┌─────────────────────────────────────────────────┐
│              Streamlit Frontend                 │
│              app.py  —  Chat UI                 │
│         Live step cards · Download button       │
└───────────────────┬─────────────────────────────┘
                    │  FastMCP Client (protocol-aware)
┌───────────────────▼─────────────────────────────┐
│           FastMCP Server  (server.py)           │
│                                                 │
│  🔎 search_web        🌐 fetch_and_chunk        │
│     Tavily API           httpx + HTML parser    │
│                                                 │
│  🧠 cluster_findings  📄 generate_report        │
│     TF-IDF + K-Means     Markdown / JSON        │
└─────────────────────────────────────────────────┘

git clone https://github.com/yourusername/deep-research-agent.git
cd deep-research-agent

pip install -r requirements.txt

cp .env.example .env

TAVILY_API_KEY=tvly-your-key-here
MCP_HOST=localhost
MCP_PORT=8000
TAVILY_SEARCH_DEPTH=advanced

# Terminal 1
python server.py

🔍 Deep Research Agent MCP Server
   Host : localhost
   Port : 8000
   Tools: search_web, fetch_and_chunk, cluster_findings, generate_report
   Tavily key: ✓ set

# Terminal 2
streamlit run app.py

search_web(
    query="AI energy crisis 2026",
    max_results=8,              # 1–15
    include_domains=None,       # e.g. [".edu", ".gov"]
    exclude_domains=None
)

fetch_and_chunk(
    urls=["https://example.com/article"],
    chunk_size=400,             # words per chunk
    chunk_overlap=50,           # overlap between chunks
    max_chunks_per_url=6
)

cluster_findings(
    chunks=[...],               # from fetch_and_chunk
    n_clusters=4,               # 2–6 themes
    top_terms_per_cluster=8
)

generate_report(
    topic="AI energy crisis 2026",
    clusters=[...],             # from cluster_findings
    format="markdown",          # or "json"
    include_sources=True
)

📝 User enters topic
        │
        ▼
🔎 search_web() × 3 queries ──────────► 24 ranked sources
        │
        ▼
🌐 fetch_and_chunk() on top 5 URLs ───► 20–30 text chunks
        │
        ▼
🧠 cluster_findings() ────────────────► 4 semantic themes
        │
        ▼
📄 generate_report() ─────────────────► Structured .md report
        │
        ▼
⬇️  Download / Display in UI

deep-research-agent/
│
├── 📄 server.py          # FastMCP server — all 4 tools
├── 🖥️  app.py             # Streamlit frontend
├── 📋 requirements.txt   # Python dependencies
├── 🔒 .env.example       # Environment variable template
└── 📖 README.md          # This file

MIT License

Copyright (c) 2026 Deep Research Agent Contributors

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including, without limitation, the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES, OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT, OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.