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Research Agent

A Docker-based research assistant with MCP (Model Context Protocol) architecture and paper graph visualization.

Reference Graph

NeurIPS Graph

Architecture

┌─────────────────────────────────────────────────────────────────────┐
│                           Web UI (React)                             │
│  ┌──────────────────────────┐  ┌──────────────────────────────────┐ │
│  │   GlobalGraphPage (B)    │  │      PaperGraphPage (A)          │ │
│  │   - All papers overview  │  │   - Reference exploration        │ │
│  │   - Embedding similarity │  │   - Incremental expansion        │ │
│  └────────────┬─────────────┘  └───────────────┬──────────────────┘ │
│               └────────────────┬───────────────┘                    │
│                                │ HTTP :3000                         │
└────────────────────────────────┼────────────────────────────────────┘
                                 │
┌────────────────────────────────┼────────────────────────────────────┐
│                        Agent Layer                                   │
│  ┌─────────┐  ┌──────────┐  ┌──────────┐  ┌─────────────┐          │
│  │ client  │──│ planner  │──│ executor │──│   memory    │          │
│  │ (entry) │  │          │  │          │  │             │          │
│  └────┬────┘  └──────────┘  └─────┬────┘  └─────────────┘          │
│       │         Planning          │         State                   │
│       │         (no side-effects) │         Storage                 │
└───────┼───────────────────────────┼─────────────────────────────────┘
        │                           │
        │      HTTP API :8000       │
        ▼                           ▼
┌─────────────────────────────────────────────────────────────────────┐
│                          MCP Layer                                   │
│  ┌─────────┐  ┌──────────┐  ┌─────────────────────────────────────┐ │
│  │ server  │──│ registry │──│              tools/                 │ │
│  │ (entry) │  │ (SSOT)   │  │  pdf | arxiv | web_search | graph   │ │
│  └─────────┘  └──────────┘  └─────────────────────────────────────┘ │
│                               Side-effects allowed                   │
└─────────────────────────────────────────────────────────────────────┘

Key Principles

Separation of Concerns
- Agent Layer: Thinking, planning, decision-making (NO side-effects)
- MCP Layer: Tool execution, file I/O, API calls (side-effects allowed)
- Web UI: Visualization and interaction
Single Source of Truth (SSOT)
- registry.py is the ONLY place where tools are discovered and collected
- Tools are auto-discovered from mcp/tools/ directory
Single Entry Points
- mcp/server.py - MCP server entry point
- agent/client.py - Agent entry point
- Other modules (planner, executor, memory) are NEVER executed directly

Project Structure

Research_agent/
├─ mcp/                          # MCP Layer (side-effects allowed)
│  ├─ __init__.py
│  ├─ server.py                  # MCP server entrypoint
│  ├─ registry.py                # Tool auto-discovery (SSOT)
│  ├─ base.py                    # Tool base classes
│  └─ tools/
│     ├─ pdf.py                  # PDF extraction tools
│     ├─ refer.py                # Reference extraction tools
│     ├─ arxiv.py                # arXiv API tools
│     ├─ web_search.py           # Web search tools (Tavily)
│     └─ paper_graph.py          # Paper graph tools (Graph A/B)
│
├─ agent/                        # Agent Layer (no side-effects)
│  ├─ __init__.py
│  ├─ client.py                  # Agent entrypoint (orchestration)
│  ├─ planner.py                 # Goal → plan creation
│  ├─ executor.py                # Plan → MCP calls
│  └─ memory.py                  # State storage
│
├─ web/                          # Web UI (React/TypeScript)
│  ├─ api/mcp.ts                 # MCP REST client
│  ├─ components/
│  │  ├─ GraphCanvas.tsx         # D3.js force-directed graph
│  │  ├─ SidePanel.tsx           # Paper details panel
│  │  └─ PaperCard.tsx           # Paper metadata card
│  ├─ pages/
│  │  ├─ GlobalGraphPage.tsx     # Graph B - All papers overview
│  │  └─ PaperGraphPage.tsx      # Graph A - Reference exploration
│  ├─ App.tsx                    # Router setup
│  ├─ main.tsx                   # Entry point
│  └─ package.json
│
├─ requirements/
│  ├─ base.txt                   # Common dependencies
│  ├─ mcp.txt                    # MCP server dependencies
│  └─ agent.txt                  # Agent dependencies
│
├─ docker/
│  ├─ Dockerfile.mcp             # MCP server image
│  ├─ Dockerfile.agent           # Agent image
│  └─ Dockerfile.web             # Web UI image
│
├─ scripts/
│  ├─ run-mcp.sh                 # Start MCP server
│  └─ process-all.sh             # Process all PDFs
│
├─ pdf/                          # Input PDF files
├─ output/                       # Extracted content
│  ├─ images/                    # Extracted images
│  ├─ text/                      # Extracted text
│  └─ graph/                     # Graph cache
│     ├─ global_graph.json       # Global graph (Graph B)
│     └─ paper/                  # Per-paper graphs (Graph A)
│        └─ <paper_id>.json
│
├─ .env.example                  # Environment template
├─ docker-compose.yml            # Service orchestration
└─ README.md

Paper Graph System

Graph A: Paper Mode (Reference Exploration)

Purpose: Explore references of a specific paper
Behavior: On-demand, incremental expansion
Usage: Double-click nodes to expand their references
Center: Selected paper is fixed at center

Graph B: Global Mode (All Papers Overview)

Purpose: Visualize relationships across all papers
Behavior: Batch processing with embedding-based similarity
Clustering: Louvain community detection
Similarity: SentenceTransformer embeddings

Quick Start

1. Setup Environment

# Clone the repository
git clone <repo-url>
cd Research_agent

# Create .env file
cp .env.example .env
# Edit .env and add your API keys:
# - OPENAI_API_KEY (required)
# - TAVILY_API_KEY (optional, for web search)

2. Build Docker Images

docker compose build

3. Add PDF Files

cp /path/to/your/papers/*.pdf ./pdf/

4. Run

Start All Services:

# Start MCP server and Web UI
docker compose up -d mcp-server web

# Open Web UI
open http://localhost:3000

Interactive Agent:

# Run Agent interactively
docker compose run --rm agent

Single Command:

docker compose run --rm agent "List all PDFs and extract text from each"

Process All PDFs:

./scripts/process-all.sh

Available Tools

PDF Tools

Tool	Description
`list_pdfs`	List all PDF files in the directory
`extract_text`	Extract text from a PDF
`extract_images`	Extract images from a PDF
`extract_all`	Extract text and images
`process_all_pdfs`	Process all PDFs
`get_pdf_info`	Get PDF metadata
`read_extracted_text`	Read previously extracted text
`check_github_link`	Find GitHub repository URLs in extracted text

arXiv Tools

Tool	Description
`arxiv_search`	Search arXiv for papers
`arxiv_get_paper`	Get paper details by ID
`arxiv_download`	Download paper PDF

Web Search Tools

Tool	Description
`web_search`	Search the web (Tavily)
`web_get_content`	Fetch URL content
`web_research`	In-depth topic research

Ranking Tools

Tool	Description
`update_user_profile`	Update interests/keywords and toggle `exclude_local_papers` (writes to `OUTPUT_DIR/users/profile.json`).
`apply_hard_filters`	Apply ALREADY_READ, blacklist keywords, and year filters.
`calculate_semantic_scores`	Compute hybrid semantic relevance scores (embeddings + optional LLM for borderline cases).
`evaluate_paper_metrics`	Compute dimension scores (keywords/authors/institutions/recency/practicality) and soft penalties.
`rank_and_select_top_k`	Combine scores, compute final ranking, and optionally add a contrastive paper.

Paper Graph Tools

Tool	Description
`has_pdf`	Check if PDF exists for a paper ID
`fetch_paper_if_missing`	Download from arXiv if not present
`extract_references`	Extract references from a PDF
`get_references`	Get cached references for a paper
`build_reference_subgraph`	Build Graph A (paper-centered)
`build_global_graph`	Build Graph B (all papers)

API Endpoints

The MCP server exposes a REST API at http://localhost:8000:

# List all tools
curl http://localhost:8000/tools

# Get tools in OpenAI format
curl http://localhost:8000/tools/schema

# Execute a tool
curl -X POST http://localhost:8000/tools/list_pdfs/execute \
  -H "Content-Type: application/json" \
  -d '{"arguments": {}}'

# Graph endpoints
curl http://localhost:8000/tools/build_global_graph/execute \
  -H "Content-Type: application/json" \
  -d '{"arguments": {"similarity_threshold": 0.7}}'

# Convenience endpoints
curl http://localhost:8000/pdf/list
curl "http://localhost:8000/arxiv/search?query=transformer"

Web UI

Access the web interface at http://localhost:3000:

Page	URL	Description
Global Graph	`/`	Overview of all papers (Graph B)
Paper Graph	`/paper/:id`	Reference exploration for a paper (Graph A)

Graph Interactions

Click: Select a node to view details
Double-click: Expand references (Graph A only)
Drag: Reposition nodes
Controls: Adjust similarity threshold, rebuild graph

Example Usage

You: What PDFs do I have?
  [Calling list_pdfs...]
Assistant: You have 3 PDF files: paper1.pdf, paper2.pdf, paper3.pdf

You: Search arXiv for papers about attention mechanisms
  [Calling arxiv_search...]
Assistant: Found 10 papers about attention mechanisms...

You: Download the first one and extract its content
  [Calling arxiv_download...]
  [Calling extract_all...]
Assistant: Downloaded and extracted the paper. Here's a summary...

You: Build a reference graph for paper 2106.09685
  [Calling build_reference_subgraph...]
Assistant: Built reference graph with 15 papers and 23 edges.

Requirements

Docker & Docker Compose
OpenAI API key
(Optional) Tavily API key for web search

License

MIT

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Saved searches

Use saved searches to filter your results more quickly

Repository files navigation

Notion Save 사용법

Research Agent

Reference Graph

NeurIPS Graph

Architecture

Key Principles

Project Structure

Paper Graph System

Graph A: Paper Mode (Reference Exploration)

Graph B: Global Mode (All Papers Overview)

Quick Start

1. Setup Environment

2. Build Docker Images

3. Add PDF Files

4. Run

Available Tools

PDF Tools

arXiv Tools

Web Search Tools

Ranking Tools

Paper Graph Tools

API Endpoints

Web UI

Graph Interactions

Example Usage

Requirements

License

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Name		Name	Last commit message	Last commit date
Latest commit History 250 Commits
agent		agent
data		data
docker		docker
instruction		instruction
logs		logs
mcp		mcp
output		output
pdf		pdf
requirements		requirements
scripts		scripts
tests		tests
web		web
.gitignore		.gitignore
README.md		README.md
docker-compose.yml		docker-compose.yml
pytest.ini		pytest.ini
remember.txt		remember.txt

hub2vu/Research_agent

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Notion Save 사용법

Research Agent

Reference Graph

NeurIPS Graph

Architecture

Key Principles

Project Structure

Paper Graph System

Graph A: Paper Mode (Reference Exploration)

Graph B: Global Mode (All Papers Overview)

Quick Start

1. Setup Environment

2. Build Docker Images

3. Add PDF Files

4. Run

Available Tools

PDF Tools

arXiv Tools

Web Search Tools

Ranking Tools

Paper Graph Tools

API Endpoints

Web UI

Graph Interactions

Example Usage

Requirements

License

About

Resources

Uh oh!

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Watchers

Forks

Releases

Packages 0

Contributors 4

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Languages

Packages