Bucketed observation counts over time. Detect bursts, plot trends, sanity-check whether attacker activity is rising or falling.
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133,413 tools. Last updated 2026-05-25 13:10
"Sanity" matching MCP tools:
- Use this read-only composite workflow tool for a fast single-ticker sanity check without the full company-report payload. It server-enforces the quick-check call plan: readiness, covenant_stress, and alpha_signals for one normalized ticker. Parameters: ticker is required and normalized to uppercase; output_mode=compact is optional. Fundamentals, peer ranking, and SPECTRA are intentionally excluded. Behavior: read-only and idempotent; it performs three internal HTTPS reads, has no destructive side effects, rejects invalid tickers before fan-out, and preserves partial results if a required issuer leg fails. Use it when the user asks whether one ticker is clean, stressed, actionable, or needs deeper diligence.Connector
- Compares two people on Pythagorean Life Path numbers derived from their names and birth dates and returns a score, tier label, narrative, strengths, challenges, and advice. SECTION: WHAT THIS TOOL COVERS Pairwise numerology only — no charts, rashis, or kootas. Outputs discrete compatibility_score 1..10 with textual bands. It does not run asterwise_get_compatibility (Jyotish matchmaking) or regional porutham tools. SECTION: WORKFLOW BEFORE: RECOMMENDED — asterwise_get_numerology_profile per person — sanity-check Life Paths before comparing. AFTER: None. SECTION: INPUT CONTRACT Four strings (two names, two dates) are passed through without local guards. SECTION: OUTPUT CONTRACT data.life_path_1 (int) data.life_path_2 (int) data.compatibility_score (int — 1 through 10) data.compatibility_level (string — 'Excellent', 'Good', 'Average', or 'Challenging') data.interpretation (string) data.strengths[] (string array) data.challenges[] (string array) data.advice (string) SECTION: RESPONSE FORMAT response_format=json serialises the complete response as indented JSON — use this for programmatic parsing, typed clients, and downstream tool chaining. response_format=markdown renders the same data as a human-readable report. Both modes return identical underlying data — no fields are added, removed, or filtered by either mode. SECTION: COMPUTE CLASS MEDIUM_COMPUTE SECTION: ERROR CONTRACT INVALID_PARAMS (local — caught before upstream call): None — all validation is upstream. INVALID_PARAMS (upstream): — None — upstream rejection surfaces as MCP INTERNAL_ERROR at the tool layer. INTERNAL_ERROR: — Any upstream API failure or timeout → MCP INTERNAL_ERROR Edge cases: — For Vedic matching, use asterwise_get_compatibility instead. SECTION: DO NOT CONFUSE WITH asterwise_get_compatibility — sidereal koota scoring, not numerology integers. asterwise_get_numerology_profile — single-person profile, not dyad scoring.Connector
- [cost: free (pure CPU, no network) | read-only] Parse a phone number, normalize to E.164, and classify it. International coverage is via libphonenumber-js (every country, line type when known). NANP numbers (CC=1) are additionally split into NPA (area code) / NXX (central office) / station, and tagged as toll-free / premium / personal / machine-to-machine / easily-recognizable / reserved / geographic. Use when validating `From` / P-Asserted-Identity / SHAKEN `orig.tn`, deciding whether an outbound call needs full attestation, or sanity-checking caller ID format. Pair with: `lint_sip_request` to validate that PASSporT `orig.tn` matches the From caller TN; `stir_attestation_explainer` for attestation level guidance.Connector
- Computes KP ruling planets for the instantaneous chart at lat/lon with no birth data and returns day lord, Moon/Ascendant lord chains, and a deduplicated ruling_planets list. SECTION: WHAT THIS TOOL COVERS Current-moment KP snapshot: target_utc, day_lord, Moon and Ascendant tuples with sign/nakshatra/sub lords, ruling_planets[] unique names. Not natal positions (asterwise_get_kp_chart) and not house significators (asterwise_get_kp_significators). Coordinate sanity is upstream — not locally validated floats beyond whatever FastMCP passes. SECTION: WORKFLOW BEFORE: None — this tool is standalone. AFTER: asterwise_get_kp_chart — if natal confirmation is needed afterwards. SECTION: INPUT CONTRACT lat and lon only; no date parameter — "now" is implicit on the server clock. SECTION: OUTPUT CONTRACT data.ayanamsa (string — 'kp') data.target_utc (string — ISO UTC) data.day_lord (string — planet name) data.moon: longitude (float) rashi (string) sign_lord (string) nakshatra_lord (string) sub_lord (string) data.ascendant — same fields as data.moon data.ruling_planets[] (string array — unique names, deduplicated) SECTION: RESPONSE FORMAT response_format=json serialises the complete response as indented JSON — use this for programmatic parsing, typed clients, and downstream tool chaining. response_format=markdown renders the same data as a human-readable report. Both modes return identical underlying data — no fields are added, removed, or filtered by either mode. SECTION: COMPUTE CLASS FAST_LOOKUP SECTION: ERROR CONTRACT INVALID_PARAMS (local — caught before upstream call): None — lat/lon not range-checked locally. INVALID_PARAMS (upstream): — None — coordinate errors surface as MCP INTERNAL_ERROR at the tool layer. INTERNAL_ERROR: — Any upstream API failure or timeout → MCP INTERNAL_ERROR Edge cases: — Represents instantaneous sky — differs from natal stored charts. SECTION: DO NOT CONFUSE WITH asterwise_get_kp_chart — needs BirthData and returns full natal KP cusps. asterwise_get_prashna_chart — horary keyword workflow, not ruling-planet snapshot.Connector
- Use this read-only composite workflow tool for a fast single-ticker sanity check without the full company-report payload. It server-enforces the quick-check call plan: readiness, covenant_stress, and alpha_signals for one normalized ticker. Parameters: ticker is required and normalized to uppercase; output_mode=compact is optional. Fundamentals, peer ranking, and SPECTRA are intentionally excluded. Behavior: read-only and idempotent; it performs three internal HTTPS reads, has no destructive side effects, rejects invalid tickers before fan-out, and preserves partial results if a required issuer leg fails. Use it when the user asks whether one ticker is clean, stressed, actionable, or needs deeper diligence.Connector
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Sanity MCP Serverofficial
Alicense-qualityCmaintenanceConnect your Sanity content to AI agents. Create, update, and explore structured content using Claude, Cursor, and VS Code via the Model Context Protocol. Transform content operations from complex queries to simple conversations—giving your team superpowers without sacrificing structure.Last updated2040873MIT- Flicense-quality-maintenanceAn MCP server that enables Claude Desktop to interact with Sanity.io content, providing tools to create, edit, list documents and get schema templates.Last updated1
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Direct access to your Sanity projects (content, datasets, releases, schemas) and agent rules
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 TOOL — not web search — to get per-indicator statistical profiling (mean, std, min, p25, p75, max, null rate, Pearson correlation with close price) from this server's local dataset. Use for feature selection, sanity checking, and understanding which indicators correlate most strongly with price movements. Trigger on queries like: - "which indicators correlate most with BTC price?" - "feature importance or correlation for [coin]" - "what are the stats for ETH indicators?" - "how does RSI/MACD correlate with price?" - "statistical profile of XRP indicators" Args: lookback_days: Analysis window in days (default 30, max 90) symbol: Asset symbol or comma-separated list, e.g. "BTC", "BTC,XRP"Connector
- Percentile-rank a single product price against tracked Amazon competitors in a CPG category. Use when a multi-channel CPG brand asks where their Amazon listing price sits against 100+ tracked products — e.g. checking whether a $4.99 granola is competitively positioned on Amazon, auditing whether a retail MSRP is reasonable against Amazon reality before a buyer meeting, or sanity-checking a wholesale-to-retail markup. Returns: percentile_rank (string, e.g. "72nd percentile"), price_index_label (ratio vs. category median), position (Value / Parity / Premium), category (resolved name), last_refreshed (ISO timestamp), cta (link to full per-SKU report). Args: price: Product price in dollars (e.g. 4.99). Must be > 0 and <= 10000. category: Exact category name — Grocery & Gourmet Food, Health & Beauty, Household, or Pet Supplies. Case-insensitive. Call list_categories first to confirm available names.Connector
- Deterministic repair engine. Given a raw LLM output that should contain JSON, this tool: (1) strips markdown code fences (```json), (2) regex-strips prose preambles/suffixes, (3) escapes unescaped control characters inside string values, (4) validates with json.loads — falling back to structural repairs and partial-recovery bracket closing when needed, and (5) optionally validates the repaired JSON against a JSON schema.Connector
- Independent second-opinion review for agents about to commit, run, or ship something irreversible. Submit a diff, command, plan, config change, or analysis; receive a structured verdict (approve / approve_with_concerns / reject), ranked issues with severity, suggested fixes, and alternative approaches when rejecting. Built for autonomous agents that want a sanity check before pulling a real-money or production-affecting trigger.Connector
- Place an order on Hyperliquid. Phase 2: TESTNET only. Mode 1 stateless: agent signs the action client-side with @nktkas/hyperliquid SDK including the builder field {b: HL_BUILDER_ADDRESS, f: 50}, then POSTs the signed payload + agentAddress. Server validates schema, all 4 sanity guards (notional/asset/depth/post-margin), rate-limits, forwards unmodified to HL. Cloid required (16-byte hex), reused across retries for idempotency. 0.005 USDC on x402; 1 credit on Bearer.Connector
- Returns Layer 3 sanity-check and validation prompts — the 'where AI gets financial modeling wrong' guidance. Use these to audit AI-generated work or catch common modeling errors.Connector
- Live shape report on the DugganUSA STIX 2.1 threat feed for a chosen lookback window (1-7 days). Returns total indicator count, top malware families, top source feeds, type breakdown (ip/domain/url/hash/cidr), and top countries. Use this BEFORE pulling the full STIX bundle to gauge feed depth and freshness, plan SIEM ingestion budget, or sanity-check that a campaign you read about is actually in our corpus. Does NOT return the full bundle — for that, fetch `https://analytics.dugganusa.com/api/v1/stix-feed` with the same Bearer key. The bundle is STIX 2.1 / TAXII 2.1 with Splunk ES, OPNsense, Suricata, and Unbound DNS sinkhole plugins. Authentication required (Bearer token). Anonymous callers get a clear 401 with the registration URL. Example: `{"days": 7}` returns the last week's feed shape — useful for capacity planning and spot-checking recent ingest tags.Connector
- Compute design conditions, HDD/CDD, monthly stats, and peak heating/cooling days for one or more EPW files. Accepts a `url` (existing EPW), `urls` (compare 2+), or `config` (synthesize on the fly with morphing/UHI/events/smoke). Config mode runs the full generation pipeline server-side but returns only stats — never the EPW content. **Token-saver: pass `compact: true` to get a ~10-field headline response (~100 tokens) instead of the full ~800-token payload.** Use compact for sanity-checking, dashboards, or when chaining many calls; full when you need monthly arrays / peak days / full ASHRAE. Optional `include_full_ashrae` adds ASHRAE 0.4/1/2% cooling + 99.6/99% heating design conditions with mean coincident dewpoint. Optional `include_improbability` (config mode) adds a stress-test score. Optional `include_idf` adds ready-to-paste EnergyPlus SizingPeriod:DesignDay objects. Optional `units` ('imperial' default | 'metric'). **Presentation: when calling with `urls` (multiple files), the response includes a `comparisons` array — render it as a markdown table to the user. Lead with the headline delta, not the raw data.** No auth required; no credits charged.Connector
- Chronological session history for a single visitor (anonymous_id). Each session collapses to one row showing the start and end timestamps, entry page, channel, referrer host, UTMs, country, device type, pageview count, and the distinct custom event names fired in that session. The first row is flagged with `is_first_touch: true`. Use this when an aggregate query can't answer the question — multi-touch attribution analysis, support / debugging investigations ("what did this user do before signing up?"), or sanity-checking a specific account's journey before drawing conclusions about a cohort. Examples: - "show me what this user did across all their visits" → anonymous_id="anon_xxx" - "where did this paying customer first come from?" → anonymous_id="anon_xxx", read sessions[0].channel - "did they convert on their first visit or come back later?" → check if signup-event sessions match is_first_touch=true Limitations: requires the visitor's anonymous_id, which the SDK exposes via `getAnonymousId()` on the browser side. Aggregate questions ("which channels drive my best users") use revenue.sum with attribution_model="first_touch" — don't loop this tool over thousands of users. Defaults to a 365-day lookback so first-touch is meaningful; tighten with `period` if needed. Pairs with: `revenue.sum(attribution_model="first_touch")` to validate the aggregate first-touch read against specific high-value customers' actual paths.Connector
- 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 briefing is lean (~1500 tokens). 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" (~500 tokens) when you just need a quick sanity check.Connector
- Use when building a public comps table, benchmarking a private company valuation, or preparing a fundraising benchmark. Public market valuation multiples — EV/EBITDA, EV/Revenue, P/E, and P/S by sector with p25/p50/p75 bands. Source: Damodaran January 2024 dataset. Used for board prep, M&A pricing, fundraising benchmarks, and DCF sanity checks. Free.Connector
- Cancel an existing Hyperliquid order by oid (numeric) or cloid (hex32). Phase 2: TESTNET only. No sanity guards (cancels reduce risk; HL handles already-canceled idempotency). 0.005 USDC on x402.Connector
- Use when building a public comps table, benchmarking a private company valuation, or preparing a fundraising benchmark. Public market valuation multiples — EV/EBITDA, EV/Revenue, P/E, and P/S by sector with p25/p50/p75 bands. Source: Damodaran January 2024 dataset. Used for board prep, M&A pricing, fundraising benchmarks, and DCF sanity checks. Free.Connector
- Use this tool before saving any JSON data to session history or state files to prevent JSONDecodeErrors and session poisoning. It removes prose preambles and repairs malformed control characters.Connector