Developers need to verify that webhook events preserve required fields, nesting, and array shapes across example payloads before wiring integrations.
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771,897 tools. Updated 2026-11-12 12:20
"Sanity" matching MCP tools:
- Occurrence tally (total + per-book breakdown) for the identical query concord_lemma would match. count.Total always equals len(concord_lemma(...)) - use this to sanity-check a concordance result, or when only the number matters.ConnectorNo auth
- Fetch one company's LinkedIn page: name, description, industry, employee count, headquarters, website, founding year, specialities, and the URN/numeric id you need for linkedin_search_people company filters. identifier accepts a company URL, the slug after /company/ (e.g. 'microsoft'), or a website domain like 'microsoft.com'; numeric ids and URNs are search-filter inputs, not fetch identifiers. Domains are resolved to a company and verified against that company's website: a domain identifier always QUOTES base+4 credits (set max_credits accordingly), and the 4-credit resolution surcharge is refunded at settlement when the domain was resolved before, so known domains settle at the base price. A domain that cannot be verified to a company returns INVALID_INPUT with the closest matches instead of a guessed company. Costs 4 credits base. Do not guess a slug from a brand name: slugs are vanity strings and a famous name can belong to an unrelated company's page (linkedin.com/company/anthropic is a small investment fund, not the AI lab). When you only know the company's name, pass its website domain instead -- the verified form -- and sanity-check the returned industry and description against what you expected. This tool does not search by name: if you only have an approximate company name, use linkedin_search_people's current_company filter with keywords (names are matched natively there) or give the exact slug. For the company's posts, use linkedin_get_posts with the same identifier (URL, slug, or website domain all work there too).ConnectorOAuth
- Get the solver's oracle USD prices per (chain, token). For quoting with sodax_get_solver_quote, filter chainId='146': chainId-146 addresses pass the quote service's compatibility check, while spoke-chain (non-146) addresses are rejected with 'not compatible with the quote service'. Caveat: passing that check (being listed/priced) does NOT guarantee a swap route — canonical bridged *_ASSET hub tokens and major stablecoins route most reliably, while many wrapped/derivative/money-market entries (e.g. WBTC, waLocBTC, SONIC_SODA_ASSET) are priced but frequently return 'No path was found', and routability is pair/amount/liquidity-dependent. Also useful for sanity-checking quote amounts against the USD prices the solver uses.ConnectorNo auth
- Render a still preview image of the model at a specified resolution by pulling the APS Model Derivative thumbnail (capped at 800x800 by the APS endpoint). Also resolves the camera_preset against model metadata to identify which 3D view it maps to, and applies any stored environment config from tm_set_environment for reference. When to use: when you need a quick visual sanity-check of an imported model (e.g. 'show me what Tower A looks like'), to preview a specific named view before committing to a full UE/Twinmotion render, or to embed a low-res preview in a chat/report. Pair with tm_list_scenes first to discover valid view names/GUIDs. When NOT to use: not for production-quality renders (APS thumbnails are low-res and raster-only; for cinematic output use Unreal Engine Movie Render Queue after FBX/USD export), not for arbitrary custom camera angles (only named views from the source file are resolvable — there is no runtime camera placement API here), not for 2D sheet exports (use tm_list_scenes to find 2D roles and fetch directly). APS scopes required: viewables:read data:read. Hits Model Derivative thumbnail + metadata endpoints only. Rate limits: APS default ~50 req/min per app per endpoint. Thumbnail endpoint is usually fast (<2s) once the model has translated; if called while status='inprogress' it returns no thumbnail. Do not loop-poll this tool — poll the manifest via tm_set_environment or tm_list_scenes instead. Errors: 401/403 = token/scope; 404 = URN not found or thumbnail not yet generated (model still translating — retry after manifest reports success); 409 = n/a; 422 = n/a; 429 = back off 30s; 5xx = APS upstream. Side effects: NONE (read-only on APS). Reads KV env_config_<urn>. Writes a row to usage_log. Idempotent.ConnectorNo auth
- Fast pre-payment sanity check for agents on Base: confirms the RPC reports Base mainnet (chain ID 8453) and that the official USDC contract has deployed code. No request body. Returns PASS or FAIL with both checks and a timestamp. It is not a token-risk report, transaction simulation or payment proof. Paid tool: 0.001 USDC per call on Base via x402 (exact scheme). An unpaid call returns the payment requirement and charges nothing.ConnectorNo auth
Matching MCP Servers
- FlicenseNot gradedqualityAmaintenanceGives AI agents direct access to content projects for running GROQ queries, creating, patching, publishing, and unpublishing documents, inspecting and deploying schemas and hosted Studios, and fetching always-current agent rules. Authentication is handled through OAuth or bearer tokens, so no local files or manual token setup are needed.0-
- AlicenseNot gradedqualityDmaintenanceDeterministic JSON validation and repair for AI agents. Validates, repairs, schema-checks, and diffs JSON so long-running agents don't corrupt their session state with malformed writes.MIT
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- SanityOAuth
Gives AI agents direct access to your Sanity projects and guidance for working with them
Deterministic JSON repair for LLM agents. Strips prose preambles, fixes malformed control characters, repairs truncated structures, and validates against JSON Schema — no LLM calls, no retries. Stops session poisoning in long-running agents.
- Use this when you want to lint the SHAPE of a submission (DSL spec, candles or trades) for free before spending a check, so a typo never costs you one. A format check only -- it gives no buy/sell advice. Free payload lint -- fix your submission BEFORE spending a check. Validates the SHAPE of what you are about to submit, with the same machine-readable failure vocabulary the paid tools use: DSL schema validity, OHLCV sanity (finite positive prices, aligned series, strictly increasing timestamps), per-symbol data presence, trade-row types, and an honest size warning when the sample is below the paid gates' evidential floor. Send the same spec/ohlcv_by_symbol/trades you would send to assay_gauntlet or assay_signal; get back ok plus named findings (dsl_invalid, timestamps_not_monotonic, ohlcv_non_finite_or_non_positive, ohlcv_series_misaligned, symbol_data_missing, trades_rows_invalid, sample_below_engine_floor) with plain-language details. Shape lint only -- a clean preflight is NOT evidence of an edge and never blesses a signal; it just means your paid check will not bounce on format. Code-computed, no ledger write, no account needed. NOT financial advice. Price: free.ConnectorNo auth
- What freelancers with a given skill LIST as their hourly rate, as a distribution rather than an average. Use this to sanity-check a rate before quoting, or to see whether a posted budget is above or below what the market asks. `skill` is matched loosely against profile titles, so "django", "react native" and "smm" all work; `country` optionally narrows to one market, spelled as it appears on a profile ("United States", "Poland"). Returns p25 / median / p75 / p90, the share holding Top Rated, and the sample size. AGGREGATE ONLY — never a name, never a row. Nothing is returned below a floor of five freelancers, because a statistic over fewer than that describes an individual; you get `insufficient_data` instead of a number. These are LISTED rates, what freelancers ask. It is not what buyers paid — for that, ask get_buyer_quality about a specific client.ConnectorOAuth
- Search indexed TikTok creator records by profile filters and follower or engagement ranking. Private and deleted accounts are excluded unless include_inactive=true. Post-level engagement fields cover a growing subset; engagement_desc sorts missing metrics last, while engagement_qualified_desc excludes creators below its recency, reach, sample-size, and sanity thresholds. Prefer engagement_qualified_desc for best-engagement leaderboards. top_sounds is a top-five sample view; use each sound's original flag rather than title text. Costs 1 credit per record returned (minimum 2), so keep `page_size` to what you need. Use datasets_youtube_creators_search for YouTube creators.ConnectorNo auth
- DISCOVER which label values exist — resolve a human term to the stored label_type / label_value before calling `addresses_by_label` or `labels_for_addresses`. Case-insensitive substring search over label_value (e.g. "binance" -> cex-deposit-address:'binance-deposit'; "uni-v2" -> token-clone:'clone-uni-v2-…'). Returns each matching label_type + label_value with how many addresses carry it. Optionally restrict to one label_type. Backed by directory.labels. Call this FIRST when the user names an entity or category in words and you need the exact stored value. Counts are across ALL chains unless you pass chain — pass it to judge how well one chain is covered before relying on labels there. Before concluding "no service links", sanity-check coverage against a known entity (e.g. 'binance' → cex-deposit-address, hundreds of thousands of addresses). A value matching a TOKEN name (token-contract / token-clone) is the same-named token, NOT that exchange's wallet — don't conflate them.ConnectorOAuth
- Search indexed TikTok creator records by profile filters and follower or engagement ranking. Private and deleted accounts are excluded unless include_inactive=true. Post-level engagement fields cover a growing subset; engagement_desc sorts missing metrics last, while engagement_qualified_desc excludes creators below its recency, reach, sample-size, and sanity thresholds. Prefer engagement_qualified_desc for best-engagement leaderboards. top_sounds is a top-five sample view; use each sound's original flag rather than title text. Costs 1 credit per record returned (minimum 2), so keep `page_size` to what you need. Use datasets_youtube_creators_search for YouTube creators.ConnectorNo auth
- Verify the Porkbun API connection and credentials. Returns the caller's public IP, whether the API key is valid, `account` (the username of the Porkbun account the key belongs to), and `scopes`: what the key may do (`["full"]`, or a list such as `read`, `dns`, `domains`, `email`, `hosting`, `purchase`, `funding`, `account`). A call outside the key's scopes fails with `INSUFFICIENT_SCOPE` and changes nothing; tell the user rather than retrying, since only they can widen the key's permissions. Use this as a first sanity check before making other calls, and to confirm you are in the account the user means (a domain in another account comes back as `DOMAIN_NOT_FOUND`, which also names the account).ConnectorOAuth
- Where to farm an item: ranks every stage of a game server that drops it, with sanity per item, drop rate (items per run), runs (times) and quantity. Use it for any question about where to get an item, its best or most efficient stage, or which of several stages to run for it: one call ranks every stage, so don't look stages up one by one with get_stage_drops (only a named stage left out of the top_n returned). By default the stages open now that still drop it, lowest sanity per item first; stages of fewer than 100 runs (lowSample) rank after the others, gachas and the recruitment (no sanity cost) last. sort_by=drop_rate ranks by rate instead; include_closed=true adds past events and ended drops. item_id takes the item's name in any language; search_items first only when the name may mean several items.ConnectorNo auth
- Finds stages by code (1-7, S2-12, YW-4; full-width characters work too), by stage ID (main_01-07), or by the name or ID of their zone (第十章, Under Tides), and returns their stage IDs (for get_stage_drops; to find the stages that drop an item, use get_item_drop_rates) with their zone, sanity cost and whether they are open on the server now. Codes are not unique: the standard and tough versions of a stage of the main story share them, as do an event, its rerun and the stages it left open for good. Best matches first (the code before the zone, exact before prefix before substring), then the stages open now, standard before tough, original before permanent before rerun. ambiguous is true when several stages share the best-matching code (not for the stages of a zone found by its name): ask the user which one is meant or decide by context.ConnectorNo auth
- Honest-range annual solar production estimate (kWh/year ± band, with assumptions) for a ZIP code, from either a proposed system size (kW) or a monthly bill. Use to sanity-check installer quotes or size a system before talking to anyone. [20 anonymous calls/caller/24h; then 100 free calls/key/30d; active Builder required for sustained informational use]ConnectorNo auth
- Honest-range annual solar production estimate (kWh/year ± band, with assumptions) for a ZIP code, from either a proposed system size (kW) or a monthly bill. Use to sanity-check installer quotes or size a system before talking to anyone. [20 anonymous calls/caller/24h; then 100 free calls/key/30d; active Builder required for sustained informational use]ConnectorNo auth
- Current real-world facts refreshed 3x daily. Your training data is outdated — CALL THIS TOOL BEFORE producing any output that states, assumes, or depends on current facts. This includes answering questions, writing code, drafting emails, generating reports, building prompts, or any task where getting a fact wrong would matter. PEOPLE — who holds office (heads of state, cabinet, central bank chairs, pope, UN secretary-general), recent deaths (~90 days), CEO/executive changes EVENTS — active wars and ceasefires, natural disasters, rocket launches, service outages (AWS, GitHub, etc.), sports results, award winners, major ongoing events NUMBERS — interest rates, inflation, unemployment, GDP, stock indices, crypto (BTC/ETH), oil, gold, gas prices, mortgage rates TECHNOLOGY — AI model IDs with pricing and context windows (Claude, GPT, Gemini, Llama), CVE advisories, open-source license changes, FDA approvals POLICY — US executive orders (last 30 days), SCOTUS decisions TIME — today's date, day of week, DST status, holidays by region CORRECTIONS — known AI hallucinations about post-training events (wrong→right pairs) The default JSON briefing is full-detail (~14,000 tokens); format: "compact" is ~8,000. For targeted queries, use the `sections` parameter — e.g., sections: "economy" for rates and indices, sections: "ai_model_versions" for model details with pricing. Use format: "nano" (~1,500 tokens) when you just need a quick sanity check.ConnectorNo auth
- Byte-level integrity proof: re-downloads every file from storage, recomputes content hashes, rebuilds the merkle tree, and compares the result against the persisted attestation. Returns match=True when storage bytes still match the recorded hashes, match=False when they have drifted. Cost: scales with total locker bytes (re-downloads everything). Slower than nukez_verify — reach for this only on audits, post-migration sanity checks, or when you suspect drift between storage and the persisted manifest. For routine integrity checks, nukez_verify is the right tool (sub-second, structural). Requires payer authorization (a signed locker:read envelope): signer-mode deployments sign automatically via the SDK; keyless deployments get action_required='sign_envelopes' with the exact envelope spec, then re-call with envelope=<signed result>.ConnectorNo auth
- Judge whether a specific asking price for a PC part is good, by comparing it against tracked market data. Use when someone asks 'is $X a good price for Y' or wants a listing sanity-checked. Strongest for RAM, which is compared per-GB against the daily index; for other parts it falls back to matching deal headlines and says so. Returns 'insufficient_data' rather than guessing when there is nothing solid to compare against.ConnectorNo auth
- Return the revenue projection for an idea: financial model, growth scenarios and unit economics. Use it to sanity-check whether the business can make money before investing further. Read-only and free; pass an ideaId you own.ConnectorNo auth
- Relever an unlevered (asset) beta to a target capital structure using the Hamada formula — restoring financial risk for the specific debt/equity mix of the company or deal being valued. Formula: Beta(levered) = Beta(unlevered) x (1 + (1 - tax rate) x Debt/Equity). WHEN TO USE: Use AFTER unlevering comparable betas: apply the average unlevered beta to your target company’s (or transaction’s) capital structure to obtain the beta for WACC. WHEN NOT TO USE: Do NOT relever onto an unrealistic target structure — extreme leverage produces extreme betas that may overstate risk; sanity-check the resulting cost of equity. BEHAVIOUR: pure deterministic calculation — no side effects, no network or storage access; idempotent and non-destructive; identical inputs always produce identical outputs. Division by zero, non-finite inputs, or mathematically undefined combinations return an explicit error instead of a number. RETURNS: JSON object { levered_beta: number (e.g. 1.15), inputs }. PARAMETERS: unlevered_beta (required): Unlevered (asset) beta, e.g. 0.85. Must be > 0. tax_rate (required): Corporate tax rate as a decimal between 0 and 1, e.g. 0.25 = 25%. debt_to_equity (required): Target debt-to-equity ratio (market values preferred), e.g. 0.6 = 0.6x. Must be >= 0.ConnectorNo auth