https://github.com/u9401066/asset-aware-mcp

Asset-Aware MCP Server — AI Agent precisely accesses tables, figures, sections from PDFs + .docx round-trip editing (DFM) with 46 tools / 13 resources, segmentation export, layout overlay, OCR preprocessing, knowledge graph (LightRAG)
https://github.com/u9401066/asset-aware-mcp

ai document-processing docx etl fastmcp knowledge-graph layout-analysis lightrag llm mcp mcp-server medical ocr pdf python rag segmentation

Last synced: about 2 months ago
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Asset-Aware MCP Server — AI Agent precisely accesses tables, figures, sections from PDFs + .docx round-trip editing (DFM) with 46 tools / 13 resources, segmentation export, layout overlay, OCR preprocessing, knowledge graph (LightRAG)

• Host: GitHub
• URL: https://github.com/u9401066/asset-aware-mcp
• Owner: u9401066
• License: apache-2.0
• Created: 2025-12-26T04:29:14.000Z (6 months ago)
• Default Branch: master
• Last Pushed: 2026-04-09T01:23:06.000Z (3 months ago)
• Last Synced: 2026-04-09T03:24:40.217Z (3 months ago)
• Topics: ai, document-processing, docx, etl, fastmcp, knowledge-graph, layout-analysis, lightrag, llm, mcp, mcp-server, medical, ocr, pdf, python, rag, segmentation
• Language: Python
• Size: 7.3 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • Changelog: CHANGELOG.md
  • Contributing: CONTRIBUTING.md
  • License: LICENSE
  • Code of conduct: CODE_OF_CONDUCT.md
  • Security: SECURITY.md
  • Roadmap: ROADMAP.md

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README

          
# asset-aware-mcp

> 🏥 Medical RAG with Asset-Aware MCP - Precise PDF asset retrieval (tables, figures, sections) and Knowledge Graph for AI Agents.

[![License](https://img.shields.io/badge/License-Apache_2.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)

🌐 [繁體中文](README.zh-TW.md) · [Docs Site](https://u9401066.github.io/asset-aware-mcp/#/overview-zh) · [GitHub Wiki](https://github.com/u9401066/asset-aware-mcp/wiki)

## 🎯 Why Asset-Aware MCP?

**AI cannot directly read image files on your computer.** This is a common misconception.

| Method | Can AI analyze image content? | Description |

|------|:-------------------:|------|

| ❌ Provide PNG path | No | AI cannot access the local file system |

| ✅ **Asset-Aware MCP** | **Yes** | Retrieves Base64 via MCP, allowing AI vision to understand directly |

### Real-world Effect

```

# After retrieving the image via MCP, the AI can analyze it directly:

User: What is this figure about?

AI: This is the architecture diagram for Scaled Dot-Product Attention:

    1. Inputs: Q (Query), K (Key), V (Value)

    2. MatMul of Q and K

    3. Scale (1/√dₖ)

    4. Optional Mask (for decoder)

    5. SoftMax normalization

    6. Final MatMul with V to get the output

```

**This is the value of Asset-Aware MCP** - enabling AI Agents to truly "see" and understand charts and tables in your PDF literature.

---

## ✨ Features

- 📄 **Asset-Aware ETL** - PDF → Markdown with a PyMuPDF-first parser and retained Marker code path:

  - **PyMuPDF** (default) - Fast extraction (~50MB)

  - **Marker** (`use_marker=True`) - High-precision structured parsing code path retained, but packaged runtime remains on security hold in v0.6.31 until upstream `marker-pdf` supports patched Pillow

- 🧩 **Unified Segmentation Export** - Normalized `segmentation.json` merges manifest, blocks, reading order, and persisted markdown line spans for downstream tools and extensions.

- 🖼️ **Layout Overlay Debugging** - Render page overlays from `original.pdf` to inspect bbox, segment type, and reading order visually.

- 🔤 **On-Demand OCR Preprocessing** - Optional `ocrmypdf` preprocessing path for scanned PDFs before ETL.

- 🧭 **Section Navigation** - Dynamic hierarchy section tree with 5 tools: browse, search, detail, content reading, and block extraction for any depth of headings.

- 🔄 **Async Job Pipeline** - Supports asynchronous ingest, Marker-required parse, OCR, and conversion jobs with progress tracking.

- 🗺️ **Document Manifest** - Provides a structured "map" of the document for precise data access by Agents.

- 🧠 **LightRAG Integration** - Knowledge Graph + Vector Index, supporting cross-document comparison and reasoning.

- 🧾 **Verified Citation Bundles** - `citation_bundle`, Foam evidence packs, citation health checks, table/figure evidence notes, and claim promotion export citation-ready spans with locator, quote/hash, context, CRAAP scaffold, and verification status.

- 📝 **Docx Editing (DFM)** - Edit .docx files in Markdown via **Docx-Flavored Markdown** format. Supports legacy `.doc`, `.odt`, and `.ods` ingest via LibreOffice auto-conversion. 17 tools: ingest, read, save, list, delete, export, strict round-trip validation, DOCX→PDF/DOC/ODT, table edit planning, and Docx ↔ A2T bridges.

- 🛡️ **DFM Integrity Checker** - Automatic validation and auto-repair at every pipeline stage (post-ingest, pre-save, post-save). Catches orphan markers, column mismatches, and format inconsistencies.

- 📊 **A2T (Anything to Table)** - 7 operation-based tools for building professional tables from **any source** (PDF assets, Knowledge Graph, URLs, user input). Features: **Citations** (AssetRef), **Audit Trail**, **Schema Evolution**, **Templates**, **Drafting**, and **Token-efficient resumption**.

- 🖥️ **VS Code Management Extension** - Graphical interface for monitoring server status, ingested documents, document artifacts, citation spans, and **A2T tables/drafts** with one-click Excel export.

- 🔌 **MCP Server** - Exposes tools and resources to Copilot/Claude via FastMCP.

- 🏥 **Medical Research Focus** - Optimized for medical literature, supporting Base64 image transmission for Vision AI analysis.

## 🏗️ Architecture



  



```

┌─────────────────────────────────────────────────────────┐

│                    AI Agent (Copilot)                   │

└─────────────────────┬───────────────────────────────────┘

                      │ MCP Protocol (Tools & Resources)

┌─────────────────────▼───────────────────────────────────┐

│            MCP Server (Modular Presentation)            │

│  ┌─────────────────────────────────────────────────┐   │

│  │ tools/: 62 tools in 7 modules                   │   │

│  │   document (19) │ docx (17) │ section (5)       │   │

│  │   job (4) │ knowledge (3) │ table (7) │ profile (7) │

│  └─────────────────────────────────────────────────┘   │

│  ┌─────────────────────────────────────────────────┐   │

│  │ resources/: 13 resources in 2 modules           │   │

│  └─────────────────────────────────────────────────┘   │

└─────────────────────┬───────────────────────────────────┘

                      │

┌─────────────────────▼───────────────────────────────────┐

│                  ETL Pipeline (DDD)                     │

│  ┌──────────┐  ┌──────────┐  ┌──────────┐              │

│  │ PyMuPDF  │  │  Asset   │  │ LightRAG │              │

│  │ Adapter  │→ │  Parser  │→ │  Index   │              │

│  └──────────┘  └──────────┘  └──────────┘              │

└─────────────────────┬───────────────────────────────────┘

                      │

┌─────────────────────▼───────────────────────────────────┐

│                   Local Storage                         │

│  ./data/                                                │

│  ├── {doc_id}/        # PDF document artifacts          │

│  ├── docx_{id}/       # Docx IR + DFM + Assets          │

│  ├── tables/          # A2T Tables (JSON/MD/XLSX)       │

│  │   └── drafts/      # Table Drafts (Persistence)      │

│  └── lightrag_db/     # Knowledge Graph                 │

└─────────────────────────────────────────────────────────┘

```

## 📁 Project Structure (DDD)

```

asset-aware-mcp/

├── src/

│   ├── domain/              # 🔵 Domain: Entities, Value Objects, Interfaces

│   ├── application/         # 🟢 Application: Doc Service, Table Service (A2T), Asset Service

│   ├── infrastructure/      # 🟠 Infrastructure: PyMuPDF, LightRAG, Excel Renderer

│   └── presentation/        # 🔴 Presentation: MCP Server (FastMCP)

├── data/                    # Document and Asset Storage

├── docs/

│   └── spec.md              # Technical Specification

├── tests/                   # Unit and Integration Tests

├── vscode-extension/        # VS Code Management Extension

└── pyproject.toml           # uv Project Config

```

## 📐 Architecture Diagrams

Visual overview for the project. All diagrams use consistent GitHub README style.

| Diagram | Description |

|---------|-------------|

| [01 — System Architecture](docs/diagrams/01-system-architecture.jpg) | Full stack: Telegram → Gateway → MCP Adapter → 3 MCP servers → Ollama |

| [02 — Data Layout](docs/diagrams/02-data-layout.jpg) | 62 tools organized in 7 categories with asset-aware data tree |

| [03 — PDF Ingestion Pipeline](docs/diagrams/03-pdf-ingestion-pipeline.jpg) | 7-stage flow from PDF upload to knowledge graph |

| [04 — DOCX Bidirectional Edit](docs/diagrams/04-docx-edit-pipeline.jpg) | DOCX ingest → TableContext edit → round-trip save workflow |

| [05 — Knowledge Graph Search](docs/diagrams/05-knowledge-graph-search.jpg) | Cross-document search with 3 parallel query paths |

| [06 — Installation Steps](docs/diagrams/06-installation-steps.jpg) | 7-step installation from clone to verification |

| [07 — PDF ETL Pipeline](docs/diagrams/07-pdf-etl-pipeline.jpg) | PyMuPDF default path + Marker security-hold diagnostics |

| [08 — KG Architecture](docs/diagrams/08-knowledge-graph-architecture.jpg) | lightrag-hku 3-layer KG architecture |

| [09 — Agent Harness Concept](docs/diagrams/09-agent-harness-concept.jpg) | Assistant harness model for stateless agents |

> 💡 All generation prompts are saved in [docs/diagrams/ALL-PROMPTS.md](docs/diagrams/ALL-PROMPTS.md) for style consistency and regeneration.

## 🚀 Quick Start

```bash

# Install dependencies (using uv) — default install skips Marker/torch

uv sync

# v0.6.31: Marker extra is temporarily empty because marker-pdf pins

# Pillow<11 while the secure runtime requires Pillow>=12.2.0.

# Use the default PyMuPDF backend until upstream marker-pdf supports patched Pillow.

# Run MCP Server

uv run python -m src.presentation.server

# Or use the VS Code extension for graphical management

```

Runtime note:

The VS Code extension prefers a managed Python 3.11 runtime when launching the MCP server via `uv` or `uvx`. This avoids native package builds on end-user machines, especially macOS systems without Xcode Command Line Tools, while keeping the project itself compatible with newer Python versions.

Installation scope note:

- The VS Code extension installs once per user (global). MCP launch env defaults `DATA_DIR` to workspace `./data` and `UV_CACHE_DIR` to `DATA_DIR/.uv-cache`; Prepare Server Runtime warms a workspace `.uv-cache`, falling back to extension global storage only when no workspace is open.

- Runtime data stays with your repo: `.env` and `assetAwareMcp.dataDir` default to `./data`, so ingested assets and the uv cache used by the launched server remain scoped to the current workspace.

Marker note:

Since v0.6.28 the packaged Marker extra has intentionally stayed on security hold: upstream `marker-pdf` 1.10.2 requires `Pillow<11`, while this release pins `Pillow>=12.2.0` for patched image-processing security. Default installs use the PyMuPDF backend only. `use_marker=True` / `parse_pdf_structure` will report that Marker is unavailable until upstream Marker supports a patched Pillow range.

## 🔌 MCP Tools

### Document & Asset Tools

| Tool | Purpose |

|------|---------|

| `ingest_documents` | Process PDF files with PyMuPDF; `use_marker=True` currently falls back or fails closed while Marker is on security hold |

| `list_documents` | List all ingested documents and their asset counts |

| `delete_document` | Delete an ingested PDF, its local artifacts, and LightRAG index entries when enabled |

| `convert_pdf_to_docx` | Reconstruct a readable DOCX from extracted PDF content; defaults to a conversion background job |

| `convert_pdf_to_pptx` | Rebuild editable PPTX slides from extracted PDF markdown and figures; defaults to a conversion background job |

| `inspect_document_manifest` | Inspect document structure before fetching specific assets |

| `fetch_document_asset` | Precisely retrieve tables (MD) / figures (B64) / sections |

| `parse_pdf_structure` | Queue structured parsing work; Marker output remains unavailable until upstream Marker supports patched Pillow |

| `search_source_location` | Search exact source locations with page + bbox for verification |

| `export_document_segmentation` | Export normalized `segmentation.json` with reading order + line ranges |

| `visualize_document_layout` | Render page overlay images for bbox / type / reading-order inspection |

| `ocr_pdf_document` | Run OCR preprocessing and generate a cleaned PDF for later ETL |

| `find_evidence_spans` | Search citation-ready spans with source revision, locator, hash, and CRAAP scaffold |

| `verify_citation_ref` | Verify span AssetRefs against the current citation index and locator metadata |

| `citation_bundle` | Export verified evidence bundles with AssetRef, quote/hash, locator, context, CRAAP scaffold, and verification status |

| `document` | Operation-based facade over PDF ingest/list/delete/inspect/parse |

| `document_asset` | Operation-based facade over asset fetch and section tree/detail/blocks/search |

| `evidence` | Operation-based facade over citation span find/verify/source-location search and bundle export |

| `convert_document` | Operation-based facade for PDF, DOCX/DFM, and Markdown conversions; conversion paths default to background jobs |

### Job Management Tools

| Tool | Purpose |

|------|---------|

| `get_job_status` | Get async ingestion/conversion job progress and final result |

| `list_jobs` | List active or historical ETL jobs |

| `cancel_job` | Cancel a running ETL job |

| `job` | Operation-based facade over job get/list/cancel |

### Knowledge Graph Tools

| Tool | Purpose |

|------|---------|

| `consult_knowledge_graph` | Citation-aware knowledge graph query with `structured`, `data`, `text`, and optional verified evidence bundles |

| `export_knowledge_graph` | Export graph summary / JSON / Mermaid for inspection |

| `knowledge` | Operation-based facade over knowledge graph consult/export |

Knowledge graph note:

- `consult_knowledge_graph` defaults to `response_mode="structured"` and can return `answer`, `references`, `metadata`, `retrieval`, `counts`, and `verified_evidence` when `verify_references=true`.

- Use `response_mode="data"` when you want retrieval payloads without final answer synthesis, or `response_mode="text"` for legacy plain-text behavior.

### Section Navigation Tools (Dynamic Hierarchy)

| Tool | Purpose |

|------|---------|

| `list_section_tree` | Display complete section hierarchy tree (supports any depth) |

| `get_section_detail` | Get detailed info for a specific section |

| `get_section_blocks` | Extract all blocks from a section with page + bbox |

| `search_sections` | Search section titles |

| `get_section_content` | Read section content via asset service |

### Docx Editing Tools (DFM — Docx-Flavored Markdown)

> Edit .docx files as Markdown. Preserves formatting, tables, media on round-trip.

| Tool | Purpose |

|------|---------|

| `ingest_docx` | Import .docx and decompose into DFM blocks |

| `get_docx_content` | Read DFM content of specific blocks |

| `save_docx` | Write DFM edits back to .docx |

| `list_docx_blocks` | List document block structure |

| `list_docx_documents` | List all ingested DOCX/DFM documents |

| `delete_docx` | Delete an ingested DOCX/DFM document and its local artifacts |

| `convert_docx_to_pdf` | Export the current DOCX/DFM state to PDF in fidelity mode; defaults to a conversion background job |

| `convert_docx_to_doc` | Export the current DOCX/DFM state to DOC in fidelity mode; defaults to a conversion background job |

| `docx_validate_roundtrip` | 6-dimension round-trip fidelity validation + file-level comparison (SHA-256, ZIP diff) |

| `docx_table_to_context` | Bridge: Docx table → A2T context |

| `docx_table_from_context` | Bridge: A2T table → Docx table |

| `docx_chart_data` | Extract chart data from Docx |

| `docx_table_edit_plan` | Preview table cell/row/column/header changes and structural risks before write-back |

| `export_markdown` | Export Markdown to .docx/.pdf/.doc; defaults to a conversion background job |

| `convert_docx_to_odt` | Export the current DOCX/DFM state to ODT; defaults to a conversion background job |

| `docx` | Operation-based facade over DOCX/DFM ingest/get/save/list/delete/blocks/validate |

| `docx_table` | Operation-based facade over DOCX table to_context/from_context/chart_data/edit_plan |

### A2T (Anything to Table) Tools — 7 Operation-Based Tools

> Agent-friendly design: each tool handles multiple operations via `operation` parameter.

> Tables accept **any source** — PDF assets, KG entities, external URLs, or user input.

| Tool | Operations | Purpose |

|------|-----------|----------|

| `plan_table` | `schema` / `templates` / `from_template` | Schema planning, browse 4 built-in templates, create from template |

| `table_manage` | `create` / `delete` / `list` / `preview` / `resume` / `render` / `add_column` / `remove_column` / `rename_column` | Table lifecycle + Schema evolution |

| `table_data` | `add_rows` / `get_row` / `update_row` / `delete_row` / `get_cell` / `update_cell` / `clear_cell` | Row & cell CRUD |

| `table_cite` | `add` / `get` / `remove` / `cell_history` | Citation management with AssetRef (7 source types) |

| `table_history` | `changes` / `tokens` | Audit trail & token estimation |

| `table_draft` | `create` / `update` / `add_rows` / `resume` / `commit` / `list` / `delete` | Draft workflow with persistence |

| `discover_sources` | — | Cross-document source discovery (sections, tables, figures, KG) |

### ETL Profile Tools

Different journals/formats need different extraction settings. Use these tools to switch profiles.

| Tool | Purpose |

|------|---------|

| `list_etl_profiles` | List all available profiles (default, arxiv, nature, ieee, elsevier) |

| `get_etl_profile` | Get detailed configuration of a specific profile |

| `get_current_etl_profile` | Show currently active profile |

| `set_etl_profile` | Switch profile for subsequent document ingestion |

| `load_etl_profile_from_json` | Load custom profile from JSON file |

| `detect_etl_profile` | Detect the best built-in profile from PDF path, doc_id, or sample text |

| `etl_profile` | Operation-based facade over profile list/get/current/set/load/detect |

## 🔧 Tech Stack

| Category | Technology |

|----------|------------|

| Language | Python 3.10+ |

| Package Manager | **uv** (all pip/setup-python removed) |

| ETL | **PyMuPDF** (fitz); **Marker** is temporarily on security hold |

| RAG | LightRAG (lightrag-hku) |

| MCP | FastMCP |

| Storage | Local filesystem (JSON/Markdown/PNG) |

## 📋 Documentation

Installation guidance:

- Default install: `uv sync`

- Marker backend: temporarily disabled in v0.6.31 because `marker-pdf` pins vulnerable `Pillow<11`; the `marker` / `pdf` extras are compatibility placeholders until upstream supports patched Pillow.

- VS Code extension: `assetAwareMcp.enableMarkerBackend` is retained as a setting, but the launcher will not install `marker-pdf` while the security hold is active.

- [Technical Spec](docs/spec.md) - Detailed technical specification

- [Architecture](ARCHITECTURE.md) - System architecture

- [Constitution](CONSTITUTION.md) - Project principles

- [Competitive Analysis](docs/competitor-analysis.md) - MCP + DOCX ecosystem landscape

## 📄 License

[Apache License 2.0](LICENSE)