Semantic Version: Parse and validate semantic versioning
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624,237 tools. Updated 2026-09-30 08:50
"SemVer" matching MCP tools:
- SemVer shapeConnectorNo auth
- Semver: Semantic versioning utilities.ConnectorNo auth
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- Create a Stripe Checkout session for the active organization and return its hosted checkout URL. The user completes the purchase in the browser; nothing is charged by this call itself. Requires an owner API key. plan defaults to developer; an unsupported plan fails with invalid_plan. Use get_billing_info to check the current plan and create_billing_portal to manage an existing subscription.ConnectorNo auth
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- AlicenseNot gradedqualityCmaintenanceMCP server that validates semantic version ranges using npm's semver engine, with payment via x402 on Base mainnet.MIT
- AlicenseNot gradedqualityBmaintenanceProvides semantic versioning tools to parse, compare, and check range satisfaction for version strings, enabling version management through natural language queries.208 npmMIT
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Semantic Versioning (semver) MCP.
SemVer shape
- Returns per-component breaking changes and a migration guide between an installed version of the project's active component package and the latest published version. Read-only: it reports an upgrade, it never performs one. Use it when planning or reviewing a component-library upgrade, or before bumping the package version in a manifest. current_version is the exact semver currently installed, e.g. "1.0.0" - not a range, so no leading "v", "^", or "~"; read it from list_packages when unsure. Passing the latest version returns an empty change set. It is not a per-component changelog and not a current spec - use get_component for one component today, and list_packages for what is installed. Requires update tracking, a Team plan feature; on lower plans it returns an upgrade-required error instead of data.ConnectorNo auth
- 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}. FEES: every opportunities[] row and partition_check.arbitrage carry edge_pp_gross (== gap_pp / overround_pp), fees_pp, edge_pp_net, net_positive, plus polymarket_fee_pp, fee_basis and fee_categories[]. BOTH cost components are modeled: Polymarket's own per-category TAKER FEE (fee = shares × rate × p × (1-p), rates crypto 0.07 / sports-economics-culture-weather-other 0.05 / finance-politics-mentions-tech 0.04, geopolitics and world events fee-free; verified against Polymarket's own docs as of 2026-09-13) and Polygon gas (~$0.02/leg). The taker fee dominates: ~$1.75 per 100 shares on a crypto market at 50c versus $0.02 of gas, so rows that looked profitable before fleet #1927 may now show net_positive:false — that is the correction, not a regression. Each leg is priced at ITS OWN market's rate and price (the fee curve peaks at 50c and falls toward both extremes). fee_basis says where the rate came from: 'payload' (read off the market, the normal case), 'category' (mapped from its fee category), 'fee_free', or 'fallback' (rate unknown — charged at the modal 0.05 rather than assumed free, so an unreadable market is never reported as costless). Where fill_check reprices against live depth, this does NOT double-count that spread cost. 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.ConnectorNo auth
- Extract the settlement clause of a single Polymarket or Kalshi market: who publishes the settling number (source), the clock time + timezone it is taken at, the precision of the computation (e.g. "1-minute candle close" vs "60-second trailing average" vs "election outcome"), the evidence standard (official_source | consensus_reporting | any_credible_report | unspecified), and void_handling (cancellation/postponement settlement — reused verbatim from bet_research's cancellation_rule detector, not re-derived). Parses Polymarket's `description` field (fetched via polymarket_market) or Kalshi's `rules_primary` + `rules_secondary` fields (fetched via kalshi_market) with regex + a small vocabulary — no LLM pass, so an unusual clause reports confidence:"low" rather than a guess. Pass `market` as a Polymarket slug/URL or a Kalshi market ticker (e.g. "KXBTCD-26SEP1317-T66999.99"); a Kalshi EVENT ticker (e.g. "KXBTCD-26SEP1317") also works — it picks one representative market under that event, since the settlement mechanism is normally shared across all strikes/legs in one event. Use this before treating a polymarket_kalshi_spread row as a real arbitrage: two ladders that look alike can settle on different sources, at different times, with different precision — this tool is how you check. Pair with resolution_diff to compare two markets directly. KNOWN GAP: idiosyncratic phrasing that doesn't match the vocabulary returns confidence:"low" and evidence_standard:"unspecified" rather than an LLM-guessed answer.ConnectorNo auth
- Run one ordered chat transcript through an Algenta model and return the assistant message plus token usage. The default text.tokenizer model is a deterministic tokenizer-backed utility route whose assistant message is a JSON tokenization summary of the user messages — not a generative LLM; provider-backed chat models advertised by list_models are routed through the configured provider service. Use responses for independent single-string utility calls. This tool does not stream and does not expose function/tool calling, and nothing is persisted. An unsupported model id fails with model_not_supported.ConnectorNo auth
- Generate one embedding vector per input string (a single string or a list of strings). The default text.hash_embedding_v1 model produces deterministic lexical hash embeddings — identical input always yields the identical vector; provider-backed embedding models advertised by list_models are routed through the configured provider service. Use embedding_similarity to score two vectors or rerank to order documents against a query vector. Read-only; nothing is stored. Returns one {index, embedding, token_count} item per input plus total token usage. An unsupported model id fails with model_not_supported.ConnectorNo auth
- Run multiple simulation requests in one call and return per-item success or failure details. Synchronous deterministic compute; nothing is persisted and no separate rate limit applies. Use simulate for a single request and submit_job for very large async runs. Returns total, succeeded, failed, and a per-item results array with index, success, the envelope's recommended_action and expected_value, or the item error.ConnectorNo auth
- Approve an agent run that is waiting on manual approval (status requires_approval) and execute it synchronously to completion. Runs in any other state fail with agent_run_invalid_state; an unknown run_id fails with agent_run_not_found. The approval is the human-in-the-loop gate for manual-mode runs and is audit-logged and checkpointed. Returns the updated run resource. Use resume_agent_run for paused runs instead.ConnectorNo auth
- Query the organization's audit-event log, newest first, with pagination (defaults page 1, limit 25) and exact-match filters. Every entry records who did what to which resource with which result; an org with no events returns an honest empty page. Requires an admin API key. Use get_audit_log_artifacts for the immutable Parquet artifact copy, and filter by policy_snapshot_id, schema_snapshot_id, manifest_version, or request_hash to trace one execution. Read-only. Returns entries plus total, page, limit, and pages.ConnectorNo auth
- Create a new API key for the current organization and return its raw_key value exactly once — it is never shown again, so store it immediately. expires_at optionally sets an ISO-8601 expiry and device_limit caps how many devices the key may register (validated against the plan ceiling, invalid_device_limit on excess). Key creation is rate-limited per organization (api_key_create_rate_limited). Use list_api_keys to see existing keys and revoke_api_key to retire one.ConnectorNo auth
- Recursively resolves one or more direct/root packages' dependency graphs — e.g. the "dependencies" section of a package.json — up to maxDepth levels deep (default 2, max 3) and batch-checks every resolved package@version against OSV.dev, so vulnerabilities buried several levels down (which would never show up from checking direct dependencies alone) still surface. `summary` is a one-sentence, deterministic recap (packages scanned, unresolved count, vulnerable count and which roots pulled them in) — read it first. The `vulnerablePaths` field directly answers "which of my dependencies pulled this in" by naming the root package(s) responsible for each vulnerable transitive package; `nodes` has the full resolved graph (depth, parents, resolutionError) for deeper inspection. An npm alias (e.g. `"totally-safe": "npm:minimist@0.0.8"`) is followed to its real target — `actualName` names the real package that vulnerability data attaches to (`name` stays the declared/alias key) — this is NOT silently skipped, since doing so would mean a vulnerable package hides behind whatever name a project calls it. A node with `resolutionError` set (unsatisfiable range, 404, or a git/file/workspace/URL specifier — those still aren't followed, only npm: aliases are) has `isVulnerable: null`, not `false` — it was never actually scanned, so "not vulnerable" would be a fabricated clean bill of health; only trust `isVulnerable: true`/`false` once a real version was resolved and checked. Scope/limits worth knowing before trusting a "clean" result: only the "dependencies" field is followed (not devDependencies/peerDependencies/optionalDependencies); each range is resolved independently per branch via semver max-satisfying against published versions — this does NOT emulate npm/yarn's actual node_modules hoisting/dedup, so read results as "which vulnerable versions are reachable in the graph," not the exact installed layout; and the whole traversal is capped at a total node budget — check `truncated`/`truncationNote` rather than assuming a large graph was scanned exhaustively. Prefer batch_query_vulnerabilities instead when you only need to check exact packages you already have a flat list for (faster, no graph walk).ConnectorNo auth
- Recursively resolves one or more direct/root packages' dependency graphs — e.g. the "dependencies" section of a package.json — up to maxDepth levels deep (default 2, max 3) and batch-checks every resolved package@version against OSV.dev, so vulnerabilities buried several levels down (which would never show up from checking direct dependencies alone) still surface. `summary` is a one-sentence, deterministic recap (packages scanned, unresolved count, vulnerable count and which roots pulled them in) — read it first. The `vulnerablePaths` field directly answers "which of my dependencies pulled this in" by naming the root package(s) responsible for each vulnerable transitive package; `nodes` has the full resolved graph (depth, parents, resolutionError) for deeper inspection. An npm alias (e.g. `"totally-safe": "npm:minimist@0.0.8"`) is followed to its real target — `actualName` names the real package that vulnerability data attaches to (`name` stays the declared/alias key) — this is NOT silently skipped, since doing so would mean a vulnerable package hides behind whatever name a project calls it. A node with `resolutionError` set (unsatisfiable range, 404, or a git/file/workspace/URL specifier — those still aren't followed, only npm: aliases are) has `isVulnerable: null`, not `false` — it was never actually scanned, so "not vulnerable" would be a fabricated clean bill of health; only trust `isVulnerable: true`/`false` once a real version was resolved and checked. Scope/limits worth knowing before trusting a "clean" result: only the "dependencies" field is followed (not devDependencies/peerDependencies/optionalDependencies); each range is resolved independently per branch via semver max-satisfying against published versions — this does NOT emulate npm/yarn's actual node_modules hoisting/dedup, so read results as "which vulnerable versions are reachable in the graph," not the exact installed layout; and the whole traversal is capped at a total node budget — check `truncated`/`truncationNote` rather than assuming a large graph was scanned exhaustively. Prefer batch_query_vulnerabilities instead when you only need to check exact packages you already have a flat list for (faster, no graph walk).ConnectorNo auth
- 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). FEES ARE NOT MODELLED HERE: vwap_fill_price/profit_usd are GROSS of Polymarket's own taker fee (rate 0.04-0.07 by category — see polymarket_edges/fees.ts), on top of which this tool prices depth-crossing cost; a thin-margin fill that looks clean here can still be net-negative after the fee.ConnectorNo auth
- Prices Kalshi daily high-temperature markets against the NWS forecast for the market's OWN settlement station, and measures whether that forecast actually beats the market. Two modes. LIVE (default): returns the full strike ladder for one city and settlement date with market_prob (mid), forecast_prob, and edge_pp per strike, plus the settlement clause verbatim. BACKTEST (`backtest_days: N`): scores an archived gridded forecast against the market on settled days and returns brier_market vs brier_forecast with a plain-English `verdict`, so the edge is MEASURED rather than asserted. READ THE WARNINGS — they are not boilerplate. (1) These markets DO NOT settle on the NWS. They settle on The Weather Company (weather.com) at a Kalshi station code such as CLINYC, which the response quotes verbatim; so part of every edge_pp is NWS-vs-Weather-Company disagreement about the same day at the same station, which is not mispricing and not tradeable. `settlement_vs_forecast_basis_f` from backtest mode is that part as a number. (2) The station is DERIVED from the settlement clause, never from the city name: Chicago settles at MIDWAY and New York at CENTRAL PARK, so a city-centre forecast would misprice a whole ladder. A station that cannot be resolved yields rows with no forecast and a reason, never a guessed coordinate. (3) forecast_prob assumes a normal distribution around the NWS high whose width is ASSUMED, not fitted (stated in `distribution_assumption`) — run backtest mode to see whether it is calibrated. (4) edge_pp is gross: no Kalshi fees, no bid-ask. MEASURED RESULT, AND IT IS NOT THE FLATTERING ONE: on the first backtest (KXHIGHNY, 13 settled days to 2026-09-11, 58 market observations) the MARKET beat the forecast — Brier 0.1008 for the market against 0.1594 for the archived gridded forecast, lower being better. So on that sample there is NO forecast edge to sell, and a large edge_pp is more likely to be the model disagreeing with a better-informed market than an opportunity. The measured settlement-vs-forecast basis was 1.7F mean absolute over 8 pinnable days, slightly warm-biased, which is a big share of a typical edge_pp on a 2-degree bracket. Re-run backtest_days before believing any edge; if a later sample reverses this, the numbers say so. NWS is US-only, so the ~30 international Kalshi weather series (London, Paris, Tokyo) return market prices with forecast_unavailable rather than a forecast. Precipitation series are listed but not yet priced. Cities: nyc, chicago, los angeles, miami, austin, houston, denver, philadelphia — or pass `series_ticker` for any other (e.g. "KXHIGHTBOS").ConnectorNo auth
- JOIN of the official release calendar (econ data, the FOMC, FDA decisions, SEC rules) against LIVE Polymarket/Kalshi markets — which scheduled releases land in the next N hours, and which live markets resolve on them. This is a POSITIONING tool, not a speed product: results are cached like every other pack (≤ 60s TTL) and there is no push/webhook — do not use this to try to beat a release, use it to see what is coming and what is already priced. CATEGORIES: econ (CPI, Employment Situation/jobs report, GDP, PCE, PPI, retail sales, housing starts, jobless claims — via fred_release_dates per known release_id, since FRED's own cross-release calendar mostly returns recent actuals, not future dates), fed (the next FOMC meeting's rate decision, via fomc_calendar), fda (PDUFA action dates + FDA advisory-committee meetings, via pdufa_catalysts / fda_adcom_calendar), sec (SEC final rules whose own DATES clause names an effective date in the window, via federal-register recent_rules — usually finds nothing in a short window since SEC rules typically take effect 30–60 days out, which is an accurate answer, not a bug), court (ALWAYS EMPTY today — court-listener has no forward-looking scheduled-hearing calendar, only filing/termination dates, so this category returns zero releases with unsupported:true rather than fabricate one). Omit `categories` or pass "all" for every category. MATCHING AND ITS HONESTY CONTRACT: every release is returned even when it has ZERO matched markets — a release is never dropped just because nothing on Polymarket or Kalshi resolves on it (most FDA/SEC releases will show markets:[]; that is signal, not a gap). Every matched market carries resolves_on_this_release: "true" (the venue's own close/end date sits within ~36h of the release AND the question passed a subject filter — econ and fed only), "likely" (same subject filter, but the venue closes days away from the release date), or "unclear" (a keyword hit with no date to anchor against — always true for the fda category, which has no ladder structure to check a date against). matched_by names the mechanism (a Kalshi series ticker, a Polymarket search query, or an FDA keyword probe) so a caller can judge the match rather than trust a label. scheduled_at carries both `utc` and `et`; econ releases use the standing BLS/Census 8:30am ET convention (FRED's calendar itself has no clock time), FOMC decisions use the 2:00pm ET convention, and FDA/SEC dates are date_only:true (no reliable clock time exists for either). DO NOT treat a matched market as a real arbitrage or a settled fact on its own — a market question sharing tokens with a release name is not proof it settles on that release's own published number. Call resolution_audit / resolution_diff (fleet #1909) on a specific market before sizing anything here. An empty window (zero releases across every requested category) returns error:"no_releases_in_window" with a widen-the-window hint rather than an empty array — econ releases especially cluster on specific dates each month, so a 48h window often straddles a dead stretch.ConnectorNo auth
- 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.ConnectorNo auth