A
licenseA
qualityD
maintenanceAn MCP server that converts PDF files to Markdown format using AI sampling capabilities, supporting both local files and URLs with incremental conversion features.
1
1
MIT
Text-Toolkit
Related Servers
Alternatives to Text-Toolkit
No user-submitted related servers found.
Related Servers
- FlicenseNot gradedqualityCmaintenanceAn MCP server that converts and processes document formats such as DOCX and PDF into Markdown, enabling AI assistants to work with document contents.-
- FlicenseNot gradedqualityDmaintenanceAn MCP server that provides developer knowledge and utility tools including local documentation search, text summarization, safe arithmetic calculation, unit conversion, and knowledge-base resources.-
- FlicenseNot gradedqualityCmaintenanceThis MCP server provides tools for OCR and keyword extraction, enabling AI workflows to be split into discrete steps for easier testing, tuning, and cost control.-
- FlicenseNot gradedqualityDmaintenanceAn MCP server that provides comprehensive PDF processing capabilities including text extraction, image extraction, table detection, annotation extraction, metadata retrieval, page rendering, and document structure analysis.-
- AlicenseNot gradedqualityDmaintenanceAn MCP server that provides tools for analyzing, linting, formatting, and generating Markdown content. It enables users to programmatically manage Markdown files through features like table of contents generation, statistics calculation, and JSON-to-table conversion.17 npm1MIT
TDQS
C2.9/5.0
Scored across 43 tools
Disambiguation5/5
Every tool has a clearly distinct purpose with no ambiguity. The case conversion tools target specific case formats, encoding/decoding tools handle different formats, and string operations are well-separated. Even similar-sounding tools like string_replace and regex_replace are clearly differentiated by their descriptions.
Naming Consistency5/5
All tools follow a consistent verb_noun or noun_verb pattern with snake_case throughout. The naming is highly predictable: case_to_*, count_*, decode_*, encode_*, format_*, generate_*, regex_*, string_*, and validate_* patterns create excellent consistency.
Tool Count2/5
43 tools is excessive for a text processing server. While the domain is broad, many tools could be consolidated (e.g., 13 case conversion tools could be a single parameterized tool). The count feels bloated and will overwhelm agents with too many similar options.
Completeness5/5
The tool surface is remarkably complete for text processing. It covers case conversion, counting, encoding/decoding, formatting, hashing, generation, regex operations, string manipulation, and validation. No obvious gaps exist for common text manipulation needs.
Maintenance
ActivityInactive
ResponsivenessNo issues