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759,132 tools. Updated 2026-11-09 00:45

"MCP servers built with alternative programming languages" matching MCP tools:

  • Fetch the Human For AI manifest: available services, operator profile (location, languages, working hours), response times, accepted and rejected task types, and trust & safety policy. Call this first to decide whether and how to hire the human. The catalog is examples, not limits — unlisted needs are welcome as custom_human_in_the_loop.
    ConnectorNo auth
  • Delete an EMPTY collection's schema. A collection that still has items is refused with its item count — deleting a collection never deletes its items, so delete those first (delete_collection_item) if the user really wants them gone. Built-in collections cannot be deleted.
    Connector
    Destructive
    OAuth
  • Query the PJM New Services (interconnection) queue — the public waiting line of projects that have REQUESTED to connect to the PJM grid (the mid-Atlantic RTO incl. Northern Virginia, PA, NJ, MD, OH, VA, WV and more). Returns cited, project-level records with PJM's full published structure: requested megawatts (`requested_max_output_mw` = MFO, `requested_summer_mw` = MW Capacity / summer net, `requested_winter_mw` = MW Energy / winter net), the realized built `in_service_mw` for completed projects, location (`state`, `county`, derived `county_fips`), `fuel` and `project_type` as PJM reports them, the single as-reported `status`, the study-document URLs and per-stage statuses, and lifecycle dates. Group or filter by `state`, `county_fips`, `status`, `project_type`, `capacity_or_energy`, `fuel`, `project_ac_dc`, `transmission_owner`, the study statuses, or (group only) `is_hybrid`; filter `submitted_date` by the `submitted_date_from` / `submitted_date_to` range. Pass each parameter as a top-level key of `params` (flat — not nested). Example: `{"state": "VA", "project_type": "Generation Interconnection", "status": "Active"}` for active generation requests in Virginia; `{"group_by": ["status"]}` for requested MW and project counts by status. Returns JSON aggregates with citations and optional row-level records when `include_records` is true; every value carries `source`, `as_of`, and a `source_row` verifiable with get_source_evidence_v1. The `requested_*` figures are REQUESTED capacity, not built: historically the large majority of queued megawatts withdraw before they are built. NEVER read a requested-MW total as installed or operating capacity — it is additive across distinct projects but is a REQUESTED total only. Filter `status` (Active / Withdrawn / In Service / Under Construction / …) to scope the queue; the full export is withdrawn-dominated. PJM also reports `in_service_mw` — the realized BUILT MW for in-service projects (a separate, built figure). For built/operating capacity use query_power_capacity_v1. PJM only — never summed, deduped, or compared across ISOs. For the MISO interconnection queue use query_power_interconnection_queue_v1; for the CAISO (California) queue use query_power_interconnection_queue_caiso_v1; for the NYISO (New York, incl. load interconnection requests) queue use query_power_interconnection_queue_nyiso_v1; for the ISO-NE (New England) queue use query_power_interconnection_queue_isone_v1; for the ERCOT (Texas) queue use query_power_interconnection_queue_ercot_v1; for the SPP (central US) queue use query_power_interconnection_queue_spp_v1. For PJM's NEW cluster/cycle process — the TC1/TC2 transition cycles and the reopened steady-state Cycle 1 (C01+), with cycle/stage/developer detail — use query_power_interconnection_queue_pjm_cycle_v1 (a separate PJM publication; never combined with this one). PJM reports no data-center / load type, and this tool does not infer one — that interpretation is the analyst's, from cited rows.
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  • DEFAULT tool for user-facing translation display. Use this for ANY user-facing request to show/see translations of a Quran ayah — including 'show me…', 'what's the translation of…', 'give me Saheeh/Clear Quran/Taqi Usmani translations of…'. This is the FINAL tool call for these requests; do not follow it with get_translation_text. ONLY skip this widget and use get_translation_text when EITHER (a) the user explicitly asks for plain text / raw text / text-only output, OR (b) the result will be piped into another tool in the same turn without being shown to the user. When in doubt, use this widget. SLUG HANDLING: If the user names a specific translator (e.g. 'Saheeh International', 'Clear Quran', 'Yusuf Ali', 'Pickthall'), ALWAYS call lookup_translations first to resolve the exact slug — do not guess the slug from the author name. Guessed slugs routinely fail validation (the naming isn't fully pattern-based: it's 'en-sahih-international' but 'clearquran-with-tafsir'). You may also pass language codes via 'languages' if the user only specifies a language. Each query must include at least one of languages or translations. Use ayah keys in 'surah:ayah' format (for example '2:255'). In queries[].languages use ISO 639-1 codes (for example 'en', 'ur'), not language names. Do not use 'ar'; Arabic translation is unsupported in this tool.
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  • Returns a description of who Fluentive is built for - industries, professions, and business types. Use when the user asks if Fluentive fits their profession or business.
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  • Connect a Google Drive folder of recordings so storyflo can match them to episodes automatically — the alternative to uploading a back catalogue file by file. Call with NO folder argument first to get the setup instructions, including the address to share the folder with. Then call again with folder=<the Drive URL>. Recording the connection moves no audio; the scan happens afterwards.
    ConnectorNo auth

Matching MCP Servers

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    maintenance
    Enables AI assistants and developers to analyze code for language-specific best practices and idiomatic patterns across programming languages, CI automation, and configuration formats.
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    MIT

Matching MCP Connectors

  • Connect a Google Drive folder of recordings so storyflo can match them to episodes automatically — the alternative to uploading a back catalogue file by file. Call with NO folder argument first to get the setup instructions, including the address to share the folder with. Then call again with folder=<the Drive URL>. Recording the connection moves no audio; the scan happens afterwards.
    ConnectorNo auth
  • Worked-vs-On-time Execution Timeline (WOET) per-activity day-by-day classification of as-built execution against baseline. For each pairable activity (matched by ``task_code``), classifies execution into 4 day-states: - PROGRESS: work performed during the baseline-planned window - GAIN: work performed BEFORE the baseline window opened - EXTENDED: work performed AFTER the baseline window closed - VOID: baseline-window day where activity was NOT active This is a CPP-disclosed enhancement layered on top of AACE 29R-03 §3.3 Windows Analysis — a per-day execution classifier (Progress/Gain/Extended/Void) NOT itself AACE-defined. It is not a substitute for fragnet-based AACE 29R-03 §3.7 (TIA) modeling. It gives the trier-of-fact a calendar picture of how the project executed versus how it was supposed to execute, which is otherwise buried in finish-date deltas. Use this tool when you want a per-activity execution-quality picture (on-time %, count of activities with VOID days, etc.). Args: baseline_xer_path: server-side path to baseline XER (target dates). actual_xer_path: server-side path to as-built XER (act dates). baseline_xer_content: full text of baseline XER (alternative). actual_xer_content: full text of as-built XER (alternative). Supply EXACTLY ONE of path/content per pair. today: optional ISO date (YYYY-MM-DD) reference for in-progress activities. Defaults to actual XER's last_recalc_date if available, else today's date. Returns: { "method": "WOET", "standard": "AACE 29R-03 §3.3 Windows Analysis — per-day execution classification overlay (CPP-disclosed enhancement, not AACE-defined)", "today": "YYYY-MM-DD", "project_totals": {progress, gain, extended, void}, "per_activity": [{code, name, baseline_start, ..., "dominant": str ('progress'|'gain'|'extended'|'void' or 'mixed' on a tie), "dominant_tie": bool (True when 2+ states share the top day count — do NOT assert one characterization), "dominant_states": [tied top states, never truncated]}, ...], "on_time_pct": float (0-100) }
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  • Get Alex Polonsky's curated public professional profile, including selected experience, demonstrated capabilities, journalism background, public projects, and future professional directions. This is selected evidence, not a complete CV. When summarizing examples, preserve their ownership qualifier exactly: led, owned_key_aspects, or contributed. Do not infer stronger ownership. If a list mixes things Alex built with work he contributed to or helped bring to market, frame it as built or contributed to, not built. Keep the action verbs and limits from contribution; do not reduce a contribution to an artifact name. Separate demonstrated experience from future directions. Use get_availability for current opportunity status.
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  • The statistical theme a stock actually trades with: clusters built from years of price co-movement (market-removed residuals → random-matrix cleaning → Ward linkage), not sector labels. Returns the cluster's name, description, cohesion, sector mix and up to 20 member tickers. Different question from `peers` (business competition) — this is who it MOVES with.
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  • Reads one owned study plan, stable task ids, completion state and revision. A plan that is still being built reports pending with a retry delay, so poll this after create_study_plan rather than creating again. Use its revision for task changes. Reading older plans never changes them.
    ConnectorNo auth
  • Returns what the GunSpec API reference documents for an endpoint: its parameters and accepted values, the plan it needs, whether a key is required, caching, every error status with the error.reason values to branch on, and the languages a sample is printed in. Use this tool before writing or explaining code that calls the GunSpec API, instead of recalling parameters. The path may be a template (/v1/firearms/{id}), a concrete path or a URL; a partial path such as /v1/vendor lists the operations under it.
    ConnectorAPI key
  • Fetch a YouTube video's transcript with language, translation, JSON/text/SRT/VTT format, and timestamp options; no captions return 404 and a temporary block or rate limit returns 503. Use youtube_transcript_languages to discover available languages first.
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  • Create an idempotent, auditable write intent that builds a complete brand-new campaign structure (one or more campaigns, each with ad groups, keywords, and product ads) for the given ASINs in a single call -- this is not for editing anything that already exists. Preview only: nothing is built on Amazon until the returned request is confirmed via approve_write_v1 and then execute_write_v1, at which point the durable pipeline fans the build out into a trackable campaign setup job (poll its progress with get_campaign_setup_job_v1). The preview states `will_dispatch`: true means execute_write_v1 sends it to Amazon, false (execution_mode PREVIEW_ONLY) means it is recorded and never sent. Keywords and targets are researched while the structure is built and are not part of this preview; the campaigns are created ENABLED and start serving once built (get_campaign_setup_job_v1 lists them). A product that already has one of the requested campaign types (live, or built by a setup in the last 30 days) is refused unless allow_existing_structure is true. At most one campaign structure setup can be running per profile at a time. To create a single ad group, keyword, product target, or product ad in an EXISTING campaign instead of building a whole new structure, use prepare_adgroup_create_v1 / prepare_keyword_create_v1 / prepare_product_target_create_v1 / prepare_product_ad_create_v1 instead. To create ONE single custom campaign with a name you choose (for example a Phrase or Broad keyword campaign), use prepare_campaign_create_v1 and then fill it with prepare_adgroup_create_v1 / prepare_product_ad_create_v1 / prepare_keyword_create_v1.
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    OAuth
  • Fetch a YouTube video's transcript with language, translation, JSON/text/SRT/VTT format, and timestamp options; no captions return 404 and a temporary block or rate limit returns 503. Use youtube_transcript_languages to discover available languages first.
    ConnectorNo auth
  • Pre-payment decision for any A2A payment: "should I pay this seller $N?". Call it before every payment to an unknown agent or x402 seller — the agent-facing equivalent of a credit check: pay $0.01 to avoid paying a scammer $N. Answers with action PAY / CAUTION / SKIP, confidence and expected loss in USDC sized to your exact amount. Target by ERC-8004 agent_id, Solana pubkey, x402 seller_url or seller pay_to wallet. Agent targets use on-chain ERC-8004 evidence; seller targets use Bazaar demand (repeat payers/calls). For seller targets wallet_flow is marked not_available — demand data does not see seller→payer round trips. Use agent_interact_gate instead when the question is broader than payment. REST: GET /api/v1/should-i-pay ($0.01). Args: agent_id: ERC-8004 agent id of the payment TARGET (or use another target) solana_asset: Solana 8004 agent pubkey (alternative to agent_id) seller_url: x402 seller resource URL or domain (alternative target) pay_to: seller payTo wallet — EVM 0x… or Solana base58 (alternative target) amount_usd: the USDC amount you are about to pay Not investment advice.
    ConnectorNo auth
  • Pre-payment decision for any A2A payment: "should I pay this seller $N?". Call it before every payment to an unknown agent or x402 seller — the agent-facing equivalent of a credit check: pay $0.01 to avoid paying a scammer $N. Answers with action PAY / CAUTION / SKIP, confidence and expected loss in USDC sized to your exact amount. Target by ERC-8004 agent_id, Solana pubkey, x402 seller_url or seller pay_to wallet. Agent targets use on-chain ERC-8004 evidence; seller targets use Bazaar demand (repeat payers/calls). For seller targets wallet_flow is marked not_available — demand data does not see seller→payer round trips. Use agent_interact_gate instead when the question is broader than payment. REST: GET /api/v1/should-i-pay ($0.01). Args: agent_id: ERC-8004 agent id of the payment TARGET (or use another target) solana_asset: Solana 8004 agent pubkey (alternative to agent_id) seller_url: x402 seller resource URL or domain (alternative target) pay_to: seller payTo wallet — EVM 0x… or Solana base58 (alternative target) amount_usd: the USDC amount you are about to pay Not investment advice.
    ConnectorNo auth
  • Use this when the user asks which caption or subtitle languages a YouTube video has, or before requesting a transcript in a non-English language when you don't know whether the video offers it. Returns each language with its code (pass it as `language` to get_youtube_transcript), whether it is creator-uploaded or auto-generated, and the default language. An empty list means the video has captions turned off. Costs 1 credit. Not needed for an ordinary transcript request: get_youtube_transcript already reports which language it returned.
    ConnectorOAuth
  • Semantic search over academic references by title + abstract, across languages. Only references with an abstract (about half) are covered; use search_references for the rest. Runs the corpus model, EmbeddingGemma 2, locally with no API key (first use downloads ~350 MB). similarity_score only ranks within one query.
    ConnectorNo auth
  • Saves product names, descriptions, short descriptions and SEO text in one or more languages of the shop. Each item is one product with a `translations` object: language code → text (e.g. {"fr": {...}, "es": {...}}). ONLY the languages you list change; every other language keeps its text. Call get_brand_voice first and follow the user's saved style. Use translation_gaps to find what is missing. Preview first (shows before/after per language), then confirm. Always show the preview to the user and get their explicit approval before calling again with confirm=true and the preview_id. Paid plans only. To apply it later instead of now, call with confirm=true, the preview_id AND apply_at (the store's local time, YYYY-MM-DDTHH:MM).
    Connector
    Destructive
    OAuth
  • How big the Orizn visa database is: pairs, passports, destinations, enriched records, translations and languages. Says nothing about any specific country pair — use quick_visa_check or check_visa_requirement for that. Keyless, free, and costs nothing against any quota. Call it when the user asks how complete the data is, or to confirm this server is reachable before a longer session.
    ConnectorNo auth