STAC MCP Server

An MCP (Model Context Protocol) Server that provides access to STAC (SpatioTemporal Asset Catalog) APIs for geospatial data discovery and access.

Overview

This MCP server enables AI assistants and applications to interact with STAC catalogs to:

• Search and browse STAC collections
• Find geospatial datasets (satellite imagery, weather data, etc.)
• Access metadata and asset information
• Perform spatial and temporal queries

Features

Available Tools

• search_collections: List and search available STAC collections
• get_collection: Get detailed information about a specific collection
• search_items: Search for STAC items with spatial, temporal, and attribute filters
• get_item: Get detailed information about a specific STAC item

Supported STAC Catalogs

By default, the server connects to Microsoft Planetary Computer STAC API, but it can be configured to work with any STAC-compliant catalog.

Installation

PyPI Package

pip install stac-mcp

Development Installation

git clone https://github.com/BnJam/stac-mcp.git
cd stac-mcp
pip install -e .

Container

The STAC MCP server is available as a secure distroless container image with semantic versioning:

# Pull the latest stable version
docker pull ghcr.io/bnjam/stac-mcp:latest

# Pull a specific version (recommended for production)
docker pull ghcr.io/bnjam/stac-mcp:0.1.0

# Run the container (uses stdio transport for MCP)
docker run --rm -i ghcr.io/bnjam/stac-mcp:latest

Container images are tagged with semantic versions:

• ghcr.io/bnjam/stac-mcp:1.2.3 (exact version)
• ghcr.io/bnjam/stac-mcp:1.2 (major.minor)
• ghcr.io/bnjam/stac-mcp:1 (major)
• ghcr.io/bnjam/stac-mcp:latest (latest stable)

Building the Container

To build the container locally using the provided Containerfile:

# Build with Docker
docker build -f Containerfile -t stac-mcp .

# Or build with Podman  
podman build -f Containerfile -t stac-mcp .

The container uses a multi-stage build with:

• Builder stage: Python 3.12 slim image for building dependencies
• Runtime stage: Distroless Python image for security and minimal size
• Security: Runs as non-root user, minimal attack surface
• Transport: Uses stdio for MCP protocol communication

Usage

As an MCP Server

Native Installation

Configure your MCP client to connect to this server:

{
  "mcpServers": {
    "stac": {
      "command": "stac-mcp"
    }
  }
}

Container Usage

To use the containerized version with an MCP client:

{
  "mcpServers": {
    "stac": {
      "command": "docker",
      "args": ["run", "--rm", "-i", "ghcr.io/bnjam/stac-mcp:latest"]
    }
  }
}

Or with Podman:

{
  "mcpServers": {
    "stac": {
      "command": "podman", 
      "args": ["run", "--rm", "-i", "ghcr.io/bnjam/stac-mcp:latest"]
    }
  }
}

Command Line

Native Installation

stac-mcp

Container Usage

# With Docker
docker run --rm -i ghcr.io/bnjam/stac-mcp:latest

# With Podman
podman run --rm -i ghcr.io/bnjam/stac-mcp:latest

Examples

Search Collections

# Find all available collections
search_collections(limit=20)

# Search collections from a different catalog
search_collections(catalog_url="https://earth-search.aws.element84.com/v1", limit=10)

Search Items

# Search for Landsat data over San Francisco
search_items(
    collections=["landsat-c2l2-sr"],
    bbox=[-122.5, 37.7, -122.3, 37.8],
    datetime="2023-01-01/2023-12-31",
    limit=10
)

# Search with additional query parameters
search_items(
    collections=["sentinel-2-l2a"],
    bbox=[-74.1, 40.6, -73.9, 40.8],  # New York area
    query={"eo:cloud_cover": {"lt": 10}},
    limit=5
)

Get Collection Details

# Get information about a specific collection
get_collection("landsat-c2l2-sr")

Get Item Details

# Get detailed information about a specific item
get_item("landsat-c2l2-sr", "LC08_L2SR_044034_20230815_02_T1")

Development

Setup

git clone https://github.com/BnJam/stac-mcp.git
cd stac-mcp
pip install -e ".[dev]"

Testing

pytest

Linting

black stac_mcp/
ruff check stac_mcp/

Version Management

The project uses semantic versioning (SemVer) with automated version management based on branch naming:

Branch-Based Automatic Versioning

When PRs are merged to main, versions are automatically incremented based on branch prefixes:

• hotfix/ branches → patch increment (0.1.0 → 0.1.1) for bug fixes
• feature/ branches → minor increment (0.1.0 → 0.2.0) for new features
• release/ branches → major increment (0.1.0 → 1.0.0) for breaking changes

Manual Version Management

You can also manually manage versions using the version script:

# Show current version
python scripts/version.py current

# Increment version based on change type
python scripts/version.py patch    # Bug fixes (0.1.0 -> 0.1.1)
python scripts/version.py minor    # New features (0.1.0 -> 0.2.0)  
python scripts/version.py major    # Breaking changes (0.1.0 -> 1.0.0)

# Set specific version
python scripts/version.py set 1.2.3

The version system maintains consistency across:

• pyproject.toml (project version)
• stac_mcp/__init__.py (version)
• stac_mcp/server.py (server_version in MCP initialization)

Container Development

To develop with containers:

# Build development image
docker build -f Containerfile -t stac-mcp:dev .

# Test the container
docker run --rm -i stac-mcp:dev

# Using docker-compose for development
docker-compose up --build

# For debugging, use an interactive shell (requires modifying Containerfile)
# docker run --rm -it --entrypoint=/bin/sh stac-mcp:dev

The Containerfile uses a secure multi-stage build approach:

• Distroless base: Minimal attack surface with no shell or package manager
• Non-root user: Container runs as unprivileged user
• Minimal dependencies: Only runtime dependencies included in final image
• Build optimization: Dependencies built in separate stage and copied over
• Production ready: Includes resource limits and security best practices

STAC Resources

• STAC Specification
• pystac-client Documentation
• Microsoft Planetary Computer
• AWS Earth Search

License

Apache 2.0 - see LICENSE file for details.