"CNN" matching MCP tools:
- 0.093 USDC via x402 on Base. Nine supplier information modules; selected current status and first page up to 10 records per list. No historical expansion or automatic paging. Not complete due diligence. Requires an x402 v2 payment client, a funded Base USDC wallet and spending authorization; a plain MCP connection alone cannot purchase data. Use an exact Chinese legal name or USCC, not a guessed English-name match. Setup and free fictional sample: https://yangchunhong3000.github.io/cn-evidence-public-docs/buyer-guide.html Optional 24h report recovery requires a saved random 32-byte hex X-CN-Recovery-Token header on the paid request, then a free POST to https://api.cnevidence.com/free/cn/payment/recover. See guide; never automatically repay after a timeout.ConnectorNo auth
- 0.093 USDC via x402 on Base. Nine supplier information modules; selected current status and first page up to 10 records per list. No historical expansion or automatic paging. Not complete due diligence. Requires an x402 v2 payment client, a funded Base USDC wallet and spending authorization; a plain MCP connection alone cannot purchase data. Use an exact Chinese legal name or USCC, not a guessed English-name match. Setup and free fictional sample: https://yangchunhong3000.github.io/cn-evidence-public-docs/buyer-guide.html Optional 24h report recovery requires a saved random 32-byte hex X-CN-Recovery-Token header on the paid request, then a free POST to https://api.cnevidence.com/free/cn/payment/recover. See guide; never automatically repay after a timeout.ConnectorNo auth
- Single-product classification. Accepts a free-text description plus optional structured hints (materials, intended_use, category, origin/destination country). POPULATE EVERY HINT YOU HAVE — materials/intended_use/category materially improve retrieval and candidate quality vs a description-only call (e.g. description:"Funko POP Vinyl", category:"Figurines", materials:["PVC plastic"], intended_use:"decorative collectible figure" reliably surfaces ch. 95). Returns top-3 CN candidates, EUDR scope, MFN duty, a bilingual reasoning_md narrative, a gap_analysis flagging missing inputs, and a tri-state status (confident / review_recommended / manual_review_required). Trust `status` for review-routing — do not re-derive your own confidence threshold. PAT-authed callers also receive prior_decisions[] from the org dictionary history.ConnectorNo auth
- Search news articles. Returns a list of matching articles. Each article includes: - article_id, classification_id, title, source, date, link, category, rank, total_shares, summary - bias_values: dict of per-dimension bias scores using plain-text keys (e.g. 'liberal conservative bias'), same schema as get_bias_from_url and get_all_source_biases (when available) - bias_analysis_status: 'evidence_ready', 'evidence_unverified', 'evidence_partial', 'evidence_failed' (all scored dimensions' quotes failed verification, so the scores do not match the article text), 'scored_legacy', or 'pending' - evidence_ratio: fraction of scored bias dimensions whose supporting quote is verified (0.0-1.0). Raise min_evidence to demand only articles with verified quotes. - bias_dimensions when include_evidence=true: a self-contained object joining each score, scale, evidence status, claim, evidence, counterevidence, confidence, and rationale. Quotes include verification method and exact character offsets when raw-text matching succeeds. Dimension evidence_status is one of: verified, provided_unchecked, quote_mismatch, metadata_incomplete, metadata_only, or missing. - bias_analysis: contract/schema/model/prompt provenance, generation and review status, input scope/hash/size, limitations, quote-verification method, and explicit evidence coverage - context: AI-generated contextual background for the article (when available) - implicit_assumptions: tacit or unstated premises the article's claims or framing rely on (list of concise strings, when available) - extracted_data: structured quantitative/qualitative facts extracted from the article - raw_data: legacy serialized form of extracted_data Args: query: Optional search keywords. Leave empty to return the most recent articles in scope (use with bias to rank them). e.g. 'NVDA earnings'. limit: Max results (1-100, default 20). source: Filter by source name, e.g. 'CNN', 'Reuters'. category: Filter by category. One of: 'trending', 'tech', 'markets', 'politics', 'business', 'science', 'memes'. days_back: Only include articles from the last N days. 0 means no date filter. Default: 90. Widen this (e.g. 720) for older coverage. min_shares: Minimum total social shares. sort: Sort order. One of: 'rank' (relevance, default), 'date' (newest), 'shares' (most shared). bias: Bias dimension to rank by, highest score first. This is a ranking, not a standalone filter: an empty query still returns other recent articles, ranked with the bias dimension on top. Any canonical bias key, e.g. 'liberal conservative bias', 'overall credibility', 'conspiracy bias'. Ranking is scoped to recent articles (the days_back window, or 365 days when days_back is 0) so one old high-scoring outlier cannot dominate. include_evidence: Include claim-level evidence, counterevidence, confidence, rationale, and limitations. Defaults to false to keep search payloads compact. only_analyzed: Return only articles with valid canonical bias scores. min_evidence: Minimum fraction of scored dimensions with verified quotes (0.0-1.0, default 0). Raise this to request only articles whose scores are backed by verified evidence, e.g. 0.5. Pair it with only_analyzed to get quotable results instead of pending records with empty bias_values. Returns a 400 if sort or bias is not a valid option.ConnectorNo auth
- Search US television news closed captions (2009–October 2024, 150+ stations) for spoken mentions of a query. Returns a bounded, paged per-station time series showing airtime devoted to the topic. Use the stations parameter to select networks (e.g. ["CNN", "FOXNEWS", "MSNBC"]) — the TV API requires at least one station, supplied either there or as a station: selector inside query. TV query also supports in-query operators: station:CNN, network:CBS, market:"National", show:"Anderson Cooper 360", context:"vaccine". Important: most station monitoring ended October 2024 — use gdelt_list_tv_stations to verify active date ranges before querying recent events.ConnectorNo auth
- Identify which font is used in an image. Powered by our OWN CNN embedding model, trained on the jinero font catalog — it matches fonts by visual shape/style, so it needs NO OCR and NO text (works for Latin and Cyrillic). Send a tight crop of one line of text as either image_url (public URL) or image_base64 (base64/data-URI, e.g. a local screenshot). The image is processed in memory and deleted immediately — never stored. Returns the most visually similar font families with scores. Typically 0.3-1.7 s (an OCR-assisted rerank of top candidates engages when retrieval is uncertain). Rate limit: 5 calls/min per IP (model inference is compute-heavy).ConnectorNo auth
Matching MCP Servers
- AlicenseAqualityAmaintenanceCNN's Fear & Greed index for the US stock market: current score and rating, the seven component indicators, and about a year of daily history. Go standard library only, no API key required.12MIT
- AlicenseAqualityDmaintenanceA Model Context Protocol server that provides real-time CNN Fear & Greed Index data for the US stock market, including current sentiment scores and historical comparisons.139 npm4MIT
Matching MCP Connectors
64 individually paid Chinese company data tools at 0.011 USDC per tool call via remote MCP and x402 on Base. 68 MCP tools total, including the schema helper and legacy tools. Selected registration, shareholder, risk, IP, legal, tax, website and other records; consult each live tool schema. Legacy Basic (3 modules) and Full (9 modules) remain 0.032 / 0.093 USDC, not bundles of the new tools. Discovery is free; data queries require a funded USDC wallet and x402 spending approval. Plain MCP clients do not pay automatically. Start with an exact Chinese legal name or company_id in company_detail; most company tools need its returned company_id. Record-detail tools use record_id from a matching separately paid parent list. New paged lists return the first page only, at most 5 rows; legacy lists at most 10. No automatic pagination, complete-history, factory or supplier-safety guarantee. Empty data is not no risk; statistics/trends are not detailed records. The old resolver is a capability notice, not a free lookup; native MPP is paused. Upstream checks passed for the 64 new tools; real-wallet payment-to-delivery acceptance and commercial redistribution/overseas delivery permission review remain pending. Guide: https://yangchunhong3000.github.io/cn-evidence-public-docs/v3-tools.html
China company data: 64 tools at 0.011 USDC/call via MCP/x402; legacy Basic/Full retained.
- Ориентировочная цена станка с опциями: мощность шпинделя (2.2/3.2/4.5/6 кВт, надбавка 25–145 тыс. ₽) и вакуумный стол (+45 000 ₽). Аргумент model — product_number (например "4") или название модели. Возвращает base_price, options и estimated_total в рублях; финальная цена — в КП менеджера.ConnectorNo auth
- Полная карточка станка по product_number (поддерживаются дробные id, например "1.1"): характеристики, цена руб./USD, изображения, комплектация, опции, 3D-модели, видео и URL страницы товара.ConnectorNo auth
- Список категорий станков завода с количеством моделей — быстрый обзор ассортимента (фрезерные, лазерные, плазменные, камнерезные, токарные и др.).ConnectorNo auth
- Контекст компании: название и бренд, город и адрес, контакты, сайты и все discovery-URL (llms.txt, llms-full, server-card, OpenAPI). Вызывай первым для справки о производителе.ConnectorNo auth
- Сравнение 2–4 станков завода по ТТХ и цене: рабочее поле, шпиндель, цена, наличие, описание. ids — массив product_number, например ["1.1", "1.2"], либо id_a/id_b. Результат — таблица для ответа клиенту.ConnectorNo auth
- Fast lookup for a known CN code. Returns the canonical description (SV + EN), chapter heading, applicable classification rules, EUDR Annex I scope (in_scope + is_ex), and the MFN duty headline. Pass include=["reasoning"] to also receive the bilingual reasoning_md narrative.ConnectorNo auth
- Avançado: envia uma query Elasticsearch crua pro índice do tribunal (escape hatch). `query` é SÓ a cláusula de busca (ex.: { match: { "classe.nome": "Apelação" } }); size, sort, _source e search_after vão nos campos próprios. Use search_after (valor `sort` do último hit) pra paginar além de 10.000 resultados. A API pública do CNJ é lenta em índices grandes: prefira size pequeno e `_source` com só os campos que precisa.ConnectorNo auth
- Multi-source market sentiment in one read: the crypto Fear & Greed index, CoinMarketCap’s variant, the traditional-market (CNN) Fear & Greed, and the Altcoin Season index. Useful for framing any "how is the market feeling" question.ConnectorNo auth
- 读取信号验证记录(track record):命中率、已验证/待验证统计、每条信号从 predicted_on 到 verify_by 的结果。这是唯一用时间积累的资产——判断层的命中历史,LLM 无法生成。Use when: 评估信号板可信度、查某行业历史命中率、复盘已兑现/落空案例。Use instead: 要当前信号清单用 read_signal_board;问判断层问题用 ask_edge;查财报追踪用 read_earnings_tracker。ConnectorNo auth
- Summarize a long text into a shorter, coherent paragraph using the facebook/bart-large-cnn model via HuggingFace Inference API. Trained on CNN/DailyMail news articles; works well for factual prose. Control output length with max_length (token cap) and min_length (token floor) parameters. Custom model override supported (e.g. google/pegasus-xsum for extreme single-sentence summaries). Useful for article digests, executive summaries, and reducing LLM context window usage.ConnectorNo auth
- Return one published supplier record in full, by the `slug` from search_suppliers results. Includes identity (legal name, Chinese registered name when a registry lookup confirmed it, location, business type, founded year, employee range), the official website or source listing, the Made-in-China.com inquiry form when there is one, capabilities (processes, materials, certifications, equipment, industries, tolerance, maximum part size) and the facet keys search_suppliers matches, certificates, product families, facilities and news items with their own source pages, the listings the record was read from with permission basis and check date, and field-level evidence (the quote, page, extraction method, and review status behind each claim). `buyer_facts.checked` lists what CNC Compass confirmed (registry review, source factory, certificates on China's national register, a named third-party audit); `buyer_facts.profile` is what the supplier publishes about itself (tolerance, inspection, lead time, MOQ, Incoterms, payment terms, ...), each item with its quote and source page: present it as the supplier's statement, to be confirmed at quotation. `verification_status`, `factory_verification` ("Verified source factory" or empty) and `last_verified_at` report editorial review. An unknown slug is a tool error.ConnectorNo auth
- List the values search_suppliers can filter on, with how many published suppliers declare each. Fields are process, material, finish, and location; pass `field` for one of them. Each value has a stable `key`, a display `label`, a `records` count, and `implies` (broader keys a narrower one also matches, such as aluminum-6061 implying aluminum). Pass a label or key as the matching optional argument of search_suppliers. Locations are the city and province words that at least three supplier addresses share, most common first; `omitted_values` counts the rarer ones, which search_suppliers still matches. `index_records` is the number of published suppliers.ConnectorNo auth
- 0.032 USDC via x402 on Base. Company registration, operating abnormalities, administrative penalties. Page 1, up to 10 records per list. No safety guarantee. Requires an x402 v2 payment client, a funded Base USDC wallet and spending authorization; a plain MCP connection alone cannot purchase data. Use an exact Chinese legal name or USCC, not a guessed English-name match. Setup and free fictional sample: https://yangchunhong3000.github.io/cn-evidence-public-docs/buyer-guide.html Optional 24h report recovery requires a saved random 32-byte hex X-CN-Recovery-Token header on the paid request, then a free POST to https://api.cnevidence.com/free/cn/payment/recover. See guide; never automatically repay after a timeout.ConnectorNo auth
- 0.032 USDC via x402 on Base. Company registration, operating abnormalities, administrative penalties. Page 1, up to 10 records per list. No safety guarantee. Requires an x402 v2 payment client, a funded Base USDC wallet and spending authorization; a plain MCP connection alone cannot purchase data. Use an exact Chinese legal name or USCC, not a guessed English-name match. Setup and free fictional sample: https://yangchunhong3000.github.io/cn-evidence-public-docs/buyer-guide.html Optional 24h report recovery requires a saved random 32-byte hex X-CN-Recovery-Token header on the paid request, then a free POST to https://api.cnevidence.com/free/cn/payment/recover. See guide; never automatically repay after a timeout.ConnectorNo auth
- Can this GPU run this open-weight LLM? Returns fits, tight or no, the memory split (weights, KV cache, overhead), a decode-speed ceiling, the longest context that fits and, on a no, every change that would make it fit: quantisation, KV cache, context, another card or a smaller model. Model: a name or id from list_models, any Hugging Face repo id, or its architecture. GPU: a name or id from list_gpus, or vram_gb for any other card.ConnectorNo auth