🚀 Install from Chrome Web Store •
📦 Download Latest Release
@@ -39,7 +41,8 @@
- [1. Clone the Repository](#1-clone-the-repository)
- [2. Start MongoDB](#2-start-mongodb)
- [3. Environment Configuration](#3-environment-configuration)
- - [4. Build and Run](#4-build-and-run)
+ - [4. Custom MCP Backend Orchestration](#4-custom-mcp-backend-orchestration)
+ - [5. Build and Run](#4-build-and-run)
- [Frontend Extension Build](#frontend-extension-build)
- [Chrome Extension Development](#chrome-extension-development)
- [Installing the Development Extension](#installing-the-development-extension)
@@ -53,6 +56,7 @@ PaperDebugger never modifies your project, it only reads and provides suggestion
- **💬 Comment System**: Automatically generate and insert comments into your project
- **📚 Prompt Library**: Custom prompt templates for different use cases
- **🔒 Privacy First**: Your content stays secure - we only read, never modify
+- **🧠 Multi-Agent Orchestration** – [XtraMCP](https://github.com/4ndrelim/academic-paper-mcp-server) support for literature-grounded research, AI-Conference review, and domain-specific revision
https://github.com/user-attachments/assets/6c20924d-1eb6-44d5-95b0-207bd08b718b
@@ -154,7 +158,19 @@ cp .env.example .env
# Edit the .env file based on your configuration
```
-#### 4. Build and Run
+#### 4. Custom MCP Backend Orchestration [OPTIONAL FOR LOCAL DEV]
+Our enhanced orchestration backend, [**XtraMCP**](https://github.com/4ndrelim/academic-paper-mcp-server), is currently closed-source while under active development.
+You can run PaperDebugger without it; all core features (chat, formatting, edits, comments) work normally.
+
+Connecting to XtraMCP unlocks:
+- research-mode agents,
+- structured reviewer-style critique,
+- domain-specific revisions tailored to academic writing powered by [XtraGPT](https://huggingface.co/Xtra-Computing/XtraGPT-14B) models
+
+We plan to **open-source XtraMCP** once the API stabilizes for community use.
+
+
+#### 5. Build and Run
```bash
# Build the backend
make build
diff --git a/demo/xtramcp/readme.md b/demo/xtramcp/readme.md
index ec572bed..f37d0afe 100644
--- a/demo/xtramcp/readme.md
+++ b/demo/xtramcp/readme.md
@@ -1,154 +1,179 @@
-# XtraMCP Server - Orchestration Prompts
-
-This directory contains MCP prompts that orchestrate complex workflows by guiding the AI on how to use multiple tools together effectively.
-
-## Available Prompts
-
-### 1. `analyze_paper_find_similar`
-**Purpose**: Analyze existing research papers (PDF/LaTeX) and find similar work in the academic literature.
-
-**Use Cases**:
-- Finding papers similar to your own research
-- Identifying related work for a paper you're writing
-- Comparing your approach with existing methods in the literature
-- Building a collection of papers related to a specific source paper
-
-**Arguments**:
-- `paper_path` (required): Path to PDF or LaTeX file to analyze
-- `analysis_focus` (optional): Focus area - 'methodology', 'application domain', 'theoretical contributions', or 'all' (default: 'all')
-- `comparison_type` (optional): Type of comparison - 'similar_methods', 'related_problems', 'same_domain', 'theoretical_connections' (default: 'related_problems')
-- `venues` (optional): Conference venues to search (default: ICLR.cc, NeurIPS.cc, ICML.cc)
-- `years` (optional): Years to search (default: last 3 years)
-- `max_papers` (optional): Maximum papers to find (default: 12)
-
-**Example Usage**:
-```
-paper_path: "./papers/my_research_paper.pdf"
-analysis_focus: "methodology"
-comparison_type: "similar_methods"
-max_papers: 15
-```
-
-### 2. `literature_review`
-**Purpose**: Conduct comprehensive and systematic literature reviews with topic-based discovery.
-
-**Use Cases**:
-- Systematic literature reviews for research proposals
-- Comprehensive coverage of a research area
-- Finding papers on a specific topic or research question
-- Multi-faceted topic exploration with related areas
-- Building reference collections for academic writing
-
-**Arguments**:
-- `main_topic` (required): Main research topic, research question, or paper description to investigate
-- `source_context` (optional): Context from existing work, abstracts, or specific research focus to guide keyword extraction
-- `related_topics` (optional): Comma-separated list of related topics, subtopics, or alternative terms to explore
-- `research_scope` (optional): 'focused' (10 papers, specific), 'standard' (15 papers, balanced), 'comprehensive' (25 papers, broad coverage) (default: 'standard')
-- `venues` (optional): Conference venues to search (default: ICLR.cc, NeurIPS.cc, ICML.cc)
-- `time_range` (optional): 'recent' (2 years), 'standard' (3 years), 'comprehensive' (5 years) (default: 'standard')
-
-**Example Usage**:
-```
-main_topic: "multimodal machine learning for medical imaging"
-related_topics: "vision-language models, medical AI, cross-modal attention"
-research_scope: "comprehensive"
-time_range: "comprehensive"
-```
-
-## Key Differences
-
-| Aspect | `analyze_paper_find_similar` | `literature_review` |
-|--------|------------------------------|---------------------|
-| **Input** | Existing paper file (PDF/LaTeX) | Research topic/question |
-| **Approach** | Paper content analysis → keyword extraction | Topic analysis → keyword strategy |
-| **Focus** | Finding work similar to specific paper | Comprehensive topic coverage |
-| **Output** | Papers similar to source paper | Systematic literature collection |
-| **Tools Used** | `search_papers_on_openreview` → `export_papers` | `search_papers_on_openreview` → `export_papers` |
-| **Export Dir** | `./papers/openreview_exports/similar_papers/` | `./papers/openreview_exports/literature_review/` |
-| **Search Strategy** | High precision (min_score 0.8) | Balanced coverage (min_score 0.75) |
-| **Loop Prevention** | Allowed to run more than once but avoid loops, proceed with results | Allowed to run more than once but avoid loops, proceed with results |
-
-## Workflow Overview
-
-Both prompts follow a structured approach:
-
-### `analyze_paper_find_similar` Workflow:
-1. **Source Paper Analysis**: Extract content from PDF/LaTeX file
-2. **Keyword Extraction**: Identify key concepts based on analysis focus
-3. **Strategic Search**: Use `search_papers_on_openreview` tool with extracted keywords
-4. **Export Collection**: Use `export_papers` tool for organized download
-5. **Similarity Report**: Analyze how found papers relate to source
-
-### `literature_review` Workflow:
-1. **Topic Analysis**: Extract effective search terms from research topic
-2. **Keyword Strategy**: Develop comprehensive search approach
-3. **Systematic Search**: Use `search_papers_on_openreview` tool with strategic keywords
-4. **Export Organization**: Use `export_papers` tool with systematic naming
-5. **Research Synthesis**: Provide structured literature analysis
-
-## Default Configuration
-
-The prompts use these optimized defaults:
-
-| Parameter | `analyze_paper_find_similar` | `literature_review` |
-|-----------|------------------------------|---------------------|
-| **Venues** | ICLR.cc, NeurIPS.cc, ICML.cc | ICLR.cc, NeurIPS.cc, ICML.cc |
-| **Search Fields** | title, abstract | title, abstract |
-| **Match Mode** | threshold | threshold |
-| **Match Threshold** | 0.6 | 0.5 |
-| **Min Score** | 0.8 (high precision) | 0.75 (balanced) |
-| **Max Papers** | 12 | 10-25 (scope dependent) |
-| **Years** | Last 3 years | 2-5 years (time_range dependent) |
-| **Search Strategy** | Allowed to run more than once but avoid loops | ONE Allowed to run more than once but avoid loops |
-
-## Output Structure
-
-Each workflow creates:
-
-- **JSON Files**: Structured metadata about found papers
-- **PDF Downloads**: Full paper downloads for offline reading
-- **Organized Exports**: Papers saved to specific subdirectories
-- **Analysis Reports**: Key findings and research insights
-
-### File Organization:
-```
-papers/openreview_exports/
-├── similar_papers/ # analyze_paper_find_similar outputs
-│ └── [source_paper]_similar_[comparison_type].json
-└── literature_review/ # literature_review outputs
- └── [topic]_review_[scope].json
-```
-
-## Integration with Tools
-
-These prompts orchestrate the following MCP tools in a two-step workflow:
-
-1. **`search_papers_on_openreview`**: Find relevant papers based on keywords and venues, returning paper IDs
-2. **`export_papers`**: Download PDFs and create organized JSON collections using the paper IDs from search results
-
-The prompts provide precise instructions on:
-- Sequential tool execution (search first, then export)
-- Paper ID extraction from search results
-- Tool parameter configuration
-- Error handling and validation
-- Output organization and naming
-
-## Tips for Effective Use
-
-### For `analyze_paper_find_similar`:
-1. **File Access**: Ensure the paper path is accessible and readable
-2. **Analysis Focus**: Choose specific focus for more targeted results
-3. **Comparison Type**: Select based on what aspect of similarity you want
-4. **File Formats**: Works with both PDF and LaTeX source files
-
-### For `literature_review`:
-1. **Topic Clarity**: Use precise, technical terminology in your main topic
-2. **Scope Selection**: Match scope to your research needs (focused/standard/comprehensive)
-3. **Related Topics**: Include synonyms and alternative terms for broader coverage
-4. **Context Utilization**: Provide source context to guide keyword extraction
-
-### General Best Practices:
-1. **Venue Selection**: Add domain-specific venues for specialized topics
-2. **Time Range**: Adjust based on field evolution and research currency
-3. **Quality Thresholds**: Higher min_score for more precise results
-4. **Export Organization**: Use descriptive names for easy file management
+# XtraMCP Server – Orchestration Prompts
+
+XtraMCP is a **custom MCP-based orchestration server** that powers PaperDebugger’s higher-level workflows:
+
+- 🧑🔬 **Researcher** – find and position your work within the literature
+- 🧑⚖️ **Reviewer** – critique drafts like a top-tier ML reviewer
+- ✍️ **Enhancer** – perform fine-grained, context-aware rewrites
+- 🧾 **Conference Formatter** (WIP) – adapt drafts to conference templates (NeurIPS, ICLR, AAAI, etc.)
+
+This document describes the core tools exposed by XtraMCP and how they combine into these workflows.
+
+> **Note:** XtraMCP is currently **closed-source** while the API and deployment story stabilize.
+> PaperDebugger runs fully without it; connecting XtraMCP unlocks the advanced research/review pipelines described here.
+
+---
+
+## Tool Overview
+
+| Tool Name | Role | Purpose | Primary Data Source |
+|---------------------------|-----------|-----------------------------------------------------------------|-----------------------------|
+| `search_relevant_papers` | Researcher | Fast semantic search over recent CS papers in a local vector DB, enhanced with semantic re-ranker module | Local vector database |
+| `deep_research` | Researcher | Multi-step literature synthesis & positioning of your draft | Local DB + retrieved papers |
+| `online_search_papers` | Researcher | Online search over external academic corpora | OpenReview + arXiv |
+| `review_paper` | Reviewer | Conference-style structured review of a draft | Your draft |
+| `enhance_academic_writing`| Enhancer | Context-aware rewriting and polishing of selected text | Your draft + XtraGPT |
+| `get_user_papers`| Misc | Fetch all papers, alongside description, published (OpenReview) by a specific user identified by email | User's email address
+
+---
+
+## 1. `search_relevant_papers`
+
+**Purpose:**
+Search for similar or relevant papers by keywords or extracted concepts against a **local database of academic papers**.
This tool uses semantic search with vector embeddings to find the most relevant results, enhanced with a re-ranker module to better capture nuance. It is fast and the default and recommended tool for paper searches.
+
+**How it works:**
+
+- Recent CS papers (last few years) are **vectorized** into a local index.
+- Queries (from your topic or draft) are embedded and matched via **similarity search**.
+- Results are reranked by an **LLM-based reranker** for better semantic alignment.
+
+**Typical usage:**
+
+- “Find the 10 most relevant papers to this draft.”
+- “Search for relevant works on diffusion models for imbalanced medical imaging.”
+
+---
+
+## 2. `deep_research`
+
+**Purpose:**
+Given a **research topic or draft paper**, perform multi-step literature exploration and synthesis. Summarize their findings, and provide insights on similarities and differences to assist in the research process.
+
+**How it works:**
+
+1. Uses `search_relevant_papers` (and optionally `online_search_papers`) to retrieve candidate works.
+2. Summarizes key ideas, methods, and results from retrieved papers.
+3. Performs **chain-of-thought style analysis** to:
+ - highlight similarities/differences vs your draft,
+ - surface missing baselines or evaluation settings,
+ - suggest how to position your contribution.
+
+**Typical usage:**
+
+- “deep_research to compare my draft to recent work on retrieval-augmented generation.”
+- “For this topic, deep_research 5-10 relevant papers and explain where the open gaps are.”
+
+---
+
+## 3. `online_search_papers`
+
+**Purpose:**
+Expand beyond the local DB to search **online academic corpora** (OpenReview + arXiv). This tool is ideal for discovering recent or broader papers beyond those available in the local database.
+
+**How it works:**
+
+- Called when local search is **too sparse** (new topic) or you explicitly want the **latest** work.
+- Queries both **OpenReview** and **arXiv** for up-to-date results.
+- Results can then be fed into `deep_research` for synthesis.
+
+**Typical usage:**
+
+- “My topic is very new. Look online for the latest preprints from OpenReview/arXiv.”
+
+---
+
+## 4. `review_paper`
+
+**Purpose:**
+Analyze and review a draft against the standards of **top-tier ML conferences** (ICLR, ICML, NeurIPS). Identifies improvements and issues in structure, completeness, clarity, and argumentation, then provides prioritized, actionable suggestions.
+
+**How it works:**
+
+- **Pass A – Deterministic checks (fast, high-precision)**
+ - Required sections present (e.g., Abstract, Method, Experiments, Limitations/Broader Impact).
+ - Abstract contains problem, approach, core results, significance.
+ - Acronyms defined at first use; “TODO”, “FIXME”, “Figure ??” flags.
+ - Figures/tables referenced; equation references consistent; citation style uniform.
+ - Reproducibility signals: code/data availability, hyperparameters, seeds, compute, eval protocol.
+
+- **Pass B – Section-aware LLM critiques**
+ - Run per section with **venue-aware rubrics** (NeurIPS/ICML/ICLR style).
+ - Suggest *minimal, targeted edits* (what to add/remove/clarify).
+ - Focus on clarity, completeness, and logical flow.
+
+- **Pass C – Cross-checks (claims vs evidence)**
+ - Are “state-of-the-art” claims backed by numbers + baselines?
+ - Are method components properly ablated?
+ - Are there red flags for data leakage, HPO on test sets, or missing uncertainty reporting?
+
+- **Prioritization**
+ - Each issue is scored by severity (blocker/major/minor), impact, and confidence.
+ - Duplicates are merged and **top-N issues** are surfaced as “quick fixes” vs “substantial rewrites”.
+
+**Typical usage:**
+
+- “review_paper this draft like a NeurIPS reviewer and give me the top 10 issues to fix.”
+- “review_paper on method clarity and experimental rigor.”
+
+---
+
+## 5. `enhance_academic_writing`
+
+**Purpose:**
+Suggest **context-aware academic writing enhancements** for selected text.
+
+**How it works:**
+
+- Powered by **XtraGPT models** tuned for academic style and LaTeX-heavy text.
+- Uses surrounding context (section, paper intent, venue) to:
+ - improve clarity and flow,
+ - reduce redundancy and filler,
+ - keep technical content intact,
+ - align tone with ML/AI papers.
+
+**Typical usage:**
+
+- "enhance_academic_writing this paragraph to be clearer and more concise, preserving all technical details.”
+- "enhance_academic_writing the abstract to be suitable for NeurIPS.”
+
+## 6. `get_user_papers`
+
+**Purpose:**
+Retrieve **all papers authored by a given user** (OpenReview), identified by email.
+Useful for quickly assembling a researcher’s publication list or grounding context for comparison/positioning.
+
+**How it works:**
+- Queries the paper database for matching author email(s).
+- Returns structured metadata: title, authors, venue, year, abstract, and identifiers.
+- Often used as a preprocessing step before `deep_research`.
+
+**Typical usage:**
+- “get_user_papers for
in summary mode.”
+- “Retrieve all publications by this researcher and then compare my draft using deep_research.”
+
+## 7. Conference Formatter (WIP)
+
+Upcoming workflows will:
+
+- map your draft onto specific **conference templates** (NeurIPS, ICLR, AAAI, etc.),
+- adjust sectioning, citation style, and boilerplate requirements,
+- highlight formatting and policy mismatches (e.g., ethics, broader impact sections).
+
+---
+
+## Putting It Together: Example Orchestrated Flows
+
+- **Researcher Flow**
+ 1. Use `search_relevant_papers` on your draft or topic.
+ 2. If results are thin or stale, fall back to `online_search_papers`.
+ 3. Call `deep_research` to synthesize and position your work.
+
+- **Reviewer Flow**
+ 1. Run `review_paper` on the full draft.
+ 2. For high-impact issues, call `enhance_academic_writing` on the relevant spans.
+
+- **Enhancer Flow**
+ 1. Select a paragraph or section in Overleaf.
+ 2. Call `enhance_academic_writing` with your preferences (e.g., “more formal”, “shorter”).
+ 3. Use edit-diff tool to effect changes.
