IA-QA Data & Dev — 36 tools

Dev utilities for agents: JSON/YAML/CSV, schema validation, encoding, text & time. Free, no key.

我该使用它吗

质量与安全性

B
描述质量
96%
模式完整度
99%
命名质量
85%
投毒风险
60%
权限匹配度
80%
协议合规性
100%

发现(9)

  • HIGHTool poisoning patterns detected
  • MEDIUMTool 'rate_tool' description contains placeholder text在 rate_tool 中
  • MEDIUMTool 'lorem_ipsum' description contains placeholder text在 lorem_ipsum 中
  • LOWTool 'flatten_json' description lacks action verb在 flatten_json 中
  • LOWTool 'base64_encode' description lacks action verb在 base64_encode 中
  • LOWTool 'url_encode' suggests web access but openWorldHint=false在 url_encode 中
  • LOWTool 'url_decode' suggests web access but openWorldHint=false在 url_decode 中
  • INFOTool description contains placeholder or incomplete text在 rate_tool 中
  • INFOTool description contains placeholder or incomplete text在 lorem_ipsum 中

基于对工具定义和协议合规性的自动分析。

上下文开销

~7,350token 数(工具定义)
~1.2 KB典型响应大小
对注意力有显著影响(占 128k 上下文窗口的 5.74%)

这是每次将服务器的工具加载到模型上下文窗口时所消耗的大致 token 数。数值越高,可用于其他任务的注意力就越少。

安装

一键安装

将以下内容添加到你的 `claude_desktop_config.json` 文件中:

{
  "mcpServers": {
    "ia-qa-data": {
      "url": "https://www.ia-qa.com/mcp/data"
    }
  }
}

远程端点

https://www.ia-qa.com/mcp/datastreamable-http

它能做什么

工具清单

工具(36)

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🟢find_tool(query, category, with_schema, max_results)

Search available MCP tools by keyword or category before calling them. Returns matching tool names, descriptions, and optionally their inputSchemas. Call this when you are unsure which tool to use or want to explore the catalogue. Categories: data, encoding, text, llm, qa, rag, dev, security, web.

输入模式

{
  "type": "object",
  "properties": {
    "query": {
      "type": "string",
      "description": "Keyword(s) to search in tool name and description (e.g. \"cors\", \"token\", \"vector\", \"json\")"
    },
    "category": {
      "type": "string",
      "description": "Optional: filter by category — data | encoding | text | llm | qa | rag | dev | security | web"
    },
    "with_schema": {
      "type": "boolean",
      "description": "Set true to include inputSchema in results (default: false)"
    },
    "max_results": {
      "type": "number",
      "description": "Maximum tools to return (default 10, max 50). Results are ranked by IDF-weighted relevance, so common words like \"test\" do not inflate the list."
    }
  },
  "required": [
    "query"
  ]
}

输出模式

{
  "type": "object",
  "properties": {
    "tool": {},
    "score": {},
    "query": {},
    "category": {},
    "count": {
      "type": "number"
    },
    "total_matches": {
      "type": "number"
    },
    "truncated": {
      "type": "boolean"
    },
    "tools": {
      "type": "array"
    },
    "hint": {}
  },
  "additionalProperties": true
}
🟢diff_text(a, b, context)

Compute a unified line-by-line diff between two text strings (LCS algorithm). Returns added/removed/unchanged line counts and formatted diff hunks with configurable context lines (0–20). Use to compare versions of prompts, configs, code snippets, or any text where you need to see exactly what changed.

输入模式

{
  "type": "object",
  "properties": {
    "a": {
      "type": "string",
      "description": "Original (before) text"
    },
    "b": {
      "type": "string",
      "description": "Modified (after) text"
    },
    "context": {
      "type": "number",
      "description": "Context lines around each change (0–20, default: 3)"
    }
  },
  "required": [
    "a",
    "b"
  ]
}

输出模式

{
  "type": "object",
  "properties": {
    "diff": {
      "type": "string"
    },
    "added": {
      "type": "number"
    },
    "removed": {
      "type": "number"
    },
    "unchanged": {
      "type": "number"
    }
  },
  "additionalProperties": true
}
🟢rate_tool(tool_name, score, comment)

Give honest usage feedback on an IA-QA MCP tool. Provide a score (1-5) and a comment. Rate low (1-2) if the tool was wrong, irrelevant, or a poor fit; rate high (4-5) only if it genuinely solved your need. Ratings are read by the IA-QA maintainers and are not published, one vote per agent and tool a month. Comments are screened before storing: one carrying a credential is not stored and personal data is replaced by placeholders — describe what happened rather than what a model should do. Skip rating routine successes — we want signal, not praise. Example: rate_tool({ tool_name: "format_json", score: 2, comment: "Tried to pretty-print a JSON5 file, it rejected trailing commas — not usable for my case." })

输入模式

{
  "type": "object",
  "properties": {
    "tool_name": {
      "type": "string",
      "description": "Name of the MCP tool to rate (e.g. \"format_json\", \"shield_analyze\")"
    },
    "score": {
      "type": "number",
      "description": "Rating from 1 (poor) to 5 (excellent)",
      "minimum": 1,
      "maximum": 5
    },
    "comment": {
      "type": "string",
      "description": "Strongly encouraged — explain what you were trying to do and whether the tool got you there. Be specific about what was missing, wrong, or a poor fit. This is the most valuable part of the rating. Up to 2000 chars are stored; go over and the response says so (truncated: true) — send the remainder as a second call rather than assuming it landed."
    }
  },
  "required": [
    "tool_name",
    "score"
  ]
}

输出模式

{
  "type": "object",
  "properties": {
    "ok": {
      "type": "boolean"
    },
    "tool_name": {},
    "score": {},
    "comment": {},
    "truncated": {
      "type": "boolean"
    },
    "stored_chars": {
      "type": "number"
    },
    "rated_at": {
      "type": "string"
    },
    "message": {
      "type": "string"
    }
  },
  "additionalProperties": true
}
🟢validate_email(email)

Validate an email address against RFC 5322 syntax before storing it, sending a transactional email, or adding it to a mailing list. Returns { valid, email } — use this to avoid bounces and malformed data.

输入模式

{
  "type": "object",
  "properties": {
    "email": {
      "type": "string",
      "description": "Email address to validate"
    }
  },
  "required": [
    "email"
  ]
}

输出模式

{
  "type": "object",
  "properties": {
    "valid": {
      "type": "boolean"
    },
    "email": {},
    "reason": {
      "type": "string"
    }
  },
  "additionalProperties": true
}
🟢decode_jwt(token)

Decode a JWT (JSON Web Token) and return its header and payload without verifying the signature. Also reports whether the token is expired and the exact expiry date. Use to inspect claims (sub, iss, exp, roles) during debugging or when integrating with an auth provider.

输入模式

{
  "type": "object",
  "properties": {
    "token": {
      "type": "string",
      "description": "The JWT string to decode (header.payload.signature)"
    }
  },
  "required": [
    "token"
  ]
}

输出模式

{
  "type": "object",
  "properties": {
    "header": {},
    "payload": {},
    "expired": {},
    "expiresAt": {},
    "note": {
      "type": "string"
    }
  },
  "additionalProperties": true
}
🟢timestamp_convert(input)

Convert between Unix timestamps (seconds or milliseconds) and ISO-8601 / UTC date strings. Auto-detects epoch vs. millisecond format. Omit input to get the current time. Returns iso, unix_s, unix_ms, utc, date, and time fields.

输入模式

{
  "type": "object",
  "properties": {
    "input": {
      "description": "Unix timestamp (number, seconds or ms) or ISO date string. Omit to get the current time."
    }
  }
}

输出模式

{
  "type": "object",
  "properties": {
    "iso": {
      "type": "string"
    },
    "unix_s": {
      "type": "number"
    },
    "unix_ms": {
      "type": "number"
    },
    "utc": {
      "type": "string"
    },
    "date": {
      "type": "string"
    },
    "time": {
      "type": "string"
    }
  },
  "additionalProperties": true
}
🟢cron_parse(expression)

Parse a cron expression into a human-readable schedule description. Supports standard 5-field cron (minute hour day month weekday).

输入模式

{
  "type": "object",
  "properties": {
    "expression": {
      "type": "string",
      "description": "Cron expression (e.g., \"0 9 * * 1-5\", \"*/15 * * * *\")"
    }
  },
  "required": [
    "expression"
  ]
}

输出模式

{
  "type": "object",
  "properties": {
    "expression": {},
    "fields": {
      "type": "object"
    },
    "human_readable": {
      "type": "string"
    }
  },
  "additionalProperties": true
}
🟢count_code_lines(input, language)

Count lines of code: total, code lines, comment lines, blank lines, and comment density. Supports JS/TS, Python, Java/C/C++, Ruby, Go, Shell, HTML/XML, and CSS.

输入模式

{
  "type": "object",
  "properties": {
    "input": {
      "type": "string",
      "description": "Source code to analyze"
    },
    "language": {
      "type": "string",
      "description": "Language hint: \"js\", \"ts\", \"py\", \"java\", \"c\", \"rb\", \"go\", \"sh\", \"html\", \"css\" (auto-detect if omitted)"
    }
  },
  "required": [
    "input"
  ]
}

输出模式

{
  "type": "object",
  "properties": {
    "total_lines": {},
    "code_lines": {},
    "comment_lines": {},
    "blank_lines": {},
    "comment_density": {},
    "code_to_comment_ratio": {
      "type": "string"
    },
    "language": {}
  },
  "additionalProperties": true
}
🟢lint_commit_message(message, strict)

Validate a git commit message against the Conventional Commits spec (feat, fix, docs, style, refactor, test, chore, ci, perf, build). Returns compliance score, breaking change detection, and actionable suggestions.

输入模式

{
  "type": "object",
  "properties": {
    "message": {
      "type": "string",
      "description": "Git commit message to validate"
    },
    "strict": {
      "type": "boolean",
      "description": "Enforce strict rules: max 72-char subject, imperative mood check (default: false)"
    }
  },
  "required": [
    "message"
  ]
}

输出模式

{
  "type": "object",
  "properties": {
    "valid": {
      "type": "boolean"
    },
    "score": {
      "type": "number"
    },
    "is_breaking_change": {
      "type": "boolean"
    },
    "type": {},
    "scope": {},
    "subject": {},
    "has_body": {
      "type": "boolean"
    },
    "checks": {}
  },
  "additionalProperties": true
}
🟢env_parse(input)

Parse a .env file content into a JSON object. Handles quoted values (single and double), inline comments, export prefix, and escaped sequences (\n, \t inside double quotes). Returns all key-value pairs. Use in CI/CD pipelines, agent config loaders, or when processing dotenv files programmatically.

输入模式

{
  "type": "object",
  "properties": {
    "input": {
      "type": "string",
      "description": ".env file content to parse (e.g. the output of `cat .env`)"
    }
  },
  "required": [
    "input"
  ]
}

输出模式

{
  "type": "object",
  "properties": {
    "vars": {},
    "count": {
      "type": "number"
    }
  },
  "additionalProperties": true
}
🟢openapi_validate(input)

Validate the structure of an OpenAPI 3.x specification (JSON or YAML). Checks required top-level fields (openapi, info.title, info.version, paths), validates each operation (responses, operationId uniqueness), detects undeclared $ref components, and flags missing 2xx responses. Returns a PASS/FAIL verdict, a 0–100 compliance score, and a list of errors and warnings with JSON-pointer locations. Use before publishing an API spec or generating SDK code.

输入模式

{
  "type": "object",
  "properties": {
    "input": {
      "type": [
        "string",
        "object",
        "array"
      ],
      "description": "The OpenAPI 3.x spec — a JSON string, a YAML string, or the already-parsed spec object."
    }
  },
  "required": [
    "input"
  ]
}

输出模式

{
  "type": "object",
  "properties": {
    "verdict": {},
    "score": {
      "type": "number"
    },
    "errors": {},
    "warnings": {},
    "stats": {
      "type": "object"
    }
  },
  "additionalProperties": true
}
🟢generate_slug(input, separator)

Convert any string into a URL-friendly slug: lowercase, ASCII-normalized (é→e), special characters removed, spaces replaced with hyphens. Use for generating SEO-friendly URL paths, file names, or identifier keys from user-provided titles or labels.

输入模式

{
  "type": "object",
  "properties": {
    "input": {
      "type": "string",
      "description": "String to slugify"
    },
    "separator": {
      "type": "string",
      "description": "Separator character (default: \"-\")"
    }
  },
  "required": [
    "input"
  ]
}

输出模式

{
  "type": "object",
  "properties": {
    "slug": {}
  },
  "additionalProperties": true
}
🟢format_json(input, indent)

Validate and pretty-print a string that is ALREADY valid JSON. Strict by design — it is a validity gate: valid JSON comes back formatted, anything else is rejected with the exact parse error. It never repairs, completes, or guesses. NOT for: plain text or prose (will fail), JSON embedded in markdown/prose (use extract_json_from_text first), JS objects (JSON.stringify them first), YAML (use yaml_to_json).

输入模式

{
  "type": "object",
  "properties": {
    "input": {
      "type": "string",
      "description": "A raw JSON string, e.g. '{\"key\":\"value\"}'. Must already parse as JSON — plain text or truncated JSON is rejected, not repaired."
    },
    "indent": {
      "type": "number",
      "description": "Indent size (default: 2)"
    }
  },
  "required": [
    "input"
  ]
}

输出模式

{
  "type": "object",
  "properties": {
    "formatted": {
      "type": "string"
    },
    "valid": {
      "type": "boolean"
    }
  },
  "additionalProperties": true
}
🟢parse_csv(input, delimiter, header)

Parse a CSV string into a JSON array of objects (or raw arrays). Full RFC 4180: quoted fields may contain the delimiter, embedded newlines (the Excel/Sheets multi-line cell), and doubled quotes. Custom delimiters supported. An unterminated quote is rejected with its position rather than parsed into corrupted rows. Use when processing spreadsheet exports, data imports, or structured text pipelines where the source is CSV. Supports up to 200 KB.

输入模式

{
  "type": "object",
  "properties": {
    "input": {
      "type": "string",
      "description": "CSV content to parse"
    },
    "delimiter": {
      "type": "string",
      "description": "Field delimiter character (default: \",\")"
    },
    "header": {
      "type": "boolean",
      "description": "Treat the first row as headers (default: true)"
    }
  },
  "required": [
    "input"
  ]
}

输出模式

{
  "type": "object",
  "properties": {
    "rows": {
      "type": "array"
    },
    "headers": {
      "type": "array"
    },
    "columns": {
      "type": "number"
    },
    "row_count": {
      "type": "number"
    }
  },
  "additionalProperties": true
}
🟢extract_json_path(input, path)

Extract a value from a JSON string using dot-notation path (e.g., "user.address.city", "items.0.name", "meta.tags"). Supports array index access via numeric path segments.

输入模式

{
  "type": "object",
  "properties": {
    "input": {
      "type": [
        "string",
        "object",
        "array"
      ],
      "description": "The JSON to traverse — a JSON string, or the object/array itself."
    },
    "path": {
      "type": "string",
      "description": "Dot-notation path, e.g. \"user.address.city\" or \"items.0.name\""
    }
  },
  "required": [
    "input",
    "path"
  ]
}

输出模式

{
  "type": "object",
  "properties": {
    "value": {},
    "type": {},
    "path": {}
  },
  "additionalProperties": true
}
🟢json_schema_validate(value, schema)

Validate a JSON value against a JSON Schema (draft-07 subset). Supports type, required, properties, items, enum, const, pattern, format (email/uri/date/date-time/uuid), minimum/maximum, minLength/maxLength, minItems/maxItems, uniqueItems, additionalProperties, anyOf, allOf, oneOf, not, and local $ref (#/definitions/…, #/$defs/…). A schema using a keyword outside that list (patternProperties, if/then, dependencies, a remote $ref…) is never reported valid: the keyword is named in `unevaluated_keywords`. Returns all validation errors with dot-notation paths.

输入模式

{
  "type": "object",
  "properties": {
    "value": {
      "type": [
        "string",
        "object",
        "array"
      ],
      "description": "The JSON value to validate — a JSON string, or the value itself."
    },
    "schema": {
      "type": [
        "string",
        "object",
        "array"
      ],
      "description": "The JSON Schema — a JSON string, or the schema object itself."
    }
  },
  "required": [
    "value",
    "schema"
  ]
}

输出模式

{
  "type": "object",
  "properties": {
    "valid": {
      "type": "boolean"
    },
    "error_count": {
      "type": "number"
    },
    "errors": {
      "type": "array"
    }
  },
  "additionalProperties": true
}
🟢flatten_json(input, mode, separator)

Flatten a nested JSON object to single-level dot-notation keys (e.g. {"a":{"b":1}} → {"a.b":1}), or unflatten dot-notation keys back to a nested object. Supports custom separators.

输入模式

{
  "type": "object",
  "properties": {
    "input": {
      "type": [
        "string",
        "object",
        "array"
      ],
      "description": "The JSON to flatten or unflatten — a JSON string, or the object itself."
    },
    "mode": {
      "type": "string",
      "description": "\"flatten\" (default) or \"unflatten\""
    },
    "separator": {
      "type": "string",
      "description": "Key separator (default: \".\")"
    }
  },
  "required": [
    "input"
  ]
}

输出模式

{
  "type": "object",
  "properties": {
    "result": {},
    "key_count": {
      "type": "number"
    },
    "max_depth": {
      "type": "array"
    }
  },
  "additionalProperties": true
}
🟢xml_to_json(input, parse_values, ignore_attrs, attr_prefix)

Convert an XML string to a JSON object. Supports attributes, nested elements, arrays, CDATA, and namespaces. Options: parse numbers, parse booleans, ignore attributes.

输入模式

{
  "type": "object",
  "properties": {
    "input": {
      "type": "string",
      "description": "XML string to convert"
    },
    "parse_values": {
      "type": "boolean",
      "description": "Auto-parse numbers and booleans (default: true)"
    },
    "ignore_attrs": {
      "type": "boolean",
      "description": "Ignore XML attributes (default: false)"
    },
    "attr_prefix": {
      "type": "string",
      "description": "Prefix for attribute keys (default: \"@_\")"
    }
  },
  "required": [
    "input"
  ]
}

输出模式

{
  "type": "object",
  "properties": {
    "result": {},
    "key_count": {
      "type": "number"
    }
  },
  "additionalProperties": true
}
🟢mock_from_schema(schema, count, seed)

Generate realistic mock data from a JSON Schema. Supports all common types (string, number, integer, boolean, array, object, null), format hints (email, date, date-time, uri, uuid), enum, const, and nested schemas. Perfect for testing MCP tools with realistic data.

输入模式

{
  "type": "object",
  "properties": {
    "schema": {
      "type": [
        "string",
        "object",
        "array"
      ],
      "description": "The JSON Schema to generate from — a JSON string, or the schema object itself."
    },
    "count": {
      "type": "number",
      "description": "Number of mock objects to generate (default: 1, max: 20)"
    },
    "seed": {
      "type": "string",
      "description": "Optional seed string for deterministic output (uses first char codes)"
    }
  },
  "required": [
    "schema"
  ]
}

输出模式

{
  "type": "object",
  "properties": {
    "count": {
      "type": "number"
    },
    "results": {}
  },
  "additionalProperties": true
}
🟢json_to_csv(input, delimiter, headers)

Convert a JSON array of objects to CSV format. Automatically detects columns from all object keys. Handles quoting and escaping per RFC 4180.

输入模式

{
  "type": "object",
  "properties": {
    "input": {
      "type": [
        "string",
        "object",
        "array"
      ],
      "description": "The array of objects to convert — a JSON string, or the array itself."
    },
    "delimiter": {
      "type": "string",
      "description": "Column delimiter (default: \",\")"
    },
    "headers": {
      "type": "boolean",
      "description": "Include header row (default: true)"
    }
  },
  "required": [
    "input"
  ]
}

输出模式

{
  "type": "object",
  "properties": {
    "csv": {
      "type": "string"
    },
    "rows": {
      "type": "number"
    },
    "columns": {
      "type": "number"
    },
    "column_names": {}
  },
  "additionalProperties": true
}
🟢json_diff(before, after, max_depth)

Compute a deep structural diff between two JSON values. Returns added, removed, and changed keys with dot-notation paths. Like git diff but for JSON objects — perfect for API response regression testing. Arrays are not compared blindly by position: the same elements in a different order collapse to a single "reordered" change, and an array of records sharing a stable identity field (id, uuid, key, name…) is matched by that field, so paths read [id=42] and a moved record is not reported as N rewrites.

输入模式

{
  "type": "object",
  "properties": {
    "before": {
      "type": [
        "string",
        "object",
        "array"
      ],
      "description": "The original JSON (before) — a JSON string, or the value itself."
    },
    "after": {
      "type": [
        "string",
        "object",
        "array"
      ],
      "description": "The modified JSON (after) — a JSON string, or the value itself."
    },
    "max_depth": {
      "type": "number",
      "description": "Max nesting depth to recurse (default: 10)"
    }
  },
  "required": [
    "before",
    "after"
  ]
}

输出模式

{
  "type": "object",
  "properties": {
    "identical": {
      "type": "boolean"
    },
    "added": {
      "type": "boolean"
    },
    "removed": {
      "type": "boolean"
    },
    "modified": {
      "type": "boolean"
    },
    "total_changes": {
      "type": "number"
    },
    "changes": {
      "type": "array"
    }
  },
  "additionalProperties": true
}
🟢json_to_yaml(input, indent)

Convert a JSON object to clean, human-readable YAML. Handles nested objects, arrays, multiline strings, and special characters. No external dependencies.

输入模式

{
  "type": "object",
  "properties": {
    "input": {
      "type": [
        "string",
        "object",
        "array"
      ],
      "description": "The JSON to convert to YAML — a JSON string, or the value itself."
    },
    "indent": {
      "type": "number",
      "description": "Indentation size in spaces (default: 2)"
    }
  },
  "required": [
    "input"
  ]
}

输出模式

{
  "type": "object",
  "properties": {
    "yaml": {},
    "lines": {
      "type": "number"
    }
  },
  "additionalProperties": true
}
🟢yaml_to_json(input, multi)

Parse a YAML string and return the equivalent JSON value. The reverse of json_to_yaml. Supports nested objects, arrays, anchors, aliases, multi-document streams, and all scalar types. Use when processing config files, CI/CD pipeline definitions, or OpenAPI specs authored in YAML.

输入模式

{
  "type": "object",
  "properties": {
    "input": {
      "type": "string",
      "description": "YAML string to parse"
    },
    "multi": {
      "type": "boolean",
      "description": "If true, parse all documents in a multi-document stream and return an array (default: false)"
    }
  },
  "required": [
    "input"
  ]
}

输出模式

{
  "type": "object",
  "properties": {
    "documents": {},
    "count": {
      "type": "number"
    },
    "json": {}
  },
  "additionalProperties": true
}
🟢json_schema_generate(input, required_all)

Infer a JSON Schema (draft-07) from a sample JSON value. Detects types, required fields, array item shapes, nested objects, and common string formats (email, uri, date, date-time, uuid). Returns a ready-to-use schema compatible with json_schema_validate. Use when you have a sample API response or LLM output and want to auto-generate a validation schema for CI/CD testing.

输入模式

{
  "type": "object",
  "properties": {
    "input": {
      "type": [
        "string",
        "object",
        "array"
      ],
      "description": "The sample JSON value to infer the schema from — a JSON string, or the value itself."
    },
    "required_all": {
      "type": "boolean",
      "description": "Mark all detected object properties as required (default: true)"
    }
  },
  "required": [
    "input"
  ]
}

输出模式

{
  "type": "object",
  "properties": {
    "type": {
      "type": "string"
    },
    "format": {},
    "items": {
      "type": "object"
    },
    "schema": {
      "type": "object"
    }
  },
  "additionalProperties": true
}
🟢text_stats(input)

Compute comprehensive statistics for any text: character count (with and without spaces), word count, line count, sentence count, paragraph count, and estimated reading time in minutes. Sentence counting is abbreviation-aware — titles (Mr., Dr.), acronyms (U.S., i.e., p.m.), initials, decimals, URLs and emails do not end a sentence, and a text with no terminal punctuation still counts as one. Use for validating form field lengths, evaluating LLM output verbosity, or content auditing.

输入模式

{
  "type": "object",
  "properties": {
    "input": {
      "type": "string",
      "description": "The text to analyse"
    }
  },
  "required": [
    "input"
  ]
}

输出模式

{
  "type": "object",
  "properties": {
    "chars": {},
    "chars_no_space": {},
    "words": {},
    "lines": {},
    "sentences": {},
    "paragraphs": {},
    "reading_time_minutes": {}
  },
  "additionalProperties": true
}
🟢regex_test(pattern, input, flags)

Test a regular expression pattern against an input string and return all matches with their index positions and named capture groups. Use for validating user inputs, extracting structured data from text, or debugging regex patterns. Supports flags g, i, m, s, u, y. The match runs in an isolated thread with a 500 ms budget: a pattern that blows up (catastrophic backtracking, e.g. "(a+)+$") comes back as redos_detected:true — a real ReDoS verdict on your pattern — instead of hanging.

输入模式

{
  "type": "object",
  "properties": {
    "pattern": {
      "type": "string",
      "description": "Regular expression pattern (without delimiters)"
    },
    "input": {
      "type": "string",
      "description": "The string to test against (max 50 KB)"
    },
    "flags": {
      "type": "string",
      "description": "Regex flags: g (global), i (case-insensitive), m (multiline), s (dotAll) — default: \"\""
    }
  },
  "required": [
    "pattern",
    "input"
  ]
}

输出模式

{
  "type": "object",
  "properties": {
    "pattern": {},
    "flags": {},
    "matched": {},
    "match_count": {
      "type": "number"
    },
    "matches": {},
    "redos_detected": {
      "type": "boolean"
    },
    "elapsed_ms": {
      "type": "number"
    },
    "verdict": {},
    "note": {}
  },
  "additionalProperties": true
}
🟢lorem_ipsum(paragraphs, sentences_per_paragraph, words_per_sentence)

Generate Lorem Ipsum placeholder text for UI mockups, design prototypes, or test data population. Configurable paragraphs (1–10), sentences per paragraph (1–20), and approximate words per sentence (3–30).

输入模式

{
  "type": "object",
  "properties": {
    "paragraphs": {
      "type": "number",
      "description": "Number of paragraphs to generate (1–10, default: 1)"
    },
    "sentences_per_paragraph": {
      "type": "number",
      "description": "Sentences per paragraph (1–20, default: 5)"
    },
    "words_per_sentence": {
      "type": "number",
      "description": "Approximate words per sentence (3–30, default: 10)"
    }
  }
}

输出模式

{
  "type": "object",
  "properties": {
    "paragraphs": {},
    "paragraph_count": {
      "type": "number"
    }
  },
  "additionalProperties": true
}
🟢case_convert(input, to)

Convert a string between naming conventions: camelCase, PascalCase, snake_case, kebab-case, UPPER_SNAKE_CASE, dot.case, Title Case. Essential for code generation and refactoring.

输入模式

{
  "type": "object",
  "properties": {
    "input": {
      "type": "string",
      "description": "String to convert (e.g., \"myVariableName\", \"my-css-class\")"
    },
    "to": {
      "type": "string",
      "description": "Target case: \"camel\", \"pascal\", \"snake\", \"kebab\", \"upper_snake\", \"dot\", \"title\""
    }
  },
  "required": [
    "input",
    "to"
  ]
}

输出模式

{
  "type": "object",
  "properties": {
    "result": {},
    "from_words": {},
    "target_case": {}
  },
  "additionalProperties": true
}
🟢generate_uuid(count)

Generate one or more cryptographically random UUID v4 identifiers. Use this when you need unique IDs for test fixtures, database records, session tokens, or any scenario requiring a guaranteed-unique string. Returns up to 100 UUIDs in one call.

输入模式

{
  "type": "object",
  "properties": {
    "count": {
      "type": "number",
      "description": "Number of UUIDs to generate (1–100, default: 1)"
    }
  }
}

输出模式

{
  "type": "object",
  "properties": {
    "uuids": {},
    "count": {
      "type": "number"
    }
  },
  "additionalProperties": true
}
🟢hash_text(input, algorithm)

Compute a cryptographic hash of a text string. Use when you need to verify data integrity, generate content fingerprints, hash passwords (prefer SHA-256+), or produce a fixed-length digest of any input. Supports SHA-256 (default), SHA-512, SHA-1, and MD5.

输入模式

{
  "type": "object",
  "properties": {
    "input": {
      "type": "string",
      "description": "Text to hash"
    },
    "algorithm": {
      "type": "string",
      "description": "Hash algorithm: sha256 (default), sha512, sha1, md5"
    }
  },
  "required": [
    "input"
  ]
}

输出模式

{
  "type": "object",
  "properties": {
    "hash": {},
    "algorithm": {},
    "input_length": {
      "type": "number"
    }
  },
  "additionalProperties": true
}
🟢base64_encode(input)

Encode a UTF-8 string to Base64. Use when you need to embed binary data, multi-line text, or special characters safely inside JSON fields, HTTP headers, or data URIs.

输入模式

{
  "type": "object",
  "properties": {
    "input": {
      "type": "string",
      "description": "Text to encode"
    }
  },
  "required": [
    "input"
  ]
}

输出模式

{
  "type": "object",
  "properties": {
    "encoded": {
      "type": "string"
    }
  },
  "additionalProperties": true
}
🟢base64_decode(input)

Decode a Base64 string back to UTF-8 text. Use for inspecting Base64-encoded API responses, JWT payload claims, config file values, or attachment data.

输入模式

{
  "type": "object",
  "properties": {
    "input": {
      "type": "string",
      "description": "Base64 string to decode"
    }
  },
  "required": [
    "input"
  ]
}

输出模式

{
  "type": "object",
  "properties": {
    "decoded": {}
  },
  "additionalProperties": true
}
🟢url_encode(input, mode)

Percent-encode a string for safe use in URLs. Call this before programmatically building query strings, path segments, or form-encoded bodies to prevent injection and malformed URLs.

输入模式

{
  "type": "object",
  "properties": {
    "input": {
      "type": "string",
      "description": "String to URL-encode"
    },
    "mode": {
      "type": "string",
      "description": "\"component\" (default) or \"full\" for encodeURI behavior"
    }
  },
  "required": [
    "input"
  ]
}

输出模式

{
  "type": "object",
  "properties": {
    "encoded": {}
  },
  "additionalProperties": true
}
🟢url_decode(input)

Decode a percent-encoded URL string back to plain text. Use when parsing query parameters from raw URLs or when displaying encoded values to users.

输入模式

{
  "type": "object",
  "properties": {
    "input": {
      "type": "string",
      "description": "URL-encoded string to decode"
    }
  },
  "required": [
    "input"
  ]
}

输出模式

{
  "type": "object",
  "properties": {
    "decoded": {}
  },
  "additionalProperties": true
}
🟢color_convert(input)

Convert a color between HEX, RGB, and HSL formats. Use when translating design tokens between CSS notations, verifying color accessibility, or normalizing color values from user input. Accepts #rrggbb, #rgb, rgb(r,g,b), or hsl(h,s%,l%).

输入模式

{
  "type": "object",
  "properties": {
    "input": {
      "type": "string",
      "description": "Color value to convert, e.g. \"#ff6b6b\", \"rgb(255,107,107)\", \"hsl(0,100%,71%)\""
    }
  },
  "required": [
    "input"
  ]
}

输出模式

{
  "type": "object",
  "properties": {
    "input": {},
    "hex": {},
    "rgb": {
      "type": "string"
    },
    "hsl": {
      "type": "string"
    },
    "r": {},
    "g": {},
    "b": {}
  },
  "additionalProperties": true
}
🟢number_base_convert(input, from_base, to_base)

Convert numbers between bases: decimal, binary, octal, hexadecimal, or any base 2–36. Auto-detects 0x, 0b, 0o prefixes.

输入模式

{
  "type": "object",
  "properties": {
    "input": {
      "type": "string",
      "description": "Number to convert (e.g., \"255\", \"0xFF\", \"0b1010\", \"0o77\")"
    },
    "from_base": {
      "type": "number",
      "description": "Source base 2–36 (auto-detects prefix if omitted)"
    },
    "to_base": {
      "type": "number",
      "description": "Target base 2–36 (omit to get all common bases)"
    }
  },
  "required": [
    "input"
  ]
}

输出模式

{
  "type": "object",
  "properties": {
    "result": {
      "type": "string"
    },
    "decimal": {},
    "from_base": {},
    "to_base": {},
    "binary": {
      "type": "string"
    },
    "octal": {
      "type": "string"
    },
    "hexadecimal": {
      "type": "string"
    }
  },
  "additionalProperties": true
}

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