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Glama

Server Details

12 free tools: PDF, OCR, QR codes, audio transcription, URL scraping, Excel, Word. No key needed.

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Status
Unhealthy
Last Tested
Transport
Streamable HTTP
URL

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. 7 tool updates
    • Addedanalyze_text
    • Addedcompare_versions
    • Addedcount_tokens_multi
    • Addeddetect_jargon
    • Addeddetect_pii
    • Addedfind_repetition
    • Addedtone_score
  2. 27 tool updates
    • First observedchunk_text
    • First observedcount_words
    • First observedcreate_shareable_paste
    • First observedcsv_to_json
    • First observeddiff_texts
    • First observedestimate_tokens
    • First observedexcel_to_json
    • First observedextract_docx_text
    • First observedextract_pdf_text
    • First observedextract_structured_data
    • First observedgenerate_pdf_from_text
    • First observedgenerate_qr_code
    • First observedget_arc_trading_signal
    • First observedhash_text
    • First observedhtml_to_markdown
    • First observedjson_to_csv
    • First observedlist_memories
    • First observedmarkdown_to_html
    • First observedmerge_pdfs
    • First observedocr_image
    • First observedprivate_execute_tool
    • First observedread_url
    • First observedrecall_memory
    • First observedrun_regex
    • First observedsave_memory
    • First observedscrape_url_js
    • First observedtranscribe_audio

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TDQS

A4.1/5.0
Disambiguation4/5

Most tools have distinct purposes, such as chunk_text for text splitting, count_words for text statistics, and extract_pdf_text for PDF extraction. However, some overlap exists between read_url and scrape_url_js (both for web content retrieval, though scrape_url_js handles JavaScript-heavy pages) and between csv_to_json and excel_to_json (both for tabular data conversion), which could cause minor confusion. Overall, descriptions help clarify differences, but a few tools have ambiguous boundaries.

Naming Consistency5/5

Tool names follow a highly consistent snake_case verb_noun pattern throughout, such as chunk_text, count_words, create_shareable_paste, and extract_structured_data. All 27 tools adhere to this convention, with no deviations in style or structure, making them predictable and easy to parse for an agent.

Tool Count2/5

With 27 tools, the count feels excessive for a general-purpose utility server, leading to potential cognitive overload and redundancy. While the tools cover diverse functions like text processing, file conversion, and web scraping, many could be consolidated (e.g., csv_to_json and excel_to_json) or omitted without losing core functionality. A more focused set of 10-15 tools would better suit the apparent scope.

Completeness4/5

The tool set provides comprehensive coverage for text and data processing, including extraction, conversion, analysis, and storage, with no major gaps in core workflows. However, minor gaps exist, such as lacking tools for direct editing of extracted data or advanced transformations beyond basic formats. The inclusion of memory management (save_memory, recall_memory) and niche tools like get_arc_trading_signal adds breadth but doesn't fully compensate for these omissions in the primary domain.

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