Medium Blog MCP Server
├── Research Engine (Wikipedia, arXiv, Web, Images)
├── AI Content Generator (Claude API)
├── Image Handler (Download + AI Description)
├── Quality Analyzer (Readability, Citations, SEO)
├── Medium Exporter (Markdown + Assets)
└── SQLite Database (Sessions, Drafts, Research)

# Clone repository
git clone <your-repo-url>
cd medium-blog-mcp

# Activate virtual environment
uv init
uv sync

# Install dependencies
uv add -r requirements.txt

# use these uv commands to test , run mcp servers
Test the server - uv run fastmcp dev main.py
Run the server - uv run fastmcp run main.py
Add the server to claude desktop - uv run fastmcp install
claude-desktop main.py

# Copy environment template
cp .env.example .env

# Edit .env and add your DB URL
# DATABASE_URL=YOUR_SQLITE_DB_URL

python main.py

{
  "mcpServers": {
    "medium-blog-generator": {
      "command": "[Your/Path/to/uv]",
      "args": [
        "--directory",
        "C:\\medium_mcp",
        "run",
        "fastmcp",
        "run",
        "main.py"
      ],
      "env": {},
      "transport": "stdio",
      "type": null,
      "cwd": null,
      "timeout": null,
      "description": null,
      "icon": null,
      "authentication": null
    }
  }
}

create_blog_session(topic="Latest AI Model Advancements", target_length="medium")

research_topic(session_id="abc123", depth="comprehensive")
get_research_summary(session_id="abc123")  # Review research
approve_research(session_id="abc123")       # Approve to continue

generate_outline(session_id="abc123", style="technical", num_sections=5)
# Review outline, optionally modify
approve_outline(session_id="abc123")

generate_full_content(session_id="abc123")
get_full_draft(session_id="abc123")  # Review full draft

prepare_plagiarism_chunks(session_id="abc123")
# Copy chunks to Grammarly/QuillBot/GPTZero manually
record_plagiarism_result(session_id="abc123", chunk_id=1, 
                        plagiarism_score=2.3, ai_detection_score=8.5, 
                        tool_used="Grammarly")

run_quality_analysis(session_id="abc123")  # Get detailed QA report
approve_final_draft(session_id="abc123")   # Final approval

export_to_medium(session_id="abc123")

medium-blog-mcp/
├── main.py                   # FastMCP server (all tools)
├── database.py               # SQLAlchemy models & DB operations
├── research.py               # Multi-source research engine
├── content_generator.py      # Claude API content generation
├── image_handler.py          # Image download & AI descriptions
├── quality.py                # Quality analysis & readability
├── exporter.py               # Medium markdown export
├── config.py                 # Configuration management
├── requirements.txt          # Python dependencies
├── .env.example              # Environment variables template
├── README.md                 # This file
└── data/                     # Generated data (auto-created)
    ├── blog_database.db      # SQLite database
    ├── sessions/             # Session-specific data
    │   └── {session_id}/
    │       └── images/       # Downloaded images
    ├── exports/              # Final exports
    │   └── {session_id}/
    │       ├── blog_post.md
    │       ├── images/
    │       ├── citations.txt
    │       ├── metadata.json
    │       └── qa_report.txt
    └── images/               # Image storage

# 1. Create session
create_blog_session(topic="GPT-4 vs Claude 3: Technical Comparison", target_length="medium")
# Returns: {"session_id": "abc123", ...}

# 2. Research
research_topic(session_id="abc123", depth="comprehensive")
get_research_summary(session_id="abc123")
# Review the 15-20 sources gathered
approve_research(session_id="abc123")

# 3. Generate outline
generate_outline(session_id="abc123", style="technical", num_sections=5)
# Review outline structure
approve_outline(session_id="abc123")

# 4. Generate content
generate_full_content(session_id="abc123")
get_full_draft(session_id="abc123")
# Review the ~2500 word blog with images

# 5. Check plagiarism manually
prepare_plagiarism_chunks(session_id="abc123")
# Copy chunks to Grammarly, check, then:
record_plagiarism_result(session_id="abc123", chunk_id=1, 
                        plagiarism_score=1.8, ai_detection_score=7.2, 
                        tool_used="Grammarly")

# 6. Quality analysis
run_quality_analysis(session_id="abc123")
# Review QA report
approve_final_draft(session_id="abc123")

# 7. Export
export_to_medium(session_id="abc123")
# Get Medium-ready markdown + all assets!

# Reset database (WARNING: deletes all data)
rm data/blog_database.db
python main.py  # Will recreate database