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Smithsonian Open Access MCP Server

by molanojustin

Smithsonian Open Access MCP Server

npm version NPM Downloads

A Model Context Protocol (MCP) server that provides AI assistants with access to the Smithsonian Institution's Open Access collections. This server allows AI tools like Claude Desktop to search, explore, and analyze over 3 million collection objects from America's national museums.

Quick Start

Option 1: npm/npx Installation (Easiest)

The npm package includes automatic Python dependency management and works across platforms:

# Install globally npm install -g @molanojustin/smithsonian-mcp # Or run directly with npx (no installation needed) npx -y @molanojustin/smithsonian-mcp # Set your API key export SMITHSONIAN_API_KEY=your_key_here # Start the server smithsonian-mcp

Option 2: Automated Setup (Recommended for Python users)

The enhanced setup script now includes:

  • API key validation - Tests your key before saving

  • Service installation - Auto-install as system service

  • Claude Desktop config - Automatic configuration

  • Health checks - Verify everything works macOS/Linux:

chmod +x setup.sh ./setup.sh

Windows:

.\setup.ps1

Option 3: Manual Setup

  1. Get API Key: api.data.gov/signup (free)

  2. Install: pip install -r requirements.txt

  3. Configure: Copy .env.example to .env and set your API key

  4. Test: python examples/test-api-connection.py

Verify Setup

Run the verification script to check your installation:

python scripts/verify-setup.py

Features

Core Functionality

  • Search Collections: 3+ million objects across 19 Smithsonian museums

  • Object Details: Complete metadata, descriptions, and provenance

  • On-View Status: ⭐ NEW - Find objects currently on physical exhibit

  • Image Access: High-resolution images (CC0 licensed when available)

  • 3D Models: Interactive 3D content where available

  • Museum Information: Browse all Smithsonian institutions

AI Integration

  • 12 MCP Tools: Search, filter, retrieve collection data, check exhibition status, and get context

  • Smart Context: Contextual data sources for AI assistants

  • Rich Metadata: Complete object information and exhibition details

  • Exhibition Planning: ⭐ NEW - Tools to find and explore currently exhibited objects

Integration

Claude Desktop

Option 1: Using npm/npx (Recommended)

  1. Configure (claude_desktop_config.json):

{ "mcpServers": { "smithsonian_open_access": { "command": "npx", "args": ["-y", "@molanojustin/smithsonian-mcp"], "env": { "SMITHSONIAN_API_KEY": "your_key_here" } } } }

Option 2: Using Python installation

  1. Configure (claude_desktop_config.json):

{ "mcpServers": { "smithsonian_open_access": { "command": "python", "args": ["-m", "smithsonian_mcp.server"], "env": { "SMITHSONIAN_API_KEY": "your_key_here" } } } }

Or copy the provided

  1. Test: Ask Claude "What Smithsonian museums are available?"

mcpo Integration (MCP Orchestrator)

mcpo is an MCP orchestrator that converts multiple MCP servers into OpenAPI/HTTP endpoints, ideal for combining multiple services into a single systemd service.

Installation

# Install mcpo pip install mcpo # Or using uvx uvx mcpo --help

Configuration

Create a mcpo-config.json file:

{ "mcpServers": { "smithsonian_open_access": { "command": "python", "args": ["-m", "smithsonian_mcp.server"], "env": { "SMITHSONIAN_API_KEY": "your_api_key_here" } }, "memory": { "command": "npx", "args": ["-y", "@modelcontextprotocol/server-memory"] }, "time": { "command": "uvx", "args": ["mcp-server-time", "--local-timezone=America/New_York"] } } }

Running with mcpo

# Start mcpo with hot-reload mcpo --config mcpo-config.json --port 8000 --hot-reload # With API key authentication mcpo --config mcpo-config.json --port 8000 --api-key "your_secret_key" # Access endpoints: # - Smithsonian: http://localhost:8000/smithsonian_open_access # - Memory: http://localhost:8000/memory # - Time: http://localhost:8000/time # - API docs: http://localhost:8000/docs

Systemd Service

Create /etc/systemd/system/mcpo.service:

[Unit] Description=MCP Orchestrator Service After=network.target [Service] Type=simple User=your-user WorkingDirectory=/path/to/your/config Environment=PATH=/path/to/venv/bin ExecStart=/path/to/venv/bin/mcpo --config mcpo-config.json --port 8000 Restart=always RestartSec=10 [Install] WantedBy=multi-user.target
# Enable and start service sudo systemctl enable mcpo sudo systemctl start mcpo sudo systemctl status mcpo

Troubleshooting mcpo

"ModuleNotFoundError: No module named 'smithsonian_mcp'" This occurs when mcpo can't find the Smithsonian MCP module. Fix by:

  1. Use absolute Python path in your mcpo config:

{ "command": "/full/path/to/your/project/.venv/bin/python", "env": { "PYTHONPATH": "/full/path/to/your/project" } }
  1. Verify paths:

# Check Python executable exists ls -la /path/to/your/project/.venv/bin/python # Test module import /path/to/your/project/.venv/bin/python -c "import smithsonian_mcp; print('OK')"
  1. Regenerate config with setup script:

./setup.sh # Will create mcpo-config.json with correct paths

"Connection closed" errors

  • Ensure API key is valid and set in environment

  • Check that the virtual environment has all dependencies installed

  • Verify the MCP server can start manually: python -m smithsonian_mcp.server --test

"Port 8000 already in use"

# Check what's using the port lsof -i :8000 # Or use different port mcpo --config mcpo-config.json --port 8001

VS Code

  1. Open Workspace: code .vscode/smithsonian-mcp-workspace.code-workspace

  2. Run Tasks: Debug, test, and develop the MCP server

  3. Claude Code: AI-assisted development with Smithsonian data

Available Data

  • 19 Museums: NMNH, NPG, SAAM, NASM, NMAH, and more

  • 3+ Million Objects: Digitized collection items

  • CC0 Content: Public domain materials for commercial use

  • Rich Metadata: Creators, dates, materials, dimensions

  • High-Resolution Images: Professional photography

  • 3D Models: Interactive digital assets

MCP Tools

Search & Discovery

  • search_collections - Advanced search with filters (now includes on_view parameter)

  • get_object_details - Detailed object information

  • search_by_unit - Museum-specific searches

  • get_objects_on_view - NEW - Find objects currently on physical exhibit

  • check_object_on_view - NEW - Check if a specific object is on display

Information & Context

  • get_smithsonian_units - List all museums

  • get_collection_statistics - Collection metrics

  • get_search_context - Get search results as context data

  • get_object_context - Get detailed object information as context

  • get_units_context - Get list of units as context data

  • get_stats_context - Get collection statistics as context

  • get_on_view_context - NEW - Get currently exhibited objects as context

New: On-View Functionality 🎨

What's New in Phase 1

The MCP server now includes comprehensive support for finding objects currently on physical exhibit at Smithsonian museums. This is a priority feature aligned with the Smithsonian's official API documentation.

Key Features

  • Find Exhibited Objects: Search for objects currently on display

  • Check Exhibition Status: Verify if specific objects are on view

  • Filter by Museum: Find what's on display at specific Smithsonian units

  • Exhibition Details: Access exhibition title and location information

  • Combined Filters: Mix on-view status with other search criteria

Usage Examples

Find all objects currently on view:

# Ask Claude: "What objects are currently on physical exhibit at the Smithsonian?" # Or with filters: "Show me paintings currently on display at the National Portrait Gallery"

Check if a specific object is on view:

# Ask Claude: "Is object edanmdm-nmah_1234567 currently on display?"

Combine with other filters:

# Ask Claude: "Find CC0 licensed objects currently on view with high-resolution images"

Tool Details

get_objects_on_view

Find objects currently on physical exhibit.

Parameters:

  • unit_code (optional): Filter by Smithsonian unit (e.g., "NMNH", "NPG")

  • limit: Maximum results (default: 20, max: 100)

  • offset: Pagination offset

Returns: Search results containing objects currently on exhibit

check_object_on_view

Check if a specific object is currently on display.

Parameters:

  • object_id: Unique identifier for the object

Returns: Object details including exhibition status

search_collections (enhanced)

Now includes on_view parameter for filtering.

New Parameter:

  • on_view (boolean): Filter objects by exhibition status

    • True: Only objects currently on display

    • False: Only objects not on display

    • None: No filter (default)

Implementation Notes

This feature is based on the Smithsonian's onPhysicalExhibit metadata field, which indicates whether an object is currently accessible to the public in a physical exhibition. The implementation includes:

  • Full API alignment with EDAN metadata model v1.09

  • Fielded search support using onPhysicalExhibit:"Yes" queries

  • Comprehensive test coverage (15 unit tests)

  • Exhibition metadata extraction (title, location)

Use Cases

Research & Education

  • Scholarly Research: Multi-step academic investigation

  • Lesson Planning: Educational content creation

  • Object Analysis: In-depth cultural object study

Curation & Exhibition

  • Exhibition Planning: Thematic object selection and visitor planning

  • Visit Planning: ⭐ NEW - Find what's currently on display before visiting

  • Exhibition Research: ⭐ NEW - Study current exhibition trends and displays

  • Collection Development: Gap analysis and acquisition

  • Digital Humanities: Large-scale analysis projects

Development

  • Cultural Apps: Applications using museum data

  • Educational Tools: Interactive learning platforms

  • API Integration: Professional development workflows

Requirements

For npm/npx installation:

  • Node.js 16.0 or higher

  • Python 3.10 or higher (auto-detected and dependencies managed)

  • API key from api.data.gov (free)

  • Internet connection for API access

For Python installation:

  • Python 3.10 or higher

  • API key from api.data.gov (free)

  • Internet connection for API access

Testing

Using npm/npx:

# Test API connection smithsonian-mcp --test # Run MCP server smithsonian-mcp # Show help smithsonian-mcp --help

Using Python:

# Test API connection python examples/test-api-connection.py # Run MCP server python -m smithsonian_mcp.server # Run test suite pytest tests/ # Run on-view functionality tests pytest tests/test_on_view.py -v # Run basic tests pytest tests/test_basic.py -v # Verify complete setup python scripts/verify-setup.py # VS Code Tasks (if using workspace) # - Test MCP Server # - Run Tests # - Format Code # - Lint Code

Service Management

Linux (systemd)

# Start service systemctl --user start smithsonian-mcp # Stop service systemctl --user stop smithsonian-mcp # Check status systemctl --user status smithsonian-mcp # Enable on boot systemctl --user enable smithsonian-mcp

macOS (launchd)

# Load service launchctl load ~/Library/LaunchAgents/com.smithsonian.mcp.plist # Unload service launchctl unload ~/Library/LaunchAgents/com.smithsonian.mcp.plist # Check status launchctl list | grep com.smithsonian.mcp

Windows

# Start service Start-Service SmithsonianMCP # Stop service Stop-Service SmithsonianMCP # Check status Get-Service SmithsonianMCP

Troubleshooting

Common Issues

"API key validation failed"

  • Get a free key from api.data.gov/signup

  • Ensure no extra spaces in your API key

  • Check that .env file contains: SMITHSONIAN_API_KEY=your_key_here

"Service failed to start"

  • Run python scripts/verify-setup.py for diagnostics

  • Check logs: journalctl --user -u smithsonian-mcp (Linux) or ~/Library/Logs/com.smithsonian.mcp.log (macOS)

  • Ensure virtual environment is activated

"Claude Desktop not connecting"

  • Restart Claude Desktop after configuration

  • Check Claude Desktop config file exists and contains correct paths

  • Verify MCP server is running: python -m smithsonian_mcp.server

"Module import errors"

  • Activate virtual environment: source .venv/bin/activate (Linux/macOS) or .\venv\Scripts\Activate.ps1 (Windows)

  • Reinstall dependencies: pip install -r requirements.txt

Getting Help

  1. Run verification script: python scripts/verify-setup.py

  2. Check the Integration Guide

  3. Review GitHub Issues

Documentation

  • Integration Guide: Claude Desktop and VS Code setup

  • API Reference: Complete tool and resource documentation

  • Examples: Real-world usage scenarios

  • Deployment Guide: Production deployment options

Contributing

  1. Fork the repository

  2. Create a feature branch

  3. Make your changes

  4. Run tests

  5. Submit a pull request

License

MIT License - see LICENSE file for details.

Acknowledgments

  • Smithsonian Institution for Open Access collections

  • api.data.gov for API infrastructure

  • FastMCP team for the MCP framework

  • Model Context Protocol community

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security - not tested
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license - not found
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quality - not tested

remote-capable server

The server can be hosted and run remotely because it primarily relies on remote services or has no dependency on the local environment.

Provides AI assistants with access to search, explore, and analyze over 3 million collection objects from the Smithsonian Institution's museums. Enables finding objects currently on exhibit, retrieving detailed metadata, high-resolution images, and 3D models from America's national museums.

  1. Quick Start
    1. Option 1: npm/npx Installation (Easiest)
    2. Option 2: Automated Setup (Recommended for Python users)
    3. Option 3: Manual Setup
    4. Verify Setup
  2. Features
    1. Core Functionality
    2. AI Integration
  3. Integration
    1. Claude Desktop
    2. mcpo Integration (MCP Orchestrator)
    3. VS Code
  4. Available Data
    1. MCP Tools
      1. Search & Discovery
      2. Information & Context
    2. New: On-View Functionality 🎨
      1. What's New in Phase 1
      2. Key Features
      3. Usage Examples
      4. Tool Details
      5. Implementation Notes
    3. Use Cases
      1. Research & Education
      2. Curation & Exhibition
      3. Development
    4. Requirements
      1. For npm/npx installation:
      2. For Python installation:
    5. Testing
      1. Using npm/npx:
      2. Using Python:
    6. Service Management
      1. Linux (systemd)
      2. macOS (launchd)
      3. Windows
    7. Troubleshooting
      1. Common Issues
      2. Getting Help
    8. Documentation
      1. Contributing
        1. License
          1. Acknowledgments

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