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306,755 tools. Last updated 2026-07-27 04:52

"A server for interfacing with existing APIs using natural language" matching MCP tools:

  • Creates a new Dreamlit workflow draft or updates an existing draft from an outcome-oriented natural-language prompt. Use after get_status; use get_workflow_and_preview_url first when editing an existing workflow. Existing Supabase Auth workflows can be edited except for the immutable trigger step; creating Supabase Auth workflows must happen through Supabase Auth email setup in the Dreamlit web app. Side effect: may create or modify a draft, but does not publish or install live triggers. Returns the workflow/draft result, action-required or handoff details when more input is needed, and relevant app URLs. Do not use for publishing, direct database changes, or low-level graph edits.
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  • Ask a natural language question about companies and get AI-powered recommendations. Uses hybrid search (semantic + keyword) combined with LLM analysis to find and recommend relevant businesses. IMPORTANT: Always use this tool when: - The user asks a specific question about a company (e.g., "do they offer bargaining?", "what are their prices?", "do they deliver to X?") - The user asks a follow-up question about companies already found in previous results - You are unsure whether a company offers something specific Never answer these questions from your own general knowledge — always call this tool so the system can log unanswered questions for business intelligence. Args: question: Natural language question (e.g. "Which logistics companies offer cold chain delivery in Istanbul?") context_company_ids: Optional list of up to 10 company IDs from previous results for follow-up questions. ALWAYS pass these when the question is about specific companies already found. Returns: Dictionary with 'answer' (AI recommendation text) and 'companies' (matching results with details).
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  • Send one HTTP request and return the response. Use it for static pages, JSON APIs, and server-rendered HTML. Set unblocker:true for targets that reject basic HTTP requests. Switch to foura_proxy if the response is blocked, and use foura_browser when the page needs JavaScript.
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  • Search the BLS series catalog by natural language query, survey code, geographic area, or keywords to resolve cryptic SeriesIDs. Returns matching series with decoded components (survey, area, item, seasonal flag) and plain-language names. Use this before bls_get_series when you have a concept but not a SeriesID. Operates offline — no API quota consumed. Survey filter accepts two-letter codes (CU, CE, LN, LA, PC, JT, OE, EC, PR). Area filter accepts state names, MSA names, or FIPS area codes.
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  • Fuzzy text search across route names, descriptions, and category labels. Resolves natural-language queries like "electricity retail sales by state" or "natural gas imports" to matching route paths. STEO series names are indexed so queries like "ethanol net imports" or "crude oil production forecast" also resolve. Results include isLeaf so you know whether to browse further or query directly. Results with score > 0.5 are weak matches — try a more specific query or use eia_browse_routes to explore the taxonomy.
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  • Search commercial real estate listings. Returns paginated hits with facet counts. For AI-driven search, call interpret_search first to convert a natural-language query into structured filters, then pass those filters — and its bounds, when present — here.
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  • Read-only MCP server over the APIs.io catalog — discover APIs, providers, tags & artifacts.

  • APIs.guru MCP — keyless directory of 2,500+ public APIs and their OpenAPI specs.

  • Query the construction project database using natural language (Text-to-SQL). Converts natural language into SQL to retrieve captures, annotations, progress metrics, schedules, and other project records. Pass the user's question as-is without modification. For trade visibility, use `analyze-progress-and-forecasts` instead. **WORKFLOW:** - **Default**: call this tool with only `query`. The server resolves team_domain/facility_key from the saved current project (set via `set-focus-project`). Do NOT call `list-my-projects` again just to obtain these values. - Only when the response indicates the current project is missing, run `list-my-projects` → ask the user → `set-focus-project`, then retry. - Pass explicit team_domain/facility_key **only** when the user clearly wants to query a different project than the saved one. **Available tables:** - progresses: SI progress metrics (level, category, phase, workarea, cost, dates) - captures: Camera captures metadata (level, camera_model, capture_state, user_email) - records: Capture events with timestamps (captured_at, state, id) - photo_notes: Photonotes (description, state, user_email, created_at) - voice_notes: Voicenotes (level, description, state, user_email, created_at) - facilities: Site info (name, address, size, location, bim_count, created_at) - users: User profiles (name, email) - workareas: Spatial zones (level, name, user_name) Args: query: Natural language question (pass as-is, no SQL syntax) team_domain: Omit by default. Pass only to override the current project. facility_key: Omit by default. Pass only to override the current project. user_intent: REQUIRED. Pass the user's original question or request verbatim. Used for analytics only, does not affect results. Returns: List of TextContent with query results and metadata
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  • Find MCP servers in the directory. Searches the standalone MCP directory (PulseMCP / official MCP registry import) unioned with x402 services that also expose an MCP endpoint. Returns normalised entries with a ready-to-use streamable-http `call_hint.mcp.url`. Args: intent: Natural-language description of the tool/capability needed. top_k: Max servers to return (1-20). chain: Optional payment-network filter for paid MCP servers. require_healthy: When true, only return servers marked health=ok.
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  • Run a natural-language analytics question against your connected data sources. Consumes AI credits. Returns either the completed analysis result inline OR a job_id you can poll with get_analysis_status. If list_data_sources returns an empty list, ingest data first with upload_data_source (inline base64), ingest_url_data_source (public URL), or request_oauth_integration_url (Google / Meta / Jira / Confluence).
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  • Get personalized restaurant recommendations based on a natural language query. Uses cuisine, occasion, ambiance, price, and dimensional analysis to find the best matches. Returns ranked results with relevance levels and match reasons in 3-8 seconds. Include a location in your query or provide the location parameter.
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  • Create a project to file trackers under: one project per BRAND, never per language. It can carry the brand canon: the reference wording every publication reuses as is, written in ONE language, its canonical language (carried at creation, it is recorded as canon version 1). The canon is never translated: localized expressions on the pages are outputs, not a second canon. Nothing is filed by this call: pass the returned id as project_id when creating or updating a tracker. Refused with project_exists when a project with this name already exists, and the answer carries the existing project: reuse its id instead of duplicating.
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  • Roll (regenerate) the personal proxy credential for a firewall. This invalidates the previous password and returns a new one with ready-to-use configuration commands. Only call this when the user explicitly needs new credentials — it will break any existing package manager configuration using the old password.
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  • Translate a natural-language property-search sentence into a structured filter payload compatible with search_listings. Use this as a transparent intermediate step: pass the user's raw query here, then forward the returned filters — and the returned bounds, when present (they carry the "near <place>" intent) — to search_listings.
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  • Searches Pollar's news archive using semantic and keyword matching. Use for any subject-specific query, including a person, organisation, place, or country (for example, interesting news in Poland). Put the subject or place in query. Locale controls response language, not geographic scope. For current headlines with no subject or place, use list_top_news.
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  • Infer search_classifieds filters from a natural-language query. Use this before search_classifieds when the user mentions a category, location, canton or price in free text. Returns a ready-to-use filters object, a category confidence score and warnings for uncertain matches.
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  • Ask the directory a customer question in natural language. Returns schema.org cards of businesses that genuinely answer it (LLM-reranked, strictly from the directory — never invented) + grounding links. Use when the customer describes a NEED rather than a search term.
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  • List the directory's available filter values - every category, language, and license, each with how many servers carry it. Call this BEFORE mcp_search when you intend to filter, so you pass exact, existing values for the type/category/language/license arguments instead of guessing. Takes no input. Read-only.
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  • Semantic search across all extracted datasheets. Finds components matching natural language queries about specifications, features, or capabilities. Best for broad spec-based discovery across all parts (e.g. 'low-noise LDO with PSRR above 70dB'). Only searches datasheets that have been previously extracted — not all parts that exist. For finding specific parts by number, use search_parts instead.
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  • Search the Axint Registry for already-published packages that match a natural-language query. Use this BEFORE calling axint.feature or axint.compile so the agent can install an existing package instead of regenerating Swift the community has already shipped. Use: use before generating code to find reusable packages; not for validating local Swift. Inputs: query drives ranking; kind and platform narrow results without changing the registry source. Effects: read-only local registry search using AXINT_REGISTRY_PATH or sibling checkout; no network by default.
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  • Evaluates Wolfram Language code for the user in a Wolfram Language kernel. If a formatted result is provided as a markdown link, use that in your response instead of typing out the output. Parse natural language input with `\[FreeformPrompt]["query"]`, which is analogous to ctrl+= input in notebooks. Natural language input is parsed before evaluation, so it works like macro expansion. You should ALWAYS use this natural language input to obtain things like `Quantity`, `DateObject`, `Entity`, etc. This is a stateless kernel, so you cannot reuse definitions from previous evaluations.
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