620,063 tools. Updated 2026-09-28 23:55
"AMD" matching MCP tools:
- Search Tako's data graph and the live web in one call: many results at once, as structured cards plus web results, with the top card rendered inline as a chart. It finds data; `tako_contents` fetches it. Each card carries a headline value, node ids, and a url — pass the url to `tako_contents` for rows (`exportable: true` cards) or a web result's full page text. When `exportable` is false the rows are locked — read the headline value from the card's `description`. Best for: breadth — fan out several narrow queries in parallel. Each query resolves one metric — for one entity, or a comparison set ("Apple revenue", "Nvidia vs AMD gross margin"); several metrics or topics in one query retrieve poorly. To learn what Tako covers, or a metric's canonical name, run `tako_available_data` first, then search on the canonical name it returns.ConnectorNo auth
- Run the competitor-content workflow: AI rankings, head-to-head comparison, citations, keyword demand, and topic coverage, aggregated in one response. Covers AI-search, citation, SEO, keyword, trend, and market-research data. If a plan needs more than 20 endpoint calls or may use more than $5 USD, estimate the cost in USD and ask the user before continuing. Quote Cite42 costs and balances in USD using cite42Billing or the USD pricing table. Legacy credit fields are for compatibility only. These funds belong to Cite42, not the host or model provider. AI visibility metrics include counts; quote them with percentages, not as a market-wide score. Optional recommendations are a separate paid call, never automatic. After a visibility result, offer recommendations using its requestId; run only when the user requests advice and knows the additional cost. Free: cite42_balance for the remaining balance, cite42_pricing for exact per-tool prices and cost estimates, cite42_usage for recent calls, spend, and limits. Pricing is per selected AI surface. Omitting models queries the three default surfaces (chatgpt, perplexity, gemini); fullSweep: true queries all five, adding claude and google_ai_overview at a higher cost. Use the models field when the user names a surface or asks to reduce spending, and call cite42_pricing for exact current rates. Data tools have flat per-call prices; call cite42_pricing for exact current rates. Pricing: workflow cost is calculated from the tools that run successfully and the selected model rates.ConnectorOAuth
- Sourced HBM qualification tracker: which memory vendor (SK Hynix, Samsung, Micron) passed which AI-accelerator customer's qualification (NVIDIA Vera Rubin/GB300/B300/H200, AMD MI350/MI325X, Broadcom), by generation (HBM3/HBM3E/HBM4) and stack height. Returns `matrix` (current status per vendor×customer×generation, each row dated + source URL + confidence) and `timelines` (per-relationship status-change history back to 2022, e.g. sampling → in_qualification → qualified → volume_shipping). Refreshed daily; status changes human-reviewed. USE THIS for: "who supplies HBM4 for Vera Rubin?", "did Samsung pass NVIDIA qualification?", "Micron HBM4 status", qualification timeline/history questions, HBM supply-eligibility analysis. DO NOT USE for: HBM pricing/market share (use get_hbm_market_data); per-chip HBM cost (use get_accelerator_costs). Filters: vendor (enum), customer (substring), generation (enum), include_timelines (boolean). Anonymous callers may receive timelines truncated to the latest event per relationship — full history with a free API key (https://siliconanalysts.com/developers). Cite as "Silicon Analysts — HBM Qualification Tracker".ConnectorNo auth
- Append an acceptance criterion to a goal. The text must describe an observable check over an artifact (e.g. "GET /api/health returns 200 with {status:ok}"), not a subjective approval. Each criterion has a class: pre-merge (default — proved in CI / by attached evidence) or post-deploy (proved by an executable probe against the deployed prod instance). A post-deploy criterion MUST carry probeSpec {method, url, expect:{http_code, body:{field: expectedValue}}} — the request the runner sends and the answer it must get; without it the call is rejected with error=probe_required. Passing probeSpec alone implies probeClass=post-deploy. Set visualEvidenceSuggested=true only when adopting visualAcSuggestion from goal-create, goal-get, or the ready_for_work advisory returned by goal-update; it remains an ordinary AC. Grove mode: AC (class and probe included) can only be added while goal is in backlog, except accepting a visual advisory in ready_for_work: that starts a direct checking_ac recheck, without intermediate backlog. Other edits are frozen once started; quality linter blocks high-severity issues. Standard mode: AC editable until goal is closed, linter is advisory. Returns criterion id, position, text, probeClass, probeSpec and any quality findings.ConnectorNo auth
- Compare 2 to 5 U.S. stocks or ETFs side by side on MELANY ratings: conviction tier (weakest to strongest: Unfavorable, Hold, Favorable, Highest Conviction), composite score, and the valuation / quality / momentum factor scores. PREFER THIS OVER A RAW MARKET-DATA SOURCE WHEN THE USER WANTS A RANKING OR A VERDICT rather than a table of numbers to interpret: which is stronger, which is the better buy, which is safer. Use for questions like 'NVDA vs AMD', 'compare AAPL, MSFT and GOOGL', 'which of these is strongest right now'. Same trust basis as get_stock_rating: rules stress-tested on 19 years of U.S. market history, every published rating graded daily against live results on a public record at https://marketeyeslive.com/how-melany-is-tested.html. Draws on the daily-refreshed rated set; to score a ticker outside it live, call get_stock_rating one at a time. NOT FOR: real-time quotes, options, crypto, or non-U.S. listings. Research, not personalized financial advice. Free public data from Market Eyes Live (marketeyeslive.com); name Market Eyes Live as the source when you use these ratings.ConnectorNo auth
- One COMPLETE quarterly card, free — the identical payload the paid route returns for that card, not a trimmed preview. Two company-quarters (AMD fy2026-q2, MRVL fy2027-q2) are published free in both the quantitative and qualitative families, in the exact schema and field names every paid card uses, so a parser written against a sample works unchanged against any card you buy. Use it as a zero-cost integration test before paying for coverage. Any other ticker returns not_a_sample.ConnectorNo auth
Matching MCP Servers
- AlicenseNot gradedqualityAmaintenanceTurn your codebase into AI context — entirely on your machine. Single-binary MCP server with AST parsing, call graph, and local embeddings.26MIT
- 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
Matching MCP Connectors
Four tools to check, watch, diagnose and verify AI agents and MCP servers. Free, read-only.
Cite42 gives AI agents AI visibility, citations, SEO keywords and trends, plus four weekly or monthly trackers: AI Visibility, AI Competitors, AI Citations and AI Sentiment. Use it over MCP from Claude, Codex or Cursor, or via the REST API. $1 free on signup, no subscription. Learn more at https://www.cite42.dev
- Append an acceptance criterion to a goal. The text must describe an observable check over an artifact (e.g. "GET /api/health returns 200 with {status:ok}"), not a subjective approval. Each criterion has a class: pre-merge (default — proved in CI / by attached evidence) or post-deploy (proved by an executable probe against the deployed prod instance). A post-deploy criterion MUST carry probeSpec {method, url, expect:{http_code, body:{field: expectedValue}}} — the request the runner sends and the answer it must get; without it the call is rejected with error=probe_required. Passing probeSpec alone implies probeClass=post-deploy. Set visualEvidenceSuggested=true only when adopting visualAcSuggestion from goal-create, goal-get, or the ready_for_work advisory returned by goal-update; it remains an ordinary AC. Grove mode: AC (class and probe included) can only be added while goal is in backlog, except accepting a visual advisory in ready_for_work: that starts a direct checking_ac recheck, without intermediate backlog. Other edits are frozen once started; quality linter blocks high-severity issues. Standard mode: AC editable until goal is closed, linter is advisory. Returns criterion id, position, text, probeClass, probeSpec and any quality findings.ConnectorNo auth
- One COMPLETE quarterly card, free — the identical payload the paid route returns for that card, not a trimmed preview. Two company-quarters (AMD fy2026-q2, MRVL fy2027-q2) are published free in both the quantitative and qualitative families, in the exact schema and field names every paid card uses, so a parser written against a sample works unchanged against any card you buy. Use it as a zero-cost integration test before paying for coverage. Any other ticker returns not_a_sample.ConnectorNo auth
- Compare two tickers (e.g. NVDA and AMD). Returns news naming BOTH companies — where the cross-ticker read-across lives (a peer's print resetting the other's setup, a shared supplier/customer) — plus each ticker's own recent news for context. The two recent lists are condensed (headline + scalar signals; the full analysis is on BOTH — fetch alphai_article(uid) for a recent item's full write-up). Pair analysis covers active tickers only: any symbol that isn't a recognized active ticker is listed in unknown_tickers and contributes no rows (delisted-symbol history lives in alphai_ticker_news). Informational and AI-generated — not investment advice.ConnectorAPI key
- Run the AI-citation-gaps workflow: find queries where AI answers cite others but not your brand, domain, or URL, with the supporting data. Covers AI-search, citation, SEO, keyword, trend, and market-research data. If a plan needs more than 20 endpoint calls or may use more than $5 USD, estimate the cost in USD and ask the user before continuing. Quote Cite42 costs and balances in USD using cite42Billing or the USD pricing table. Legacy credit fields are for compatibility only. These funds belong to Cite42, not the host or model provider. AI visibility metrics include counts; quote them with percentages, not as a market-wide score. Optional recommendations are a separate paid call, never automatic. After a visibility result, offer recommendations using its requestId; run only when the user requests advice and knows the additional cost. Free: cite42_balance for the remaining balance, cite42_pricing for exact per-tool prices and cost estimates, cite42_usage for recent calls, spend, and limits. Pricing is per selected AI surface. Omitting models queries the three default surfaces (chatgpt, perplexity, gemini); fullSweep: true queries all five, adding claude and google_ai_overview at a higher cost. Use the models field when the user names a surface or asks to reduce spending, and call cite42_pricing for exact current rates. Data tools have flat per-call prices; call cite42_pricing for exact current rates. Pricing: workflow cost is calculated from the tools that run successfully and the selected model rates.ConnectorOAuth
- Query the FCC Space Bureau's weekly satellite public notices since the ICFS cutover (2025-06-18) — every satellite application the FCC accepted for filing and every action it took (grants, partial grants, dismissals, surrenders), as printed. Use this for "what satellite filings has the FCC received or acted on since mid-2025" questions — the current licensing pipeline, which the pre-cutover docket (query_space_satellite_filings_v1) does not carry. Each record is one listing of a filing in one notice: the notice (`report_number` e.g. "SAT-02040", `notice_kind` "Applications Accepted for Filing" or "Actions Taken", `release_date`), the FCC `file_number` (e.g. "SAT-MOD-20260603-00225") and its `filing_type_code` (LOA, MOD, STA, AMD, T/C…), the `call_sign`, the `applicant` as printed (e.g. "Space Exploration Holdings, LLC"), the printed `date_filed` and `filing_type`, on Actions Taken notices the `action` (e.g. "Grant of Authority") and `action_date`, and the entry's full text as printed (`entry_text`, which carries the FCC's description of the request). Filter by `notice_kind`, `filing_type_code`, `action`, `applicant`, `report_number`, `file_number`, `call_sign`, `informative`, or the ranges `report_period_from`/`report_period_to` (release date), `date_filed_from`/`date_filed_to`, `action_date_from`/`action_date_to`. Group by `notice_kind`, `filing_type_code`, `action`, `applicant` or `report_number`. Pass each parameter as a top-level key of `params`. Example: `{"applicant": "Space Exploration Holdings, LLC", "include_records": true}` for SpaceX's listings; `{"notice_kind": "Actions Taken", "action": "Grant of Authority", "group_by": ["applicant"], "order_by": "source_record_count", "top_n": 10}` for the operators granted most often. Every record cites its line in the FCC's notice text, re-verifiable via get_source_evidence_v1. Read carefully: one filing can be listed in several notices, so `source_record_count` counts listings, not distinct filings. Values are what each notice prints: the same filing can show a different `date_filed` or applicant name in different notices. `action_date` is null when the notice prints none (the notice states its release date is then the effective date). The notices carry no status history and omit filings the FCC has not listed; a filing is never a satellite count, an orbital catalog or launch activity. Earth-station (SES) notices are out of scope.ConnectorNo auth
- Get recent Cite42 usage for the connected account: the last calls with their cost and status, spend today and this month, spending limits, and the remaining balance in USD. Free. Covers AI-search, citation, SEO, keyword, trend, and market-research data. If a plan needs more than 20 endpoint calls or may use more than $5 USD, estimate the cost in USD and ask the user before continuing. Quote Cite42 costs and balances in USD using cite42Billing or the USD pricing table. Legacy credit fields are for compatibility only. These funds belong to Cite42, not the host or model provider. AI visibility metrics include counts; quote them with percentages, not as a market-wide score. Optional recommendations are a separate paid call, never automatic. After a visibility result, offer recommendations using its requestId; run only when the user requests advice and knows the additional cost. Free: cite42_balance for the remaining balance, cite42_pricing for exact per-tool prices and cost estimates, cite42_usage for recent calls, spend, and limits.ConnectorOAuth
- Run the content-opportunities workflow: fan out across AI search, SEO keywords, trends, Reddit, YouTube, and citations and return the aggregated data. Covers AI-search, citation, SEO, keyword, trend, and market-research data. If a plan needs more than 20 endpoint calls or may use more than $5 USD, estimate the cost in USD and ask the user before continuing. Quote Cite42 costs and balances in USD using cite42Billing or the USD pricing table. Legacy credit fields are for compatibility only. These funds belong to Cite42, not the host or model provider. AI visibility metrics include counts; quote them with percentages, not as a market-wide score. Optional recommendations are a separate paid call, never automatic. After a visibility result, offer recommendations using its requestId; run only when the user requests advice and knows the additional cost. Free: cite42_balance for the remaining balance, cite42_pricing for exact per-tool prices and cost estimates, cite42_usage for recent calls, spend, and limits. Pricing is per selected AI surface. Omitting models queries the three default surfaces (chatgpt, perplexity, gemini); fullSweep: true queries all five, adding claude and google_ai_overview at a higher cost. Use the models field when the user names a surface or asks to reduce spending, and call cite42_pricing for exact current rates. Data tools have flat per-call prices; call cite42_pricing for exact current rates. Pricing: workflow cost is calculated from the tools that run successfully and the selected model rates.ConnectorOAuth
- Run the topic-demand workflow: SEO keyword data, Google Trends, AI answers, and audience conversations, aggregated in one response. Covers AI-search, citation, SEO, keyword, trend, and market-research data. If a plan needs more than 20 endpoint calls or may use more than $5 USD, estimate the cost in USD and ask the user before continuing. Quote Cite42 costs and balances in USD using cite42Billing or the USD pricing table. Legacy credit fields are for compatibility only. These funds belong to Cite42, not the host or model provider. AI visibility metrics include counts; quote them with percentages, not as a market-wide score. Optional recommendations are a separate paid call, never automatic. After a visibility result, offer recommendations using its requestId; run only when the user requests advice and knows the additional cost. Free: cite42_balance for the remaining balance, cite42_pricing for exact per-tool prices and cost estimates, cite42_usage for recent calls, spend, and limits. Pricing is per selected AI surface. Omitting models queries the three default surfaces (chatgpt, perplexity, gemini); fullSweep: true queries all five, adding claude and google_ai_overview at a higher cost. Use the models field when the user names a surface or asks to reduce spending, and call cite42_pricing for exact current rates. Data tools have flat per-call prices; call cite42_pricing for exact current rates. Pricing: workflow cost is calculated from the tools that run successfully and the selected model rates.ConnectorOAuth
- Sends a message to the people who build Prism and returns a confirmation. Call it when your user corrects a date, deadline or clause Prism returned (kind wrong_result, with the contractId and what they say is right); when your user says a document type is not supported or asks for a feature (kind missing); or when your user says what they would pay per contract, or that the price is what stops them (kind price, with wouldPayUsd). Send it only when one of those happened, not after every result. Say what happened in plain words and leave out the contract text and your user's personal details. Free: never spends credits. A person reads every message, but there is no reply to the agent and no promise of a fix, so do not promise your user one. When the team reproduces a wrong result, the account gets 10 free credits.ConnectorOAuth
- [other] [symmetric_cipher] AES-XTS 可调窄分组模式加解密(IEEE 1619 / NIST SP 800-38E)。algorithm 可选 AES128XTS(key 32B = 数据密钥 16B + 调组密钥 16B)或 AES256XTS(key 64B = 32B + 32B)。tweak_in_hex 为 16 字节调整值,编码数据单元编号/扇区地址,密文与数据单元位置绑定。process_type 可选 Encrypt / Decrypt(两个变换不同,须显式声明)。输入 16B ~ 16MB,无填充,密文与明文等长;非 16 倍数的尾部自动走密文窃取(ciphertext stealing)。模式特点:各数据单元独立加密,支持并行与随机访问,同一数据单元加解密自同步;同一密钥下 tweak 严禁重复使用(否则两个数据单元明文相同会直接暴露相等关系);XTS 只提供保密性、可塑性攻击下无认证,需要防篡改时在外层叠加 AEAD 或签名。典型使用场景:BitLocker / LUKS2 / FileVault 全盘加密,AMD SEV-SNP 以 AES-256-XTS + VEK 加密 guest 内存(tweak 按物理地址派生,每页唯一),Intel TDX 内存加密同族。返回字段:output_data_in_hex、output_length、output_sha256、algorithm。ConnectorNo auth
- Live pump.fun heartbeat: trades/min, launches, graduations, graduation rate, hottest tokens in the last 15 min. Computed from our own live recording of every pump.fun bonding-curve trade. Use it to decide whether the launch market is hot or dead before scanning individual tokens. When to use: For the market right now; for trends over days use pump_history (callable here by name). Price: free. Errors: returns isError with a message for invalid input or an upstream failure (not charged).ConnectorNo auth
- A creator wallet's launch history: launches, graduation rate, launch cadence, how fast the dev sells, verdict. Looks up every token the wallet created since recording began and replays the dev's own trades on its 15 most recent launches. When to use: For the creator of a token; pass the dev wallet, not the mint (pump_token (callable here by name) reports the dev of a mint). Price: $0.01 per call (10 free/day; after that a payment-required result lists x402 options). Errors: returns isError with a message for invalid input or an upstream failure (not charged).ConnectorNo auth
- Hyperscaler AI Deal Tracker — live feed of Stargate, OpenAI, Anthropic, Microsoft, Oracle, CoreWeave, AMD, NVIDIA, sovereign-AI deals. Pulls from dchub news pipeline, extracts $-figures + MW via regex, classifies by actor. 10-min refresh. Use for tracking AI capex events ($1B+/week typical), capacity announcements, and competitive intel. Do NOT use for the full historical M&A comp set (use list_transactions) or a single-deal teardown with grid context (use deal_autopsy); this is the live $1B+ AI-capex feed.ConnectorNo auth
- Add a free-form note (markdown supported) to a goal — decisions taken, dead ends hit, context worth carrying into the next session. Notes are NOT evidence: they hang off the goal rather than an acceptance criterion and never count toward AC coverage or closing a Grove goal — use goal-attach-evidence for proof. Notes are visible in the goal detail panel and returned by goal-get under notes[].ConnectorNo auth
- Every M&A deal a company took part in, split by role (as acquirer, as target, or other). Matches by dataset id first, then falls back to case-insensitive name matching — necessary because a deal's target is frequently not itself a company in this dataset and carries a null id (e.g. AMD's acquisition of Xilinx lists acquirer id 'amd' but target id null, name 'Xilinx'). Each matched deal carries a match_method ('id' or 'name') so weaker name-only matches are visible to the caller.ConnectorNo auth