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307,088 tools. Last updated 2026-07-27 21:33

"An overview or definition of a code interpreter" matching MCP tools:

  • Look up an airport by city name (e.g. "Tokyo", "New York", "London") OR by 3-letter IATA code (e.g. "JFK", "LHR"). City lookup uses a bundled map of the top ~150 international hubs; cities with multiple airports return all primary ones. For airports not in the bundle, pass an IATA code or use the aviationstack pack for full-text name/country search.
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  • Start here when building an application. Returns an overview of what the AdCritter platform offers and a catalog of feature guides you can query with the adcritter_guidance tool to learn how to build each part of the app. Call adcritter_guidance(key) for any feature area to get detailed building instructions with API endpoints and response shapes.
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  • Indian bank branch lookup by IFSC code. Resolves an 11-character IFSC code (printed on Indian cheques and bank statements) to the bank name, branch, address, city, district, state, MICR code, SWIFT code, and contact number, plus whether the branch supports the NEFT, RTGS, UPI, and IMPS payment rails. India banking / fund-transfer routing data via the open Razorpay IFSC dataset (keyless). Also returns an offline format_valid check of the code structure. NOTE: this validates and resolves the IFSC code itself — it does NOT verify a bank account or account holder. Examples: ifsc_lookup({ ifsc: "HDFC0CAGSBK" }), ifsc_lookup({ ifsc: "sbin0000691" }) (case and spaces are forgiven).
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  • Get a complete overview of all senses for a Danish word in a single call. Replaces the common pattern of calling get_word_synsets → get_synset_info per result → get_word_synonyms, collapsing 5-15 HTTP round-trips into one SPARQL query. Only returns synsets where the word is a primary lexical member (i.e. the word itself has a direct sense in the synset), excluding multi-word expressions that merely contain the word as a component. Args: word: The Danish word to look up Returns: List of dicts, one per synset, each containing: - synset_id: Clean synset identifier (e.g. "synset-3047") - label: Human-readable synset label - definition: Synset definition (may be truncated with "…") - ontological_types: List of dnc: type URIs - synonyms: List of co-member lemmas (true synonyms only) - hypernym: Dict with synset_id and label of the immediate broader concept, or null - lexfile: WordNet lexicographer file name (e.g. "noun.animal"), or null if absent Example: overview = get_word_overview("hund") # Returns list of 4 synsets, the first being: # {"synset_id": "synset-3047", # "label": "{hund_1§1; køter_§1; vovhund_§1; vovse_§1}", # "definition": "pattedyr som har god lugtesans ...", # "ontological_types": ["dnc:Animal", "dnc:Object"], # "synonyms": ["køter", "vovhund", "vovse"], # "lexfile": "noun.animal"} # Pass synset_id to get_synset_info() for full JSON-LD data on any result: # full_data = get_synset_info(overview[0]["synset_id"])
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  • Validate a TypeScript intent definition without generating Swift. Runs the full Axint validation pipeline (134 diagnostic rules) and returns a JSON array of diagnostics: { severity: 'error'|'warning', code: 'AXnnn', line: number, column: number, message: string, suggestion?: string }. Returns an empty array [] when validation passes. Use: use for TypeScript DSL diagnostics before Swift output; use swift.validate for existing Swift. Inputs: source is TypeScript DSL text; strictness options affect diagnostics only and never emit Swift. Effects: read-only diagnostics; writes no files and uses no network.
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  • Render a Mermaid diagram definition and return the image with metadata. The definition should be valid Mermaid syntax (e.g. flowchart, sequence, class, ER, state, or Gantt diagram). Returns a list of content blocks: the rendered image plus a JSON text block with metadata including a mermaid.live edit link for opening the diagram in a browser editor. Args: definition: Mermaid diagram definition text. filename: Output filename without extension. format: Output format — ``"png"`` (default), ``"svg"``, or ``"pdf"``. download_link: If True, return a temporary download URL path (/images/{token}) that expires after 15 minutes; if False, return inline image bytes. Defaults to True (URL) — set ``DIAGRAMS_INLINE_DEFAULT=true`` on the server to flip the default. SVG/PDF and PNGs larger than the inline limit always use a download link.
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  • Google AI Overview answers and cited sources via the Apify Google AI Overview API, hosted MCP.

  • Interpret lab values against ACLM-optimized ranges. Returns deprescription signals.

  • Wait for an SMS verification code / OTP to arrive on a Palmyr phone number you own, and return the parsed code. Blocks up to timeout_s (default 60, max 90) checking every ~2s — one call replaces hand-rolled polling of phone_read_messages during account signups and 2FA flows. Messages that arrived up to lookback_s seconds (default 10) BEFORE the call also match, so a code that landed early is not missed — pass lookback_s=0 when reusing a number across signups so a stale code can't be re-served. Default extraction handles standalone 4-8 digit codes, 'code is/code:' tokens, and Google-style G-XXXXXX; pass pattern to override (max 256 chars; a pattern that blows its per-match budget is dropped mid-wait and pattern_timeout: true is reported). Returns { found: true, code, message_text } on a hit or { found: false, waited_s } on timeout (not an error — just call again). Costs 0.02 USDC, paid per-action via x402.
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  • Get a snapshot of the quantum computing landscape — no parameters needed. Use when the user asks broad questions like "how's the quantum job market?", "what are trending topics?", or wants an overview of the quantum computing industry. Returns: total active jobs, top hiring companies, jobs by role type, papers published this week, total researchers tracked, and trending technology tags. For specific job/paper/researcher searches, use the dedicated search tools instead.
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  • Returns runnable code that creates a Solana keypair. Solentic cannot generate the keypair for you and never sees the private key — generation must happen wherever you run code (the agent process, a code-interpreter tool, a Python/Node sandbox, the user's shell). The response includes the snippet ready to execute. After running it, fund the resulting publicKey and call the `stake` tool with {walletAddress, secretKey, amountSol} to stake in one call.
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  • Lookup FDA device classification details by product code. Returns device name, device class (I/II/III), medical specialty, regulation number, review panel, submission type, and definition. Requires: product code (3-letter code from 510(k), PMA, or device product listings). Related: fda_product_code_lookup (cross-reference across 510(k) and PMA), fda_search_510k (clearances for this product code), fda_search_pma (PMA approvals for this product code).
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  • Get an overview of the Velvoite regulatory corpus. Returns document counts by source, regulation family, entity type, urgency distribution, obligation summary, and date range. Call this FIRST to orient yourself before running queries. No parameters needed.
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  • Returns runnable code that creates a Solana keypair. Solentic cannot generate the keypair for you and never sees the private key — generation must happen wherever you run code (the agent process, a code-interpreter tool, a Python/Node sandbox, the user's shell). The response includes the snippet ready to execute. After running it, fund the resulting publicKey and call the `stake` tool with {walletAddress, secretKey, amountSol} to stake in one call.
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  • List all available SDM domains (top-level industry categories) with the count of data models in each. Use this as the entry point when the user wants an overview of what sectors are covered, or before calling list_models_by_domain. No parameters required. Example: list_domains({})
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  • Get one principle cluster by stable slug. Returns the cluster definition, shared rationale, and the full set of member principles (slug + title) so the caller can pivot into principles.get without a second list call. WHEN TO CALL: the user has already named a specific cluster (e.g. 'delegation', 'visibility', 'trust', 'orchestration') OR you have a slug from a prior clusters.list / principles.list response and need its full definition + member principles. The response embeds member principle slugs + titles already, so DO NOT loop principles.get over each member to get a cluster overview — read the response. WHEN NOT TO CALL: the user is describing a topic, failure mode, or keyword in natural language (call principles.search instead); the user wants to discover which clusters exist (call clusters.list); the user wants the definition of one specific principle (call principles.get directly). Idempotent + cacheable per slug. Returns 404-shaped error_payload on unknown slug — the slug must match exactly the value emitted by clusters.list, with no normalization.
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  • Returns the canonical Arco definition, related terms, and source URL for any Lexicon term. Supports fuzzy matching — "autonomous company" resolves to "Autonomous Business". Use this tool when you need a precise definition. Use suggest_terms instead when you have a block of text and want to discover which terms apply.
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  • Get complete product information about Savvly, an SEC-registered security offering longevity protection — use it whenever the user asks what Savvly is, how it works, its fees, eligibility, or payouts, or wants an overview. Pass `section` to focus the answer (default 'all'). It renders an interactive product overview card the user expects to see. These facts come from Savvly's own current records; the response includes primary sources (e.g. SEC filings) for reference.
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  • Get the structure (Data Structure Definition) of one ILOSTAT dataset: its ordered dimensions and, for each, the valid codes. Use this to learn how to build the dot-separated SDMX key for get_data. The key positions correspond to the dimensions in order; an empty position is a wildcard. Common dimensions are REF_AREA (ISO3 country code, e.g. "USA", "FRA"), FREQ (A=annual, Q=quarterly, M=monthly), SEX, AGE, and MEASURE. Always call this before get_data. Example: dataflow_structure({ dataflow_id: "DF_SDG_0852_SEX_AGE_RT" }).
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  • Public (no auth): describe what Cabgo is. Returns the full product catalog — what kinds of apps an operator can launch, pricing, who Cabgo is for, and how to onboard. Use ONLY when the user explicitly asks what Cabgo is, what it does, or wants an overview. **Do NOT call this as a pre-step before cabgo_create_my_app** — when the user wants to create / launch an app, go directly to cabgo_create_my_app without fetching context first.
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  • Validate whether a US medical code exists, is current, and is billable in the active bundled release. Returns a discriminated status — valid_billable, valid_not_billable, valid_header, or terminated — with a `whyNot` explaining non-billable and terminated cases (e.g. "valid ICD-10-CM category but not billable — submit a more specific child code"). This is the detail a coder needs before submitting a claim. Auto-detects the system from the code's shape; pass an explicit `system` to disambiguate. A non-billable or terminated code is a successful result with a whyNot, not an error — only a code that exists in no bundled system raises unknown_code.
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  • Plain-language definitions of industry terms in a service category (e.g. SEER2, AFUE, AHRI match). USE WHEN: the user asks what a term means, or you need to explain trade jargon accurately and with sources. ARGS: `category`; optionally `term` (a slug) for one definition — omit to list. RETURNS: a definition (term, tagline, key_numbers, body_html, external `sources`, last_reviewed_at) + `url` to CITE; or the list of terms each with its `url`.
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