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605,003 tools. Updated 2026-09-23 21:57

"An overview of MATLAB software and its features" matching MCP tools:

  • Fetch a disaster record by ReliefWeb numeric ID including description, affected countries, GLIDE number, profile overview, key content links, and active appeals or response plans. Use after reliefweb_search_disasters to retrieve full details. Each curated list also has an archive, which the record leaves out. Two alternative selectors, at most one per call: sections names parts of the record to return, archive pages one list's archived entries in place of the record. Description and profile overview can together run to tens of KB for major disasters. A record over the response budget comes back as a section outline naming every section and its byte size. Nothing is truncated on any path.
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  • Explain how HelloBooks and Munimji (the in-app AI assistant) help a specific business — given a free-text description of the user's own operations. Returns a curated capability knowledge base: business-operation areas (sales, purchases, banking, tax, reports, inventory, payroll, multi-entity, setup), and for each AI capability WHO does the work — `autonomous` (Munimji does it on its own, e.g. OCR extraction, running reports), `approval` (Munimji prepares the entry and you one-click approve before it posts to the ledger, e.g. AI categorization, find-and-match, creating invoices/bills by chat), `assist` (co-pilot, e.g. guided onboarding, voice), or `manual` (a software feature you run yourself). Each capability links to the backing software features. Use this when a user describes their business and asks "how can HelloBooks help me?", "what can the AI do for my shop/practice/agency?", or "what can Munimji do on its own vs what do I approve?". Pass their description in `businessDescription`; optionally filter by `area` or `autonomy`. The AI never posts to a ledger without approval. For the full software catalog call list_features; for pricing call list_plans.
    ConnectorNo auth
  • Explain how HelloBooks and Munimji (the in-app AI assistant) help a specific business — given a free-text description of the user's own operations. Returns a curated capability knowledge base: business-operation areas (sales, purchases, banking, tax, reports, inventory, payroll, multi-entity, setup), and for each AI capability WHO does the work — `autonomous` (Munimji does it on its own, e.g. OCR extraction, running reports), `approval` (Munimji prepares the entry and you one-click approve before it posts to the ledger, e.g. AI categorization, find-and-match, creating invoices/bills by chat), `assist` (co-pilot, e.g. guided onboarding, voice), or `manual` (a software feature you run yourself). Each capability links to the backing software features. Use this when a user describes their business and asks "how can HelloBooks help me?", "what can the AI do for my shop/practice/agency?", or "what can Munimji do on its own vs what do I approve?". Pass their description in `businessDescription`; optionally filter by `area` or `autonomy`. The AI never posts to a ledger without approval. For the full software catalog call list_features; for pricing call list_plans.
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  • Inspect the live search landscape: which SERP features (AI Overview, snippet, PAA, local pack, video) appear for a keyword, plus domain-level top rankings, visibility distribution, and competitor domains. Results are fetched from the live SERP at call time, capped by limit per action. Use for who ranks and why; for keyword demand use keyword_research. Already scoped to the connected workspace and its site; call directly, no domain or site parameter is needed. Cost: bills AI credits per call (live vendor data at actual cost); reads of your own stored data elsewhere are free.
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  • PROJECT-SCOPED: this call acts only on the explicit project_id and returns the project identity with its result. Current EDL JSON and version. Large timelines return a compact index instead of invalid truncated JSON. Request top-level sections such as ['captions','overlays'] and paginate list sections with offset/limit. Natural aliases are accepted without a retry: cuts/segments -> keep, text -> texts, zooms/transitions/grades/fades -> effects, audio -> all audio sections, and program/overview/summary -> the compact program overview. compact=true always returns counts, caption state and duplicate assets.
    ConnectorOAuth
  • Free preview of breaking changes / new releases for a software dependency. Pass an npm/PyPI `package` (resolved and fetched live if not already tracked) or a GitHub `repo` (owner/repo). Returns up to 5 recent changes plus the package's current version. Full history, significance filtering, and the LLM brief are paid via x402.
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Matching MCP Servers

  • A
    license
    Not graded
    quality
    A
    maintenance
    Provides Dev Container Features that install code intelligence (LSP) and repository knowledge search (Orama) MCP servers into any dev container, enabling coding agents to perform go-to-definition, find references, and hybrid search over project files.
    MIT

Matching MCP Connectors

  • Google AI Overview answers and cited sources via the Apify Google AI Overview API, hosted MCP.

  • Library of Congress (loc.gov) MCP — the world's largest library.

  • Feature Leaderboard: place or raise the linked account's ET10 bid on one open feature to move it up the board. The first bid on a feature is at least the minimum from feature_bidding_rules. A bid can be raised, never lowered or withdrawn. A bid is NEVER collected (nothing is charged, locked or paid): the account must hold at least 100,000 ET10, and enough ET10 to cover ALL of its standing bids on open features, or the bid is refused and the reason is returned. Bug reports and shipped or closed features take no bids. A bid does not guarantee a feature is built. Bid only an amount your human approved.
    Connector
    Destructive
    No auth
  • Returns the base ReoGridJsonDocument schema and an index of advanced features. The base schema already covers cell values, formulas, styling, borders and merges — those need no follow-up call. Call get_feature_spec(feature) only for a name listed in the returned features[] array, passing features[].name verbatim.
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  • Start here when building an application. Returns an overview of what the AdCritter platform offers and a catalog of feature guides you can query with the adcritter_guidance tool to learn how to build each part of the app. Call adcritter_guidance(key) for any feature area to get detailed building instructions with API endpoints and response shapes.
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  • Returns a full overview of Fluentive - what it is, who it's for, and its core value proposition. Use when the user asks what Fluentive is, searches for a scheduling or CRM tool, or wants a summary.
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  • Get one integration in full: its configuration, the scopes it was granted, and the result of its last sync. Use it to diagnose an integration that list_integrations shows as unhealthy, or to check which scopes were granted before relying on a capability. Covers a single integration — list_integrations gives the overview. Reads only; it does not re-run a sync or change any setting. Requires an API key. The response describes what the integration is permitted to do, which is not the same as what it has successfully done — read the last sync result for that.
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  • A single provision with its citation, its position in the act, the structural features its text carries, and what it points at. **Cost: 2 credits.** This does not return the provision's text. `GET /acts/{actId}/sections/{n}/body` does, and is priced separately because it reads the act document. `wordCount` is summed across every passage of the provision. `actsReferenced` is whitespace-normalised before deduplication, because the publisher's line breaks otherwise make one cited act look like two.
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  • Get G2 software reviews. Returns ratings, pros, cons, use cases. Args: product: Software product name (e.g. 'Salesforce') max_results: Max reviews (default 20)
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  • Searches across ALL Fluentive content — features, pricing, FAQ, comparisons, and live blog posts — for topics relevant to a query. Use for generic questions like 'does Fluentive support X?', 'is it good for Y type of business?', or 'I need software that does Z'. Returns the top 5 most relevant content excerpts.
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  • Queries municipal indicators from IBGE (similar to Cidades@ portal). Features: - General overview of a municipality (population, HDI, GDP, etc.) - Query specific indicators - Historical indicator data over years - List available surveys and indicators Available indicators: populacao, area, densidade, pib_per_capita, idh, escolarizacao, mortalidade, salario_medio, receitas, despesas Examples: - São Paulo overview: tipo="panorama", municipio="3550308" - Population history: tipo="historico", municipio="3550308", indicador="populacao" - View surveys: tipo="pesquisas" - Available indicators: tipo="indicador" This tool is the panel for a SINGLE municipality (Cidades@). Use a different tool when: - Census themes / historical series → ibge_censo - Comparing multiple municipalities → ibge_comparar - A macro indicator time series → ibge_indicadores Behavior: read-only and idempotent — a live GET against the public IBGE APIs (Cidades@/agregados). Returns Markdown plus a typed structuredContent payload.
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  • Get this workspace's Brand DNA: brand_name, brand_kind, overview, tagline, offer, features, products, audience, palette, logos, plus `checks`: what to fix before rendering (thin Brand DNA, a typed accent the brand's own work does not use). Call right after get_account; fix thin DNA first with update_brand_dna and upload_product_screen, or ask the human for the site. Not Brand Memory.
    ConnectorOAuth
  • Get one software product (Market) One engine of the software library: the same row the list returns (product metadata, host count per observed role, first/last seen, the compliance signal and the host-count trend) plus the catalogue version and generation stamp. `engine` is a catalogue engine slug as published in `engine` on the list; an unknown slug is a 404. Beyond the list row it also returns `advisory_list[]` (issue #798): every live advisory of the engine's lanes with its id, normalized severity, CVSS score, summary, url and publication stamp, newest first. Null when no lane of the engine has an advisory feed; `[]` when it has one and upstream has published nothing. Market tier.
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  • Get Google Ads API reporting view documentation. Without a view name: returns an overview of all ~167 available reporting views (campaign, ad_group, keyword_view, search_term_view, etc.). With a view name: returns the full field schema for that view, including every attribute, segment, and metric with data types, enum values, and whether each field is filterable/selectable/sortable. Args: view: The reporting view name (e.g. "campaign", "ad_group", "search_term_view"). Omit for the overview of all views.
    ConnectorOAuth
  • Suggest Apple-native features for an app based on its description. The domain is only a weak hint; the app description wins. Returns a ranked list of features with recommended surfaces (intent, widget, view, component, store, app), estimated complexity, and a one-line description for each. Use: use before generation to choose Apple surfaces; not a substitute for registry search or validation. Inputs: prompt is the product brief; dir adds project context; Pro mode is used only when configured. Effects: local mode is read-only; Pro mode may call Axint endpoint when credentials are configured.
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  • An end-to-end overview of one management topic: its definition, an in-depth explanation of the discipline, the 3 editor-curated top documents, all known aliases, document and case study counts, related topics, and the topic page URL. Use this to survey a discipline before going deep — e.g. "what does Digital Transformation cover and what are its key frameworks" — or to orient when the user describes a broad problem area. Follow with search_content (topic filter) for the full catalog.
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  • Get an overview of RZ AI Labs and its founder Amit Raz: what the practice does, his background, and notable clients.
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