VisualDoc

VisualDoc

MCP server for automated visual-layout QA of DOCX documents, enabling rendering, measurement, rule checking, patching, and diffing in a closed loop.

Category
Visit Server

README

VisualDoc

Visual-layout QA untuk dokumen — "Playwright, tapi untuk DOCX / Google Docs / Word." Satu MCP server yang dipakai identik oleh Claude Code dan OpenCode: render → ukur → cek → patch → diff → ulangi.

Status: Fase 0 + Fase 1 (+ penguatan) ✅ terverifikasi end-to-end lewat klien MCP stdio sungguhan, 47 pytest hijau. Loop tertutup: doc_autofix membawa dokumen contoh dari {critical:1} → {critical:0} dalam 1 iterasi. Penguatan: anchor stabil w14:paraId, mode review/safe/full, regression guard (revisi yang memunculkan isu baru → rollback), dan guardrails input: validasi DOCX, deteksi halaman di luar rentang, serta error terstruktur {ok:false, error{code}} — menutup celah "laporan hijau padahal salah".

doc_render_report → 1 critical (table_overflow) + 1 warning (image_low_dpi)
doc_autofix       → baseline{critical:1} → final{critical:0}  accepted=True
                    iter1: set_table_width(el-4) → resolved [p1:table_overflow]
                    unresolved: [p1:image_low_dpi]   (butuh aset resolusi lebih tinggi)

Loop (Fase 1)

doc_get_structure ──► el-N (posisional) + anchor (w14:paraId, stabil) + version_hash
        │
doc_apply_patch(ops, expected_version_hash) ──► revisi + validasi round-trip
        │            target = el-N | anchor      (file asli tak disentuh)
doc_render_report(revisi) ──► ukur ulang
        │
doc_diff_versions ──► resolved / new(regresi) / delta
        ↺  (dibungkus jadi satu tool: doc_autofix — mode review|safe|full)
   berhenti saat tak ada yang bisa diperbaiki / max_iter / regression guard
   (revisi yang memunculkan warning baru → dibuang, versi sebelumnya dipertahankan)

Loop hidup sebagai satu tool (doc_autofix), bukan Claude Code hook — supaya portabel ke OpenCode (docs/01-compatibility.md). Agen juga bisa menyetir loop lebih halus sendiri via doc_get_structure + doc_apply_patch.

Struktur

namanya-nanti/
├── .mcp.json · pyproject.toml · README.md
├── docs/  00-concept · 01-compatibility · 02-preview-model (DOCX vs LaTeX)
├── src/visualdoc/
│   ├── server.py          # MCP server (FastMCP, stdio) — 7 tool
│   ├── core/              # FORMAT-AGNOSTIC (bekerja atas PDF apa pun)
│   │   ├── geometry.py    #   PDF -> bbox/font/DPI/tabel
│   │   ├── rules.py       #   rule engine (+ engine_sensitivity)
│   │   ├── report.py      #   analyze_pdf()
│   │   ├── diff.py        #   diff_reports() before/after
│   │   └── raster.py      #   PDF page -> PNG (kanal visual opsional)
│   └── adapters/docx/     # FORMAT-SPECIFIC
│       ├── render.py      #   DOCX -> PDF (LibreOffice)
│       ├── meta.py        #   margin/style OOXML
│       ├── patch.py       #   get_structure + ops aman + validasi round-trip
│       ├── autofix.py     #   loop deterministik (structure-driven, render-verified)
│       └── pipeline.py    #   build_report()
├── rules/general.yaml · configs/ · scripts/
└── workspace/  original/ revisions/ renders/ reports/

Tool (7)

Tool Fungsi
doc_selftest() Cek kesehatan (soffice/PyMuPDF/python-docx) + daftar patch_ops.
doc_render_report(document, pages?, rules?) Render + ukur + cek → JSON (summary.headline, pages[]). Tanpa gambar.
doc_get_structure(document, assign_anchors?, output?) Elemen ter-alamat: el-N + anchor (w14:paraId, stabil) + version_hash + text_column_mm. assign_anchors → normalized_output.
doc_apply_patch(document, ops, expected_version_hash?, output?) Op aman ke salinan (target el-N | anchor) + validasi round-trip.
doc_autofix(document, rules?, max_iter?, mode?) Loop tertutup + regression guard → revisi final + history/diff. mode: review|safe|full.
doc_diff_versions(before, after, rules?) Diff dua versi: resolved / new / delta.
doc_get_page_image(document, page?, dpi?) Opsional: PNG satu halaman (mahal token; pakai hemat).

Op aman (doc_apply_patch): set_spacing, set_keep_with_next, set_page_break_before, set_paragraph_style, set_font, set_table_width. Tiap op melapor applied/error independen; op salah tak menggagalkan yang benar. target bisa el-N (posisional) atau anchor (w14:paraId — bertahan lintas-edit; doc_get_structure(assign_anchors=true) menuliskannya ke normalized_output).

Mode doc_autofix: review (rencana saja) · safe (invariant: fit tabel) · full (safe + heading keep_with_next + clamp spacing). Warning membawa engine_sensitivity (invariant benar di renderer manapun; dependent hanya valid untuk layout LibreOffice ini) — lihat docs/02-preview-model.md.

Kontrak error: tiap tool mengembalikan ok: true saat sukses, atau {ok: false, error: {code, message, detail?}} saat gagal — code ∈ {not_found, invalid_docx, invalid_rules, pages_out_of_range, stale_version, bad_argument, no_ops, no_ops_applied, render_unavailable, render_failed, internal}. Input DOCX & rule-pack divalidasi (bukan-DOCX / .doc lama / korup / YAML rusak ditolak), render yang gagal/timeout terbedakan dari input salah, dan halaman di luar rentang tak pernah menghasilkan laporan "hijau" palsu (semua di luar rentang → error; sebagian → di-flag). apply_patch yang 0-perubahan tidak menulis file (no_ops/no_ops_applied).

Keandalan tabel (#4): table_overflow dikoroborasi dengan lebar OOXML (patch._table_width_mm) — jumlah kolom di pesan direkonsiliasi ke angka OOXML yang otoritatif (mis. render 7 → OOXML 8), tiap tabel render dijembatani ke element_id, dan overflow yang tak terdeteksi renderer (mis. tabel tanpa border) tetap muncul sebagai isu struktural, bukan hilang diam-diam.

Prinsip desain

Semua analisis di server, dikembalikan sebagai teks/JSON — bukan gambar ke model. Rule engine jalan murni atas angka geometri (PyMuPDF), tanpa vision → murah token, deterministik, jalan di kedua klien bahkan dengan model text-only. Alasan: docs/01-compatibility.md.

Quickstart

# Prasyarat sistem (sekali):
sudo apt-get install -y --no-install-recommends libreoffice-writer python3-venv fonts-liberation
python3 -m venv .venv && .venv/bin/pip install -e .

# Coba:
.venv/bin/python scripts/make_sample.py    # -> workspace/original/sample.docx
.venv/bin/python scripts/mcp_smoke.py       # uji 7 tool end-to-end lewat protokol MCP
.venv/bin/mcp dev src/visualdoc/server.py   # (opsional) MCP Inspector interaktif

# Test (mengunci semua perilaku agar tak regres):
.venv/bin/pip install -e ".[test]" && .venv/bin/python -m pytest

Registrasi di klien

  • Claude Code — .mcp.json sudah ada di root: /mcp → approve visualdoc (perlu restart sesi; server MCP tak hot-load).
  • OpenCode — salin configs/opencode.json ke opencode.json project Anda.

Contoh perintah ke agen: "jalankan doc_autofix pada workspace/original/sample.docx, ringkas apa yang diperbaiki dan apa yang tersisa."

Batasan (jujur, by design)

  • Anchor elemen stabil (w14:paraId) sudah ada; pemetaan elemen↔halaman presisi (korelasi render↔OOXML, mis. inject-marker) masih penyempurnaan lanjut.
  • Auto-fix: table overflow (safe) + heading keep_with_next & clamp spacing (full). image_low_dpi & orphan_heading dilaporkan, belum di-auto-fix (butuh aset/keputusan).
  • Satu engine (LibreOffice) — temuan dependent (page-break/orphan) perlu engine target (Word) untuk kepercayaan penuh. Multi-engine = Fase 4.
  • Belum ada preview-ui/ (viewer manusia) dan adapter non-DOCX. Roadmap → docs/00-concept.md.

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured