ai-netcafe
Verified · 21 days agoTables and ledgers checked by arithmetic, not by a model. 24 tools. MCP 2026-07-28 ready.
PDF-to-Markdown extraction that audits its own output and flags any extractor's silent drops.
claude mcp add pdfmux -- uvx pdfmux
A self-auditing PDF extraction pipeline: it routes each page to the best of several rule-based backends — PyMuPDF, Docling, RapidOCR, Marker, and others — scores per-page confidence, and re-extracts pages that fail its own audit, with optional BYOK LLM fallback for the hardest ones. That confidence-scored, fail-loudly design is genuinely distinctive for RAG ingestion, and it runs locally with no required API keys unless you enable LLM backends. It is a young single-maintainer project with marketing-forward benchmark claims that deserve independent verification. For anyone whose pipeline silently ingests garbled PDF text today, worth a trial.
Tables and ledgers checked by arithmetic, not by a model. 24 tools. MCP 2026-07-28 ready.
Puter MCP enables AI tools to interact with Puter: manage files, websites, workers, and more
MCP server for filesystem access
MCP server for terminal commands, file operations, and process management
Local-first knowledge management with bi-directional LLM sync via Markdown files.
Markdown knowledge base as agent memory. Runs against the notes directory it is started in.