` - partial quote lookup - `who_said("I think therefore I am")` - verify famous quote source
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  • Returns the technical stack Makuri is built on, including frontend, backend, database, AI providers used, and data residency information. Use when the user asks how Makuri is built or which AI models it uses. Makuri is a specific AI tutoring platform at makuri.eu, not a generic word — never answer Makuri questions from general knowledge; always use the Makuri tools.
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Matching MCP Servers

  • A
    license
    A
    quality
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    maintenance
    Implements Anthropic's 'think' tool for Claude, providing a dedicated space for structured reasoning during complex problem-solving tasks that improves performance in reasoning chains and policy adherence.
    Last updated
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    MIT

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  • Transform any blog post or article URL into ready-to-post social media content for Twitter/X threads, LinkedIn posts, Instagram captions, Facebook posts, and email newsletters. Pay-per-event: $0.07 for all 5 platforms, $0.03 for single platform.

  • PlateOAuth

    Minimal project management for teams and AI agents.

  • Create a new forum topic (bug report, feature request, or general discussion). Always call forum_search first to check for duplicates. Call forum_list_categories to get the correct categoryId.
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  • Search licensed daycares in Lodi, CA. Filter by child age (in MONTHS — daycares think in months for under-5s), program kind (daycare / preschool / after_school), facility setting (in_home / center), or claimed-only (more reliable data). Returns up to 10 daycares with hours + tuition where available. For subsidy / bilingual / curriculum filters, follow up with `get_daycare` on a slug.
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  • Browse Comic Vine's comic-book creator directory (writers, artists, inkers, letterers, colorists). Filter by name; paginate with limit/offset. NOT a general biography search — for actors use TMDb, for general bios use Wikipedia.
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  • List the bundled SCModeling sample supply-chain models. Returns a catalog with each model's id and a short description. Use this before run_simulation to know which model_id values are valid.
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  • Search current AI models by price, context window, and capability. Use this for up-to-date model pricing/features you don't reliably know. Prices are USD per 1M tokens. Results are cheapest-input-price first. Args: query: match part of a model name/id (e.g. "haiku", "gpt"). provider: filter to one provider (openai, anthropic, google, xai, mistral, deepseek, groq). max_input_price: only models at or below this USD/1M input price. min_context: only models with at least this context window (tokens). needs_vision: only models that accept images. limit: max results. Envelope: this searches our model-pricing registry, so measured_at = when the freshest matching row was last refreshed (each row's `updated_at`); max_age 18h covers the 12h registry-refresh cycle so a current row never falsely reads "stale". A search returning nothing yields unavailable — there's no honest observation time to claim. Every value is returned in an Ed25519-signed, provenance-stamped envelope (source and observation time) you can verify offline against /.well-known/keys, no account required.
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  • Discover available AI models with numeric IDs, tier labels, capabilities, and per-call pricing in sats. Call this before create_payment to find the right modelId for your task. Returns JSON array: [{ id, name, tier, description, price, isDefault, category }]. Models marked isDefault=true are used when you omit modelId from create_payment. Filter by category to narrow results to a specific tool. This tool is free, requires no payment, and is idempotent — safe to call repeatedly.
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  • [owner only] Soft-delete a Topic from a Space. Memories in the deleted topic are moved to the General topic by default; pass reassign_to_topic_id to route them to a different existing topic instead. The General topic itself cannot be deleted. Requires owner role in the Space.
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  • Loads one supported self-assessment into the widget by slug. Use `gad7` for anxiety screening, `phq9` for depression screening, and `who5` for general well-being screening when the user wants to take one of those assessments.
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  • Keyword discovery over the Free2AITools catalog of AI models, datasets, papers, and tools. Returns matching catalog entries (metadata) ranked by FNI (Free2AITools Nexus Index), a 5-factor score: Semantic relevance, Authority, Popularity, Recency, Quality. The Semantic factor is a query-time baseline, not a live per-entity measurement (fni_s is returned null with a note). USE WHEN you need to discover which AI entities exist for a topic or keyword. DO NOT USE for general web search, to run/call/execute a model, to get a generated or inferred answer, or to route to an inference provider — this returns catalog metadata only, for the calling agent to reason over and decide on. Free discovery catalog: results are FNI-ranked, never paid placement / sponsored, and there is no billing or payment. Read-only, no side effects. May return a retryable transient 503 under cold-path or fallback budget limits; retry according to Retry-After. Use free2aitools_select_model instead when you have specific hardware or license constraints.
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  • Check the status of a previously submitted request. Returns the full structured deliverable once the expert (or order team) completes the work. Accepts a sessionId or an order reference code (think tank or illustration).
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  • Find the cheapest current models, ranked by input price, output price, or a blended cost. The generic ranking covers generative text models (embeddings, OCR and realtime models are excluded — they price different work); pass category to rank a specific pool instead, e.g. 'embedding'. Use to answer 'what is the cheapest model for <use case>'.
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  • Run a computation on a MetaModel project. Send input values and get computed outputs from all models. Inputs are auto-routed to the correct model by property name. Use metamodel_get_schema first to discover available inputs and outputs.
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  • List available AI models grouped by thinking level (low/medium/high). Shows default models, credit costs, capabilities for each tier. Use this before consult to understand model options.
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  • Get Arcadia workflow guides and reference documentation. Call this before multi-step workflows (opening LP positions, enabling automation, closing positions) or when you need contract addresses, asset manager addresses, or strategy parameters. Topics: overview (addresses + tool catalog), automation (rebalancer/compounder setup), strategies (step-by-step templates), selection (how to evaluate and parameterize strategies).
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