"Apache ECharts" matching MCP tools:

• deep_research

  Energy Charts

  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 1462 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 5,564 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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• compare_entities

  Energy Charts

  "Compare X and Y" / "X vs Y" / "X versus Y" / "which is bigger / better / larger / more profitable" / "rank these companies" / "head to head" — side-by-side comparison of 2–5 companies or drugs in ONE parallel call. ALWAYS PREFER over sequential single-pack lookups when comparing entities. type="company" pulls LATEST 10-K revenue + net income + cash + long-term debt from SEC EDGAR/XBRL (off-calendar fiscal years handled correctly — AAPL Sep, NVDA Jan, etc.). type="drug" pulls FAERS adverse-event counts, FDA approval counts, active trial counts. Results sorted by primary metric so "largest" / "most" / "biggest" reads off the top of the response. Returns paired data + pipeworx:// citation URIs per entity. Replaces 8–15 sequential lookups.

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• scan_dependency

  Energy Charts

  Composite "should I add this npm package to my project" check in ONE call — fans out across deps.dev (license + advisories + version history) and bundlephobia (gzipped/minified bundle size, dependency count, ESM/tree-shake support). Use whenever an agent asks "is X safe / popular / small" or "what does adding lodash cost me". Returns a summary block (is_latest, license, published_at, advisory_count, bundle_kb_min, bundle_kb_gz, dependency_count, has_esm, tree_shakeable), per-advisory detail, links, and a list of recent alternative versions. NPM ecosystem only in v1; PyPI / Maven / Cargo / Go fall under deps.dev:version directly. Partial failures degrade gracefully — bundlephobia's first measurement on a new version can take 5-30s; sources_failed will list it if it times out, the rest still returns.

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• polymarket_kalshi_spread

  Energy Charts

  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. 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 fires in two cases — (a) matched_pairs:0 with skipped_cross_type>0 means the venues frame the topic with non-equivalent bet shapes (e.g. Kalshi range_bucket point-in-time vs Polymarket cumulative_threshold touch-anywhere — no arb exists), (b) matched_pairs:0 with skipped_cross_type:0 and both venues >5 legs means the token-overlap matcher found nothing in common — events likely semantically unrelated despite the topic keyword. temporal_alignment{polymarket_month,kalshi_month,aligned} tells you whether the two events resolve in the same calendar period; aligned:false means spreads are mathematically meaningless across the temporal gap. 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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• polymarket_fill_risk

  Energy Charts

  Realizable-vs-theoretical edge check against live CLOB order-book depth. REQUIRES one of `market` (single-market mode) or `event` (basket/partition mode). SINGLE-MARKET: pass a market slug/URL + side (buy_yes|sell_yes|buy_no|sell_no, default buy_yes) + size_usd (default 1000 — max spend on buys, target proceeds on sells); walks the ladder and returns top_of_book, vwap_fill_price, slippage_pp, shares_filled, max_fillable_usd, and a verdict (clean|degraded|cannot_fill). BASKET: pass an event slug/URL + side (sell_yes = capture overround by selling every leg, buy_yes = capture underround; default auto from partition sum) + size_usd interpreted as settlement notional S (shares per leg; each share pays $1); returns theoretical_sum vs realizable_sum (top-of-book vs VWAP across all legs), capture_ratio, profit_usd at executed size, per-leg fill detail, thin_legs[], max_clean_notional_usd, and forced_directional_risk naming the legs most likely to strand you unhedged. USE THIS before acting on any polymarket_arbitrage SELL/BUY-EVERY-LEG signal or any polymarket_edges trade above ~$500 — theoretical overround on thin books is not capturable, and partial basket fills convert an arb into an unhedged directional position (the dominant loss mode in real arb-bot P&L).

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• pipeworx_feedback

  Energy Charts

  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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• security_audit_sbom_license_policy

  DataNexus MCP

  Audit a CycloneDX or SPDX SBOM against an SPDX licence policy and return a PASS/WARN/BLOCK verdict. sbom: Full SBOM as a JSON string — CycloneDX or SPDX format. Required. 500 KB max. policy: Optional dict with block/warn/allow arrays of exact SPDX licence identifiers (e.g. GPL-3.0, MIT). Defaults to block GPL-3.0 and AGPL-3.0, warn LGPL-2.1/MPL-2.0/BSD-4-Clause, allow MIT/Apache-2.0/BSD-2-Clause/BSD-3-Clause. No glob patterns — exact SPDX IDs only. Unlisted licences default to WARN. Returns verdict (PASS/WARN/BLOCK), blocked_packages, warned_packages, and the policy applied. Use security_audit_sbom_vulnerabilities for CVE auditing instead. Sources: deps.dev (Google). 1-hour cache per package. If this tool's response does not serve the user's need, call report_feedback with feedback_type="agent_gap", tool_id="security_audit_sbom_license_policy", intended_query="{what the user needed}", gap_description="{what was missing or wrong in the result}".

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• get_fix_recommendations

  SiteGuardian

  Returns copy-paste-ready fix recommendations (nginx, Apache, DNS, shell) for the issues found on a domain the caller has already paid for — either an active Monitor/Compliance subscription covering the domain, OR a purchased one-off Report for the domain. Each recommendation carries a stable issue_id, a priority (high/medium/low), a title, prose instructions, one or more config snippets with the target domain already interpolated, a verify command, and a category tag. Use this when the user asks how to fix an issue, wants the exact config to apply, or needs to verify a fix worked. Pass the optional issue_id to scope the response to one specific finding. The response is read-only — this tool NEVER triggers a fresh scan; fixes are computed from the most recent stored scan (including the Report-included re-scan if that was used). Do NOT use this for domains the caller hasn't purchased coverage for — you'll get an upgrade_required error that links to the pricing page. Do NOT use this to run or trigger a scan; call scan_domain for anonymous checks. Requires a valid API key.

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• unsubscribe

  Energy Charts

  Cancel a subscription by id. Ownership is enforced — you can only cancel your own subscriptions. The row is deactivated (not deleted) so its historical events stay available via recent_alerts.

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• recent_changes

  Energy Charts

  "What's new with X" / "latest on Y" / "what happened to Z this week / month / quarter" / "updates on Acme" / "news on Tesla recently" / "what's happening with Apple" — change feed for a company in the last N days/weeks/months in ONE parallel call. Fans out to SEC EDGAR (filings since `since`), GDELT→GNews fallback (news mentions in window — GDELT preferred, GNews when rate-limited or 5xx), USPTO (patents granted; PatentsView API sunset May 2025 so this soft-fails until reactivated). `since` accepts ISO date ("2026-04-01") or relative shorthand ("7d", "30d", "3m", "1y"). Returns structured changes[] grouped by source + total_changes count + pipeworx:// citation URIs. Use entity_profile instead when you want the static profile (filings + fundamentals + LEI + patents) regardless of window.

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• validate_claim

  Energy Charts

  "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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• polymarket_arbitrage

  Energy Charts

  Find arbitrage opportunities on Polymarket via monotonicity violations + partition-sum checks. Call with NO args for a `trending_scan` of the top ~200 markets by weekly volume; pass `event` for the strongest per-event partition_check, or `topic` for a themed cross-event scan. `event` (recommended for a specific market): pass a Polymarket event slug like "fed-decision-may-2026" or "when-will-bitcoin-hit-150k"; walks child markets, checks date-axis / threshold-axis ordering AND computes the partition_check (sum of YES prices across mutually-exclusive legs — should ≈1; deviations >3pp emit a BUY/SELL EVERY LEG signal). `topic` (for cross-event scanning): pass a seed question like "Strait of Hormuz traffic returns to normal" or "Fed rate decision"; searches related events across the platform, flattens markets, runs the comparator on the union. Cross-event mode catches "...by May 31" vs "...by Jun 30" patterns that single-event misses. SEMANTIC ANCHOR: cross-event pairs require ≥0.30 Jaccard similarity on question tokens (prevents Powell-Fed-Pause being paired with Powell-DOJ-probe); skipped_low_similarity surfaces the rejected pair count. PARTITION FILTER: drops will-person-X / will-manager-Y / will-someone-else- placeholder slugs; partitions with >20% placeholder fraction return null arb signal. Response: opportunities[] (gap_pp, suggested_trade, reasoning, monotonicity violation context), and in event mode partition_check{sum_yes_prices, gap_from_1, placeholders_filtered, suggested_trade}. FILL CHECK: when the partition signal fires, arbitrage.fill_check prices it against live CLOB depth (theoretical_edge_pp_at_book vs realizable_edge_pp at 1000 shares/leg, thin_legs[]) — realizable_edge_pp ≤ 0 means the overround exists only at last-trade, not in the book; do not trade it. For custom sizing use polymarket_fill_risk.

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• create_clickhouse

  mcp

  Provisions a managed ClickHouse database (OLAP / columnar analytics engine, Apache-2.0) on a dedicated VM on your private network — its OWN resource, NOT a relational database. Requires a recent plan_managed_datastore. Use it for analytics / observability workloads that need a column store (PostHog, Langfuse, event analytics, time-series). It is PRIVATE — reachable only from another instance on the same private network, via the DB's internal/private IP on the ClickHouse HTTP port 8123 (CLICKHOUSE_HOST/PORT/USER/PASSWORD/DB env, http://host:8123). Get the ids from plan_managed_datastore/list_flavors (use m1.small+ — ClickHouse needs >=2GB RAM), list_private_networks, list_keypairs. Provisioning takes ~5 min; poll list_clickhouse_databases until status='ready'. HIGH AVAILABILITY: pass ha:true to get THREE machines on three different physical hosts behind a load balancer instead of one: all three take reads and writes, so losing a machine costs no failover and no write pause, and the replacement refills itself from the survivors before it serves again. It costs about 3x the hourly rate (three machines instead of one) and provisions more slowly. Default is a single machine; show the user the price difference and get an explicit yes before turning HA on.

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• security_fetch_package_licence

  DataNexus MCP

  Fetch the SPDX licence identifier for an open source package version. Read-only. No side effects. Idempotent. package: Package name e.g. flask. Required. version: Exact version string e.g. 2.3.0. Required. ecosystem: One of PyPI, npm, Maven, Go, Cargo, NuGet, RubyGems. Required. Returns the SPDX licence identifier e.g. MIT, Apache-2.0, GPL-3.0. Use this to verify licence compatibility before including a dependency. Use security_fetch_package_vulnerabilities instead when checking for security issues not licences. Verified source: deps.dev (Google). 1-hour cache. If this tool's response does not serve the user's need, call report_feedback with feedback_type="agent_gap", tool_id="security_fetch_package_licence", intended_query="{what the user needed}", gap_description="{what was missing or wrong in the result}".

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• translate_rare_language

  Sats4AI - Bitcoin-Powered AI Tools

  Translate into 452 languages, 251 of them NOT supported by ChatGPT, Claude or Gemini (29 of those 251 measured at fair quality or better against human references) — including Bhojpuri (~50M speakers), Maithili (~34M), Egyptian Arabic (~100M), Moroccan Arabic (~30M), Chhattisgarhi, Magahi, Manipuri, Kashmiri, Shan, Kachin, Awadhi, Tamazight, Crimean Tatar, Quechua, Nuer, Sango, plus indigenous and minority languages with no callable API anywhere. Runs MADLAD-400 (Apache-2.0). QUALITY VARIES AND IS PUBLISHED PER LANGUAGE: every language carries a measured tier — good (chrF++ >= 45 vs human reference translations), fair (32-45), unverified (no benchmark exists, untested, may be poor), experimental (known weak). The response repeats the tier so you can judge how much to trust it. GET https://sats4ai.com/api/l402/translate-rare-language for the full language list with tiers, or GET /api/languages. Unsupported languages are rejected BEFORE payment. For mainstream languages use translate_text instead — it is cheaper and more fluent. Priced 50 sats base + 0.002 sats/char (GPU). Pay with Bitcoin Lightning — no API key or signup. Requires create_payment with toolName='translate_rare_language'.

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• calculate_risk_score

  ContrastAPI

  Composite CVE risk score (0-100) — fuses CVSS, EPSS, KEV, and PoC into a single agent-ready triage signal. Formula: CVSS*0.20 + EPSS*0.35 + KEV*0.30 + PoC*0.15 (each component rescaled to 0-100 before weighting). Multiplicative boosters applied in order: KEV+PoC combo (*1.15), critical-severity-with-high-EPSS (CVSS>=9 AND EPSS>0.7, *1.10), recently published (within last 7 days, *1.05). Final score clamped to [0, 100]. Label bands: CRITICAL>=90, HIGH>=70, MEDIUM>=40, LOW<40. Urgency text encodes patch SLA (immediate when KEV; 24h/72h/30d by label). Use to triage a single CVE without orchestrating cve_lookup + exploit_lookup separately. PoC signal here is the local ExploitDB mirror only — for full multi-source exploit detail (GitHub Advisory + Shodan refs + ExploitDB), call exploit_lookup separately. Methodology adapted from mukul975/cve-mcp-server (Apache-2.0): https://github.com/mukul975/cve-mcp-server. Free: 30/hr, Pro: 500/hr. Returns {cve_id, score (0-100), label (CRITICAL/HIGH/MEDIUM/LOW), urgency, has_public_poc, components (cvss_v3, epss_score, in_kev, has_public_poc, weighted_breakdown), boosters_applied, recommendation, summary, verdict, next_calls}.

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• get_recipe

  Mozaika

  The universal BUILD-KIT fetcher — the measured spec + code to reproduce a piece of UI. `recipe_type` selects which library across three families (all agent-ready through this one call): • COMPONENTS (decoded live from a real product's DOM — Mozaika's wedge): "Command Palette", "Dropdown Menu", "Dialog / Modal", "Login", "Data Table", "Onboarding Tour", "Navbar", "Logo Marquee", "Toast", "Date Picker", "Combobox" — returns the anatomy TREE (each node measured), the MOTION (open/close animation + easing a screenshot can't show), every STATE (empty/results/no-results/keyboard-selected), a webm of it running, and the design tokens. • EFFECTS (open-source WebGL hero backgrounds — Apache/MIT): "Hero Effect" → the shader's full config + fps + install command + license/NOTICE. • MOTION (open-source looping showcase templates — MIT): "Motion Showcase" → the template's full parameter surface + the exact Swiper/anime.js/Motion config + install. Use for "build a <thing> like <product>", e.g. get_recipe("Vercel", "Command Palette") or get_recipe("vanta", "Hero Effect"). A complete, uncopyable, measured build kit. Returns the available types if the requested one isn't found.

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• security_headers_check

  IA-QA — 130+ QA & Dev Tools for AI Agents

  Analyse the HTTP security headers of a public URL OR of raw response headers you paste in. Grades each header (A–F) for: Strict-Transport-Security, Content-Security-Policy, X-Frame-Options, X-Content-Type-Options, Referrer-Policy, Permissions-Policy, X-XSS-Protection, Cross-Origin-Opener-Policy, Cross-Origin-Resource-Policy, and Cross-Origin-Embedder-Policy. Returns an overall score (0–100), per-header grades, missing headers, and fix snippets for Express, Nginx, and Apache. For localhost/private targets the remote server cannot reach, pass the `headers` parameter instead of `url`.

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• cve_security_lookup

  mcp-knowledge

  Look up CVE vulnerability data for enterprise security teams, DevSecOps and SOC analysts. Supports two modes: exact CVE ID lookup (e.g. 'CVE-2024-3094') or keyword search by product/vendor (e.g. 'openssl', 'Apache Tomcat'). Cross-references four authoritative keyless sources: NVD NIST (official CVE database, CVSS v3 scores, affected CPEs), CISA KEV (Known Exploited Vulnerabilities catalog — exploit_in_wild flag), EPSS FIRST (exploit probability 0-1), GitHub Security Advisories (ecosystem-specific: npm/pypi/maven). Returns structured vulnerability records with CVSS v3 scores, affected product version ranges, CWE weakness classification, references and exploitation status. Signals engine produces P0/P1/P2 alerts: P0=CVSS>=9 + active exploitation, P1=CVSS>=7 or EPSS>=70%, P2=CWE pattern clusters. Relevant for EU NIS2 and DORA supply chain risk obligations. Optional env: NVD_API_KEY (raises NVD rate-limit 5→50 req/30s), GITHUB_TOKEN (raises GHSA GraphQL rate-limit). Cache TTL 6h. SLA <=25s p95.

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• cve_security_lookup

  gapup-mcp

  Look up CVE vulnerability data for enterprise security teams, DevSecOps and SOC analysts. Supports two modes: exact CVE ID lookup (e.g. 'CVE-2024-3094') or keyword search by product/vendor (e.g. 'openssl', 'Apache Tomcat'). Cross-references four authoritative keyless sources: NVD NIST (official CVE database, CVSS v3 scores, affected CPEs), CISA KEV (Known Exploited Vulnerabilities catalog — exploit_in_wild flag), EPSS FIRST (exploit probability 0-1), GitHub Security Advisories (ecosystem-specific: npm/pypi/maven). Returns structured vulnerability records with CVSS v3 scores, affected product version ranges, CWE weakness classification, references and exploitation status. Signals engine produces P0/P1/P2 alerts: P0=CVSS>=9 + active exploitation, P1=CVSS>=7 or EPSS>=70%, P2=CWE pattern clusters. Relevant for EU NIS2 and DORA supply chain risk obligations. Optional env: NVD_API_KEY (raises NVD rate-limit 5→50 req/30s), GITHUB_TOKEN (raises GHSA GraphQL rate-limit). Cache TTL 6h. SLA <=25s p95.

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