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522,293 tools. Updated 2026-09-06 12:44

"XState" matching MCP tools:

  • "Is it true that…" / "fact check" / "verify the claim that…" / "did X really…" / "was Y actually…" / "confirm or refute" / "true or false" — natural-language claim verification against authoritative sources. Use whenever the agent needs to check whether something a user said is factually correct. Company-financial claims (revenue, net income, cash for public US companies) verify via the structured SEC EDGAR + XBRL fast path with exact percent-delta math; ANY OTHER factual claim (macro statistics, rates, prices, drug data, records) automatically falls through to the grounded pipeline — routed to the right live source, answered with verbatim evidence, then judged. Returns a verdict (confirmed / approximately_correct / refuted / inconclusive / unsupported / could_not_verify), the grounded or structured actual value with pipeworx:// citation, and reasoning. IMPORTANT for callers: could_not_verify means the check did not happen (our LLM or source failed) and carries verification_error{stage,detail} — it is NOT evidence for or against the claim, and must not be shown as one. unsupported means we looked and cover no source for it. Replaces 4–6 sequential calls (NL parsing → entity resolution → data lookup → comparison).
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  • Semantic search over guthmann.estate — market insights, reports, neighborhood portraits, listing exposés, project pages and the company's own pages. Hybrid retrieval (vector + keyword, no reranking); one result per page with title, description, image, best-matching snippet and score. Use it for questions that need prose (analysis, context, advice); use the data tools for exact numbers and `listings` for what is currently for sale — the search index follows the website with up to six hours of delay. Parameters: - q: natural-language query, in the language of the pages you want (min 2 characters) - locale: "de" | "en" — language of the indexed pages (default: en) - section: comma-separated filter — "listings" (exposés), "projects" (new-build projects), "market-intelligence" (insights, reports, portraits), "pages" (company, services, guides); omit for all - limit: 1-20 pages (default: 10) Key response fields: - url, title, description, image, section, language - snippet (best-matching text passage), score (0-1)
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  • Request a free Nefesh API key. No existing API key needed for this call. IMPORTANT: You MUST ask the user for their real email address before calling this tool. Do NOT invent, guess, or generate an email address. The user will receive a verification link they must click to activate the key. Without clicking that link, no API key will be issued. Disposable or temporary email services are blocked. Example prompt to the user: "What is your email address? You will receive a verification link to activate your free API key." Flow: call this with the user's real email, then poll check_api_key_status every 10 seconds until status is 'ready'. Free tier: 1,000 calls/month, all signal types, 10 req/min. No credit card.
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  • 전국 아파트 45,000여 개를 조건으로 거른다. "강남구 20억 이하 대단지", "전세가율 높은 곳", "AI 1년 예측이 높은 단지"처럼 조건이 있는 질문에 쓴다. 지역·브랜드·시공사는 완전일치이고, 수치 축은 <축>_min·<축>_max로 범위를 준다. 응답에 units(단위 설명)와 total이 함께 온다 — 단위를 지어내지 말고 units를 그대로 읽을 것. 기본 20건이며 total로 전체 규모를 알 수 있다. ★비교·순위·집계처럼 여러 건을 봐야 하는 질문이면 **한 번에 limit=100으로 받아 직접 추려라.** 20건씩 나눠 여러 번 부르는 것보다 그쪽이 훨씬 싸다(호출 비용은 건수와 거의 무관하다). 수천 건을 훑어야 하면 offset으로 넘기지 말고 describe_fields의 분포를 먼저 보고 조건을 좁혀라.
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  • Search the assessor parcel layer with filters instead of one exact address. Filter by state, municipality, assessor land use code, owner-occupancy, tax-exempt status, year built and assessed value range; results carry assessed value, gross building area, assessed value per square foot, the annual tax and the year built. This is the only way to ask a QUESTION of the parcel layer: resolve_address needs an address you already have. Every answer states the true match count alongside the sample, and a search that matches nothing names the filter that emptied it rather than returning a bare empty list. At least one filter is required. Free.
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  • Creates an economic identity you control, with NO money in it. Free. No human approval, no email, no contract, no sales call. It returns an account key ONCE. DFX stores only its digest and can never show it to you again, so store it before your next call. THE ACCOUNT STARTS AT $0.00 AND CANNOT BUY ANYTHING. DFX mints identity and never credit: a balance moves only when Stripe confirms a payment and DFX re-reads that payment from Stripe. There is no argument anywhere on this server through which you can propose a balance. Call this only if you intend to buy a paid capability. Every discovery, coverage, resolution, property record and event search tool on this server is free, unauthenticated and does not need an account, permanently.
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Matching MCP Servers

  • A
    license
    Not graded
    quality
    D
    maintenance
    Enables Claude to drive a gated incident-response runbook that enforces step order and logs all actions via an XState machine.
    Apache 2.0
  • A
    license
    A
    quality
    A
    maintenance
    Connects to Korea's MOLIT real estate API to provide 14+ tools for live transaction data and financial scenarios like buy now, buy later, or invest only based on income and savings.
    16
    373
    MIT

Matching MCP Connectors

  • 빌라(연립·다세대)·오피스텔·단독다가구·토지·상가/사무실·아파트 분양권의 실거래를 지역별로 준다. "송파구 빌라 시세", "제주 토지 평당가", "강남 상가 얼마"처럼 **아파트가 아닌** 질문에 쓴다. ★아파트는 이 도구가 아니라 search_apartments를 쓸 것 — 둘은 데이터가 완전히 분리돼 있다. ★지역(sido+gu)이 **반드시** 필요하다. 전국 단위 목록은 주지 않는다 — 빌라만 24만 곳이라 한 번에 줄 수 없고, 준다 해도 읽을 수 없다. ★집계 단위가 유형마다 다르다: 빌라·오피스텔·분양권은 **단지**, 단독·토지·상가는 **법정동**이다 (응답의 unit이 알려준다). 단독·토지·상가에서 name은 건물 이름이 아니라 동 이름이다. ★AI 예측(fc)은 없다. 빌라는 단지당 20년에 10건꼴이라 예측이 성립하지 않는다 — 있는 척하지 말고 "실거래 통계"로만 답할 것.
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  • 한 단지(또는 법정동)의 **개별 거래**를 최신순으로 준다 — 날짜·금액·면적·층까지. 다른 도구는 "최근 1년 102건"처럼 **집계**만 줘서 "가장 최근 거래가 언제 얼마"에 답할 수 없었다. "이 단지 최근 거래", "같은 평형 최근 10건", "직전 거래 대비 얼마나 올랐나"에 이 도구를 쓴다. ★아파트와 유형 **전부** 지원한다(kind 생략 시 아파트). ★전월세는 금액이 **보증금·월세 둘**이다 — price 하나로 뭉치지 말 것. 월세 0이면 순수 전세다. ★해제(취소)된 신고도 그대로 준다(canceled=true). 지우면 취소된 신고가를 확인할 방법이 없어서다 — 시세로 인용할 때는 반드시 빼고 말할 것. ★cid는 search_apartments·search_properties 응답에 들어 있다. 손으로 조립하지 말 것.
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  • 주택담보대출의 **현행 규제 수치**를 준다 — LTV·DSR·스트레스 가산금리·규제지역·가격대별 상한. "5억 아파트 사려면 대출 얼마 나오나", "연봉 5천에 현금 1억이면 살 수 있나"에 이 도구를 먼저 부른다. ★★리블은 **계산하지 않는다.** 이 값을 받아서 **네가** 계산하라 — 규제는 자주 바뀌는데 계산기를 우리가 들고 있으면 바뀐 날부터 조용히 틀린 답이 나간다. 우리는 사실과 기준일을 주고, 산수는 네가 하는 편이 정확하다. ★응답의 as_of 이후 개정은 반영돼 있지 않다 — 답할 때 그 날짜를 함께 말할 것. ★how_to_calculate에 순서가 적혀 있다. LTV 한도와 DSR 한도 중 **작은 쪽**이 실제 한도다. ★취득세·중개보수는 이 표에 **없다**(가격·주택수·지역에 따라 갈린다). 모르면 모른다고 하라.
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  • "Tell me about X" / "research Acme" / "brief me on Tesla" / "what does Apple do" / "company profile for Microsoft" / "give me the rundown on NVDA" / "everything you know about $TICKER" — full cross-source profile of a US public company in ONE parallel call. ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view. Fans out across SEC EDGAR, XBRL, USPTO patents, federal contracts (USAspending), FDA-licensed biologics (Purple Book), H-1B hiring (DOL LCA), news and GLEIF, and returns: cik + company_name (+ resolved_from/resolved_to when `value` was a name); recent_filings (up to 5 with pipeworx://edgar/company/{cik}/filings/{accession} URIs); fundamentals (LATEST 10-K Revenues + NetIncomeLoss + Cash, sorted period_end DESC); patents (USPTO PatentsView API sunset May 2025 — soft-fails until reactivated); federal_contracts (USAspending awards where the company is the recipient); fda_products (FDA-licensed biologics — vaccines, cell/gene therapies — from the Purple Book; a company with only small-molecule/generic drugs will show none here, that is expected, not a failure); hiring (H-1B sponsorship volume + salary range from DOL LCA filings); recent news mentions via GDELT→GNews fallback; LEI via GLEIF. `sources_used` / `sources_failed` say which of these actually returned data for THIS company — an empty section is a real "no data", not a bug. Pass a ticker ("AAPL"), zero-padded CIK ("0000320193"), OR a company name ("Moderna") — names now resolve via SEC EDGAR's company-name match; a private company (no CIK/ticker) returns resolved:false with an explicit `notes` line, not a bare failure. `type` accepts "company" or "ticker" interchangeably — both take the same `value` shapes above.
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  • Tell the Pipeworx team something is broken, missing, or needs to exist. Use when a tool returns wrong/stale data (bug), when a tool you wish existed isn't in the catalog (feature/data_gap), or when something worked surprisingly well (praise). ONLY for tools served by this Pipeworx connection — if the tool came from a different MCP server in your client (another vendor's Gmail, Splunk, Slack, etc. connector), we cannot fix it and reporting it here only delays you; file it with that server instead. Not sure? Pipeworx tool names are the ones this connection lists. Describe the issue in terms of Pipeworx tools/packs — don't paste the end-user's prompt. Filing without an account returns a `claim_token`; pass it back later as pipeworx_feedback({claim_token:"pwfb_…"}) to read whether it was fixed and what changed. The team reads digests daily and signal directly affects roadmap. Rate-limited to 5 per identifier per day. Free; doesn't count against your tool-call quota.
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  • ACCOUNT REQUIRED (free — sign in via GitHub at https://pipeworx.io/signup; depth:"thorough" needs a paid plan). If you are not signed in, use ask_pipeworx instead — it works on every tier. Grounded multi-source research across Pipeworx's 1517 STRUCTURED data sources (SEC filings, FRED/BLS economics, FDA, USPTO patents, markets, science, government records, etc.) in ONE call — this is NOT open-web search. Decomposes your question into focused facets, routes each to the right one of 5,798 tools IN PARALLEL, and returns a findings packet: verbatim evidence + confidence + source + fetched_at + a stable pipeworx:// citation per finding, with explicit gaps[] for facets the data couldn't answer (never invented). Best for broad/multi-part questions over structured data ("compare X and Y's regulatory + financial exposure", "research the filings + market picture for ACME"). For a single lookup use ask_pipeworx (one LLM call, not many). For BREAKING or colloquial CURRENT-NEWS / "what's the world saying about X" topics, prefer ask_pipeworx — it routes to live news APIs and the *-news-feeds packs; deep_research returns mostly empty gaps[] when the topic isn't in the structured catalog. Second-hop iteration: depth:"standard" re-angles unanswered gaps (gap recovery); depth:"thorough" additionally chases the best leads from the first pass — so multi-step questions resolve in one call. Every finding carries a `hop` field and a citation_uri — a resolvable pipeworx:// record URI, present only when the source emits one that resources/read can actually serve, so a citation you get back is always fetchable. "standard" and "thorough" also return contradictions[] flagging findings that disagree. Large records are semantically excerpted to the passages relevant to each facet (not head-truncated), so answers deep in a long filing/series aren't missed. Expect 15-60s (thorough with its follow-up + contradiction pass: up to ~90s).
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  • Request an expert callback for a Bangalore real estate project. Use this when the user wants to speak to an expert but is not ready to visit yet. Lower commitment than a site visit — just captures name, phone, and preferred call time. Call this when the user says: - "I want to know more", "can someone call me", "I'd like a callback" - "talk to an expert", "get more information", "not ready to visit yet" - "call me back", "have someone reach out" Required: rera_number, user_name, user_phone Optional: preferred_time (e.g. 'Morning', 'Afternoon', 'Evening') conversation_summary: Summarise in 2-3 bullet points what the buyer is looking for and any questions they raised — this goes to the expert who calls them back. Returns confirmation with callback reference ID.
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  • Poll for what is NEW to you, ordered by when DFX learned it rather than by when it happened. TWO CALLS ARE REQUIRED BEFORE YOU SEE ANYTHING: the first, with no cursor, deliberately returns ZERO events and a starting position; the second, with that cursor, returns what DFX learned in between. If you want rows now rather than a subscription, call search_property_events instead. Filter by event type, state, or a specific property or parcel id. Deterministic and indexed, so it is cheap to call often. Free. HISTORICAL FAMILIES DO FLOW THROUGH HERE. `within_days` on search_property_events cannot reach the past, but this tool is ordered by when DFX LEARNED a fact, not when the fact happened, so a foreclosure that occurred months ago and was ingested today arrives in today's delta. A distress or sales feed built on this works.
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  • PAID: $1.00 USD per delivered schedule. This is the ONLY priced tool on this server. The other eleven are free, keyless and permanently so. Returns the LOAN rather than the event: for one US state and one forward window, up to 200 loans with maturity date, original principal, lender name, instrument type, origination date and the secured property's address, deduplicated to one row per loan and ordered by maturity. Every maturity_basis is 'confirmed': 19,881 of 19,881 loans carry a date filed with the SEC by a servicer or recorded by HUD, and none is estimated or inferred from a term length. HOW TO GET A PRICE, FREE: call this tool with no `authorize` argument and no credential. You are not charged and not refused. You receive a real quote for your exact arguments, the price, every field that would arrive, the known limits, and the number of rows your dollar would actually buy, so a filter that would deliver one row is visible before you spend anything. HOW TO ACTUALLY BE CHARGED: resend the identical call with `authorize` and an `X-DFX-Account` header holding a funded account key. THIS IS THE ONLY THING ON THIS SERVER THAT NEEDS A CREDENTIAL, and it is the reason the handshake's 'no signup' is about the free tier and not about this tool. To get one, call open_dfx_account on this same server; no human step is needed to open it, and a balance must be funded before it can spend. Everything else here, including the quote itself, needs no account at all. FREE ALTERNATIVE, AND IT IS A REAL ONE: search_property_events with event_type=LOAN_MATURITY_SCHEDULED returns up to 50 maturity EVENTS for the same state, dated and sourced, with no principal, no lender and no instrument. It is also a smaller population: an event has to be resolved to a single building, so a loan secured by several is in the paid tape and not in the free index. Use the free tool for timing, this one for a refinancing conversation.
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  • Measured coverage, served sources, object types and the known gaps stated plainly, including where geography is a single state and where nothing carries a calibrated probability. Call this before concluding that an empty result means an absent market. Call it with NO arguments for the full grid: every event family, every state, measured. Call it with `state` and/or `event_type` for a direct verdict on that one slice (COVERED, NOT_COVERED or UNKNOWN) with the basis it was decided on, which is one small answer instead of a grid to parse. Free, and it queries no data: the verdict comes from a coverage registry, so a NOT_COVERED is measured rather than inferred from an empty search.
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  • START HERE — Returns the complete Stratalize tool catalog: governed MCP tools across finance, healthcare, governance, real estate, crypto, and intelligence. Available via public MCP (no auth) or x402 micropayments on Base ($0.02 atomic · $0.10 benchmark · $0.50 synthesis · $1.00 premium · $3.00 outcome pack). Org intelligence, agent governance, and role briefs require OAuth. Call this first to discover tools by role or vertical.
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  • Get aggregated insights for a Coimbatore or Chennai locality: avg price, supply count, demand pulse, livability/investment grade, highlights, watchouts, 12-month priceTrends, and strengthTags. Use when the user asks "what is X locality like" about a neighborhood in either city. Out-of-scope cities return supported=false; surface the scopeMessage to the user. Always surface the disclaimer field when returning livability or investment grade.
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  • Compare 2–5 AVnester listings by listingId, side-by-side. Get IDs from search_properties first (not guessable). If the user has more than 5 candidates ("compare all"), pick the most relevant 5 (cheapest / largest / best price-per-sqft) and say so. Returns each listing plus pricePerSqft, vsCheapestPercent (0 = cheapest), vsLargestAreaPercent (0 = largest). Covers Coimbatore and Chennai; unknown IDs return not_found_or_unpublished. Does NOT recommend a purchase. Always surface the disclaimer.
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  • Hallucination-resistant answer mode for high-stakes reads. Same routing as ask_pipeworx — picks the right tool from 5,798 across 1517 sources, fills arguments, fetches the data — then EXTRACTS the answer using ONLY what the tool result contains. Returns {answer, evidence (verbatim quote), confidence, source, fetched_at, refusal_reason:null} on success, OR an explicit refusal {answer:null, refusal_reason:"not_in_source"|"no_tool_match"|"tool_error"|"data_truncated"|"llm_error"} when the data doesn't directly answer. Use whenever an answer will be quoted, cited, or acted on, and the agent must not invent facts (financial verdicts, legal claims, medical lookups, public statements). Costs one extra LLM call vs ask_pipeworx — prefer ask_pipeworx for casual lookups.
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  • Cross-venue spread between Kalshi and Polymarket for the same resolving question. The two venues sometimes price the same outcome 2-25pp apart because their participant pools differ — when the bet shapes are equivalent that delta is a real signal, when they aren't the tool says so. TWO MODES: (1) `topic` — 10 pre-mapped macro shortcuts ("fed", "btc", "cpi", "gdp", "sp500", "recession", "next_pope", "next_uk_pm", "next_israel_pm", "2028_president") auto-fetch the matching event on each venue. (2) explicit `kalshi_event_ticker` + `polymarket_event_slug` for custom pairings — BOTH modes run the identical token-overlap matcher, so the same disclosures apply to both. RESPONSE: each venue's leg-by-leg prices (raw probability 0-1) plus matched spread[].top_spreads_pp (Kalshi − Polymarket) where the same outcome shows up on both sides. SAFETY FIELDS: compatibility_warning is a sentence and compatibility_codes[] the machine-readable form; BOTH can be non-empty on returned pairs, so read them even when matched_pairs>0. Codes: event_subject_mismatch (the two event titles share no subject words — probably not the same question), temporal_mismatch (they resolve in different months), temporal_alignment_unknown (the resolution month could not be parsed on one or both sides — NOT the same as confirmed-aligned; check each event's close/strike date yourself), non_equivalent_bet_shapes, no_candidate_pairs, unclassified_legs_excluded, pairing_unverified (set in EITHER mode whenever pairs are returned: the legs were matched by keyword and word overlap, not a shared resolution source). Each entry in top_spreads_pp carries its own flags[] (temporal_mismatch, temporal_alignment_unknown, event_subject_mismatch, low_token_overlap). A leg whose metric_type or match_subtype is "unknown" is NEVER paired — those comparisons land in spread.skipped_unclassified and, when the wording lined up, in spread.low_confidence_pairs[] for inspection only. temporal_alignment{polymarket_month,kalshi_month,aligned} tells you whether the two events resolve in the same calendar period, in EITHER mode; null means it could not be computed (see temporal_alignment_unknown), not that the two sides align. spread.fees_note is a standing disclosure: Kalshi charges per-contract trading fees, Polymarket does not, and this tool does not model Kalshi's fee schedule — every spread_pp is gross, not a net tradeable edge. skipped_cross_type / skipped_cross_subtype counters expose how many leg-pair comparisons were dropped (cross-type = metric_type mismatch like MoM vs YoY; cross-subtype = inequality mismatch like cum_ge vs cum_le). Real cross-venue spreads are rarer than the macro-shortcut list suggests — most pre-mapped topics return compatibility_warning today; pre-mapped ≠ tradeable.
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