Any file → clean Markdown for AI agents: PDF, Office, EPUB, HTML, images. Local Rust MCP server.
Copy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.
One-click editor setup isn’t available for this listing yet — we don’t have a confirmed install command, and we’d rather show nothing than point your editor at the wrong package or host. Follow the project’s own setup instructions, linked above.
PDF, Word, PowerPoint, Excel, EPUB, HTML and web pages, images (OCR), audio and video (metadata, subtitles, transcripts). A fast Rust MCP server and CLI that runs on your machine. No API key.
[](https://github.com/SylphxAI/repomap#agent-readiness-score)Install · Benchmarks · Tools · CLI · Formats · Docs
Formerly pdf-reader-mcp. Migrating from pdf-reader-mcp
A real, unedited terminal recording (asciinema + agg, script). The last command is Claude Code answering from the PDF through the anymd MCP server.
<!-- page 3 --> citation anchors, a small front-matter header, and compact tables. A token budget and a cursor keep large documents within your agent's context.search looks across all of them.Add anymd to every MCP client on your machine (Claude Code, Codex, Cursor, VS Code, Claude Desktop, Windsurf, Gemini CLI) with one command:
Or add it by hand: every MCP client runs the same command, npx -y @sylphx/anymd. Node 18+ is the only requirement; npm installs the native binary for your platform.
Or as a plugin, with the anymd skill: /plugin marketplace add SylphxAI/anymd, then /plugin install anymd@anymd.
or in ~/.codex/config.toml:
or in .vscode/mcp.json:
Add to claude_desktop_config.json (Settings → Developer → Edit Config):
Any client that speaks MCP over stdio: command npx, args ["-y", "@sylphx/anymd"]. To keep the server inside one folder, add --allow-dir=/path/to/docs.
AgentDocBench is an open benchmark for document → Markdown conversion for agents: license-clean documents in 12 categories (math papers, two-column papers, financial tables, forms, scans, CJK, slides, spreadsheets, Word, EPUB, HTML), scored on verbatim sentences, text F1, reading order, and table cells, with time and output tokens. Every tool runs on the same kind of GitHub-hosted runner (4 CPUs):
| anymd | docling | kreuzberg | unstructured | markitdown | marker | pdftotext | |
|---|---|---|---|---|---|---|---|
| Overall score | 96.3 | 93.0 | 81.7 | 81.2 | 76.8 | 71.0 | 42.2 |
| Table cells F1 | 92.2 | 89.9 | 38.4 | 38.4 | 57.2 | 60.9 | 0.0 |
| Reading order | 98.8 | 94.4 | 96.8 | 93.9 | 85.5 | 76.8 | 52.0 |
| Docs converted | 38/38 | 38/38 | 38/38 | 38/38 | 38/38 | 30/38 | 23/38 |
| Time, all docs | 22.9 s | 2,432.4 s | 16.0 s | 346.5 s | 75.6 s | 7,104.5 s | 0.90 s |
The generated leaderboard, per-category scores (including where anymd loses), and method are in the benchmark guide. The corpus, ground truth, adapters, and raw results are in bench/, and the Benchmark workflow reruns everything; new tools can join with a single adapter file.
anymd exposes three tools.
| Tool | Use it to | Key arguments |
|---|---|---|
read | Turn a file, URL, or folder into Markdown | source, pages ("1-5,8"), max_tokens (default 20000), cursor, ocr, transcript, download_whisper_model |
search | Find text across files, folders, and URLs | query, sources, mode (auto · literal · ranked), glob, max_results |
inspect | Go deeper on a PDF | operation: render_page, extract_regions, ocr_pages, structure (JSON with geometry), compare, inspect |
A read answer looks like this:
search answers with one line per hit:
If nothing matches exactly, search falls back to BM25-ranked passages, so a question like "how does bidirectional pretraining work" still finds the right page.
The same binary is a command-line converter, like MarkItDown but much faster:
Run with no arguments from an MCP client (piped stdin), or as anymd mcp, and it serves MCP over stdio.
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