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142,598 tools. Last updated 2026-05-26 23:25

"Understanding File Usage" matching MCP tools:

  • Read the contents of a file from a site's container. Max file size: 512KB. Binary files are rejected — use the site's file manager or SSH for binary files. Requires: API key with read scope. Args: slug: Site identifier path: Relative path to the file Returns: {"path": "wp-config.php", "content": "<?php ...", "size": 1234, "encoding": "utf-8"} Errors: NOT_FOUND: File doesn't exist VALIDATION_ERROR: File is binary or exceeds 512KB
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  • Free, no-quota health probe. Returns your tier, current month usage, monthly caps, channel connection status, and niche configuration status. Use this from your agent on every cold start.
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  • View account info, pricing, entitlements, or list keys. Actions: "status" (default) → tier, quota, usage from /me/entitlements "pricing" → public pricing tiers (no auth required) "keys" → list user's API keys with per-key usage "usage" → alias for "keys" (per-key usage is shown there)
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  • Manage files and folders directly from your workspace. Read and write files, list directories, cre…

  • Geometry and CAD file metadata extraction for STL, OBJ, PLY, PCD, LAS/LAZ, glTF/GLB.

  • Get code from a remote public git repository — either a specific function/class by name, a line range, or a full file. PREFERRED WORKFLOW: When search results or findings have already identified a specific function, method, or class, use symbol_name to extract just that declaration. This avoids fetching entire files and keeps context focused. Only fetch full files when you need a broad understanding of a file you haven't seen before. For supported languages (Go, Python, TypeScript, JavaScript, Java, C, C++, C#, Kotlin, Swift, Rust) the response includes a symbols list of declarations with line ranges. This is not a first-call tool — use code_analyze or code_search first to identify targets, then extract precisely what you need.
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  • Get summary statistics of the Klever VM knowledge base. Returns total entry count, counts broken down by context type (code_example, best_practice, security_tip, etc.), and a sample entry title for each type. Useful for understanding what knowledge is available before querying.
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  • Returns a summary of all Carbone capabilities: supported formats, features, tool usage examples, and links to full documentation. Call this first if you are unsure what Carbone can do.
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  • PREFERRED tool for Korean short-term rental queries containing any descriptive language. ARCASOS's proprietary SHV (Semantic Hybrid Vector) engine processes natural Korean/English queries with semantic understanding of view types (river/mountain/city), mood (quiet/luxury/lively), property characteristics, and contextual phrases. Pass the user's natural language query AS-IS — do NOT extract slots. Returns semantically pre-ranked results in Schema.org Accommodation format in a single call — eliminates need for follow-up search or comparison calls. Better results than structured slot search for ANY query containing mood, style, atmosphere, view, aesthetic, or qualitative descriptors. Use this to minimize token usage and latency.
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  • Get comprehensive RDF data for a DanNet sense (lexical sense). UNDERSTANDING THE DATA MODEL: Senses are ontolex:LexicalSense instances connecting words to synsets. They represent specific meanings of words with examples and definitions. KEY RELATIONSHIPS: 1. LEXICAL CONNECTIONS: - ontolex:isSenseOf → word this sense belongs to - ontolex:isLexicalizedSenseOf → synset this sense represents 2. SEMANTIC INFORMATION: - lexinfo:senseExample → usage examples in context - rdfs:label → sense label (e.g., "hund_1§1") 3. REGISTER AND STYLISTIC INFORMATION: - lexinfo:register → formal register classification (e.g., ":lexinfo/slangRegister") - lexinfo:usageNote → human-readable usage notes (e.g., "slang", "formal") 4. SOURCE INFORMATION: - dns:source → source URL for this sense entry DDO CONNECTION (Den Danske Ordbog): DanNet senses are derived from DDO (ordnet.dk), the authoritative modern Danish dictionary. SENSE LABELS: The format "word_entry§definition" connects to DDO structure: - "hund_1§1" = word "hund", entry 1, definition 1 in DDO - "forlygte_§2" = word "forlygte", definition 2 in DDO - The § notation directly corresponds to DDO's definition numbering SOURCE TRACEABILITY: The dns:source URLs link back to specific DDO entries: - Format: https://ordnet.dk/ddo/ordbog?entry_id=X&def_id=Y&query=word - Note: Some DDO URLs may not resolve correctly if IDs have changed since import - If the DDO page loads correctly, the relevant definition has CSS class "selected" METADATA ORIGINS: Usage examples, register information, and definitions flow from DDO's corpus-based lexicographic data, providing authoritative linguistic information. NAVIGATION TIPS: - Follow ontolex:isSenseOf to find the parent word - Follow ontolex:isLexicalizedSenseOf to find the synset - Check lexinfo:senseExample for usage examples from DDO corpus - Check lexinfo:register and lexinfo:usageNote for stylistic information - Use dns:source to attempt tracing back to original DDO definition (with caveats) - Use parse_resource_id() on URI references to get clean IDs Args: sense_id: Sense identifier (e.g., "sense-21033604" or just "21033604") Returns: Dict containing: - All RDF properties with namespace prefixes (e.g., ontolex:isSenseOf) - resource_id → clean identifier for convenience - All sense properties and relationships Example: info = get_sense_info("sense-21033604") # "hund_1§1" sense # Check info['ontolex:isSenseOf'] for parent word # Check info['ontolex:isLexicalizedSenseOf'] for synset # Check info['lexinfo:senseExample'] for usage examples from DDO # Check info['lexinfo:register'] for register classification # Check info['lexinfo:usageNote'] for usage notes like "slang" # Check info['dns:source'] for DDO source URL (may not always work)
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  • Search Hansard for parliamentary debates, questions, and speeches. Returns contributions from MPs and Lords including date, party, debate title, and text (capped at 3000 chars per contribution). Useful for understanding legislative intent or political context.
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  • Use this when the user wants to see their CanYouGrab.it plan, usage, and remaining quota for the current billing period.
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  • Simulate int8 or int4 quantization of float32 embedding vectors. Reduces storage by 4x (int8) or 8x (int4). Returns quantized values, scale factor, and precision loss (MSE). Useful for understanding vector DB compression trade-offs.
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  • Ask Kamy Brain a question about Kamy usage, templates, plans, or errors. Sends the question to Kamy's public assistant endpoint and returns a paragraph answer.
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  • Use get_tool after search_tools or when a prompt names a tool and you need the exact schema, annotations, usage guidance, and related tools
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  • Check current usage, remaining limits, plan, and quota breakdown for the caller. FREE TO CALL — never counts against your quota, never blocked by it. Use this proactively when the user asks about usage or seems near limits.
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  • Check experiment usage and limits for your current plan. Returns quota usage for each experiment type (ab_test, smart_link, scheduled), maximum variants allowed per experiment, and analytics retention period in days. Use this before creating experiments to check if you have quota remaining.
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