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524,225 tools. Updated 2026-09-06 14:34

"Understanding and Using JSON" matching MCP tools:

  • POST /tools/tool_data_transformer/run — Extracts structured JSON from raw text using a caller-supplied JSON Schema. Input: {raw_text: string, target_json_schema: object (JSON Schema draft-07)}. Output: {success, extracted_data, extraction_method, validation_passed, error}. extraction_method is one of: 'direct_parse', 'embedded_json', 'regex_extraction'. No LLM involved — pure parsing pipeline. Type coercion applied for integer/number/boolean fields. Works best with flat schemas; deeply nested structures extract less reliably via key-value pass. Cost: $0.0500 USDC per call.
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  • POST a PxWeb query to a Hagstova Føroya table and return observations as json-stat2. body must be {query:[{code, selection:{filter,values}}], response:{format:'json-stat2'}}. PxWeb rejects requests exceeding its cell limit — narrow each dimension's selection.values using codes from table_meta.
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  • POST a PxWeb query to a Statistics Greenland table and return observations as json-stat2. body must be {query:[{code, selection:{filter,values}}], response:{format:'json-stat2'}}. An empty query ({query:[]}) requests the full table but may be rejected for large tables — narrow selections using codes from table_meta.
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  • Returns the complete Trident 2D specification including grammar, syntax rules, coordinate system, containers, nodes, connections, shapes, and icon reference. Use this when you need deep understanding of the Trident DSL.
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  • List Categories List all agent categories with counts. Returns every category in the directory along with the number of agents in each. Useful for building category filters or understanding the directory's coverage areas. ### Responses: **200**: Successful Response (Success Response) Content-Type: application/json **Example Response:** ```json [ { "category": "Category", "count": 1 } ] ```
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  • Get aggregate statistics about missions on the HomeVisto platform. Returns total counts, status breakdown, and average bounty information. Useful for understanding platform activity.
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  • Convert JSON samples into TypeScript interfaces and Zod schemas, with inference caveats.

  • Validates JSON against a JSON Schema, lists violations. x402 payment required (testnet USDC).

  • 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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  • 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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  • Check subscription status, plan details, billing cycle, and feature access. Useful for understanding what the business can and cannot do on their current plan.
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  • Generate variations of an existing brand name using deterministic prefix, suffix, compound, and wordplay patterns. Returns JSON alternatives[] each with the name, the pattern used, a description, and a 0-100 brandability score. Use this to riff on a name the user already has; use namesniper_generate for brand-new AI ideas from a description. Free, no API key needed.
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  • Browse all funding categories with opportunity counts. Categories include: Grant, Construction, Goods & Services, Professional Services, Technology, Healthcare, Research, and more. Useful for understanding what types of opportunities are available. Does not count toward your monthly searches.
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  • POST a PxWeb query to a Moldova National Bureau of Statistics (Statbank) table and return observations as json-stat2. body must be {query:[{code, selection:{filter,values}}], response:{format:'json-stat2'}}. PxWeb caps responses at ~10,000 cells — narrow each dimension's values using codes from table_meta.
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  • Returns the latest stable release for each supported Vaadin major version (25, 24, 23, 14, 8, 7) with version number, release date, and whether it requires a commercial license. Useful for migration planning and understanding which versions are available.
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  • Browse profiled companies (Fortune 1000) by name or industry; ranked by overall technology-readiness signal. `industry` takes an insights industry NAME from insights_industries (e.g. "Industrial") — a different vocabulary from the catalog industry slugs find_providers uses — and matches every roster a company sits on, not just its primary. Understanding plan.
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  • Get nationwide association statistics for France. Returns total associations across all regions and departments, top regions, top departments, and overall distribution insights. Useful for understanding the French associative landscape.
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  • Convert JSON to an Excel .xlsx file using a Claix json-excel schema. Provide json_data inline or file_base64 with a .json file. Returns base64-encoded xlsx on success.
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  • Extract structured JSON from already processed plain text, HTML, or XML using a Claix txt-json schema. Send the payload in the content field (no file). Max 300,000 characters. POST /api/txt-json.
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  • One business capability: its definition, its sub-capabilities, the external authorities it cites, and WHICH catalog providers reach it with their ratings. Accepts a slug or a BC id (e.g. "payments-card-management" or "BC-1340"). Free. The per-tag edges WITH their evidence are get_capability_edges (Understanding).
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  • UNDERSTANDING — what ONE vendor's published APIs let a business DO, rolled up by capability, with the tag-level evidence under each. Answers "what is this vendor actually for" from its own contracts rather than its marketing. NOT get_provider_capabilities, which is artifact counts and agent-readiness dimensions and is free. Understanding plan.
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  • Analyze the programming language composition of a GitHub repository. Returns percentage breakdown of languages used, dominant language, and file counts per language. Use for understanding project tech stack or evaluating language distribution.
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