Toolora

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Document processing, data conversion, and web content APIs for AI agents. All tools are free via MCP. Also available as a paid x402 Agent API (Stellar XLM or Solana USDC, no API key required). Tools: extract text from PDFs, merge PDFs, generate QR codes, convert CSV to/from JSON, count words/stats, and fetch + clean any public URL with Mozilla Readability.

Status: Healthy
Last Tested: 2026-03-31 10:30
Transport: Streamable HTTP
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Available Tools

12 tools

count_wordsInspect

Count words, characters, sentences, and paragraphs in a block of text. Also returns estimated reading time. Useful for checking document stats, validating content length, or summarising text metrics.

ParametersJSON Schema

Name	Required	Description	Default
`text`	Yes	The text to analyse.

csv_to_jsonInspect

Convert a CSV string into a JSON array of objects. The first row is treated as column headers by default. Handles quoted fields, embedded commas, and CRLF line endings. Useful for processing spreadsheet exports, data files, and tabular data.

ParametersJSON Schema

Name	Required	Description	Default
`csv`	Yes	The CSV data as a string.
`headers`	No	Whether the first row contains column names (default: true).

excel_to_jsonInspect

Parse an Excel file (.xlsx, .xls, .csv, .ods) and return all sheets as JSON arrays of objects. Column headers from the first row become object keys. Returns a map of sheet name to row array, plus total row count.

ParametersJSON Schema

Name	Required	Description	Default
`filename`	Yes	Filename with extension (e.g., 'data.xlsx') — required for format detection.
`fileBase64`	Yes	The Excel or CSV file contents encoded as a base64 string.

extract_docx_textInspect

Extract all plain text from a Microsoft Word (.docx) file. Accepts the file as a base64-encoded string. Returns the full text, paragraph count, word count, and character count. Works with files from Microsoft Word, Google Docs, and LibreOffice.

ParametersJSON Schema

Name	Required	Description	Default
`filename`	No	Optional filename for format validation.
`fileBase64`	Yes	The .docx file contents encoded as a base64 string.

extract_pdf_textInspect

Extract all plain text from a PDF file. Accepts the file as a base64-encoded string. Returns the text content, page count, word count, and character count. Useful for reading documents, research papers, invoices, or any PDF without needing to open it.

ParametersJSON Schema

Name	Required	Description	Default
`filename`	No	Optional original filename, used for validation only.
`fileBase64`	Yes	The PDF file contents encoded as a base64 string.

generate_qr_codeInspect

Generate a QR code image from any text or URL. Returns a base64-encoded PNG. Supports custom size and error correction level. Useful for creating shareable links, contact cards, payment addresses, or any scannable code.

ParametersJSON Schema

Name	Required	Description
`size`	No	Image width/height in pixels (64–2048, default 400).
`text`	Yes	The text or URL to encode in the QR code. Max 2953 characters.
`errorCorrectionLevel`	No	Error correction level: L (7%), M (15%, default), Q (25%), H (30%).

json_to_csvInspect

Convert a JSON array of objects into a CSV string. Column names are inferred from all object keys. Handles special characters, embedded commas, and quotes with proper escaping. Returns a CSV with CRLF line endings.

ParametersJSON Schema

Name	Required	Description	Default
`data`	Yes	Array of objects to convert to CSV rows.
`delimiter`	No	Column delimiter character (default: ',').

merge_pdfsInspect

Merge 2 to 20 PDF files into a single PDF document. Each file is provided as a base64-encoded string. Returns the merged PDF as a base64 PNG. Ideal for combining reports, invoices, chapters, or any multi-file PDF workflow.

ParametersJSON Schema

Name	Required	Description	Default
`files`	Yes	Array of PDF files to merge, in order. Each item must have a 'base64' field.

ocr_imageInspect

Extract text from an image using OCR (Optical Character Recognition). Accepts the image as a base64-encoded string. Returns extracted text, confidence score, and word count. Useful for reading scanned documents, screenshots, handwritten notes, or any image where text needs to be extracted without a vision model.

ParametersJSON Schema

Name	Required	Description	Default
`filename`	No	Optional filename with extension (e.g., 'scan.png') to help with format detection.
`imageBase64`	Yes	Image file contents as a base64 string. Supported: PNG, JPEG, WEBP, BMP, TIFF.

read_urlInspect

Fetch a public web page and return its main readable content as plain text, along with the title, author, and excerpt. Uses Mozilla Readability to strip navigation, ads, and boilerplate. Great for reading articles, documentation, or any page you want to process without a browser.

ParametersJSON Schema

Name	Required	Description	Default
`url`	Yes	The full URL to fetch (must be http:// or https://).

scrape_url_jsInspect

Fetch and extract content from a web page that requires JavaScript rendering (SPAs, dynamically loaded content). Unlike read_url which uses simple HTTP fetch, this tool uses a headless browser to render the page first. Returns clean text or markdown. Use for React/Next.js/Angular/Vue apps, product pages, news sites behind JS paywalls, or any page where read_url returns empty content.

ParametersJSON Schema

Name	Required	Description	Default
`url`	Yes	The full URL to scrape (must be http:// or https://).
`format`	No	Output format: 'text' for plain text (default), 'markdown' to preserve headings and links.

transcribe_audioInspect

Transcribe speech from an audio file to text using OpenAI Whisper (gpt-4o-mini-transcribe). Accepts the audio as a base64-encoded string. Returns the full transcript, word count, and character count. Supported formats: flac, m4a, mp3, mp4, mpeg, mpga, oga, ogg, wav, webm. Maximum file size: 25MB. Great for transcribing meeting recordings, podcasts, voice notes, interviews, or any spoken audio.

ParametersJSON Schema

Name	Required	Description	Default
`filename`	Yes	Filename with extension (e.g., 'recording.mp3') — used for format detection.
`audioBase64`	Yes	The audio file contents encoded as a base64 string.

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Claim this connector by publishing a /.well-known/glama.json file on your server's domain with the following structure:

{
  "$schema": "https://glama.ai/mcp/schemas/connector.json",
  "maintainers": [
    {
      "email": "your-email@example.com"
    }
  ]
}

The email address must match the email associated with your Glama account. Once verified, the connector will appear as claimed by you.

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