Geocoding vs Gis MCP
A side-by-side look at the Geocoding and Gis MCP MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.
Verdict: choose Geocoding for location services work as a local process; choose Gis MCP for location services as a local process. You can also run both side by side in one mcpServers block.
Which MCP server should you choose?
Choose Geocoding when
- You need dedicated capabilities in the Location Services domain.
- You prefer a local stdio subprocess transport.
- You want tools like
geocode, reverse_geocode, search_places.
Choose Gis MCP when
- You need dedicated capabilities in the Location Services domain.
- You prefer a local stdio subprocess transport.
- You want tools like
read_file_gpd, append_gpd, merge_gpd.
Feature & specification comparison
Rows where the two servers differ are marked.
| Spec | ||
|---|---|---|
| Category | Location Services | Location Services |
| Quality signal | 59/100 · Good | 63/100 · Good |
| Install command | Confirmed | Confirmed |
| Transport | Local subprocess (stdio) | Local subprocess (stdio) |
| Auth | Not declared | Not declared |
| Pricing | Not declared | Not declared |
| Required env vars | None listed | None listed |
| Verified owner | Community listing | Community listing |
| GitHub stars | 1 | 198 |
| Directory activity | 4 views 0 installs 0 upvotes | 1 views 0 installs 0 upvotes |
| Tools | 4 | 87 |
| Full listing | View Geocoding | View Gis MCP |
Tools & capabilities
Geocoding tools 4
geocodeConvert an address, place name, or landmark into geographic coordinates. Use this tool when: - The user gives a place/address and you need its latitude/longitude - You need to disambiguate a place name (returns ranked matches) - You need a place's coordinates before another geo operation Args: query: Address, place name, or landmark. limit: Max results. country_codes: Optional ISO country filter. response_format: 'markdown' or 'json'. Returns: str: Ranked matches with coordinates, type, and full display name. Example: Input: {"query": "Eiffel Tower"} Output: 48.8584, 2.2945 — Tour Eiffel, Paris, Francereverse_geocodeConvert geographic coordinates into a human-readable address. Use this tool when: - The user gives latitude/longitude and wants to know what's there - You have coordinates (e.g. from geocode) and need the address Args: latitude: Latitude (-90 to 90). longitude: Longitude (-180 to 180). response_format: 'markdown' or 'json'. Returns: str: The address/place at those coordinates, with structured components. Example: Input: {"latitude": 48.8584, "longitude": 2.2945} Output: Avenue Anatole France, Paris, Francesearch_placesSearch for places or points of interest by description, with coordinates. Like geocode, but oriented toward finding multiple matching places/POIs (shops, landmarks, amenities) rather than resolving one address. Use this tool when: - The user wants places of a kind in an area ("parks in Austin") - The user wants options, not a single precise address Args: query: What to find, optionally including a location. limit: Max places. country_codes: Optional ISO country filter. response_format: 'markdown' or 'json'. Returns: str: Matching places with coordinates and type. Example: Input: {"query": "bookstores in Paris", "limit": 5} Output: Up to 5 bookstores with names and coordinatesdistance_betweenCompute the straight-line (great-circle) distance between two places. Geocodes both endpoints, then computes the as-the-crow-flies distance. (This is not driving/route distance.) Use this tool when: - The user asks how far apart two places are - You need a quick distance between two named locations Args: origin: Start place or address. destination: End place or address. unit: 'km' or 'miles'. response_format: 'markdown' or 'json'. Returns: str: The distance, plus the resolved coordinates of each endpoint. Example: Input: {"origin": "Paris", "destination": "Berlin"} Output: ~878 km between Paris and Berlin
Gis MCP tools 87
read_file_gpdReads a geospatial file and returns stats and a data preview.append_gpdReads two shapefiles directly, concatenates them vertically.merge_gpdMerges two shapefiles based on common attribute columns, This function performs a database-style join, not a spatial join. Args: left_shapefile_path: Path to the left shapefile. The geometry from this file is preserved. right_shapefile_path: Path to the right shapefile to merge. output_path: Path to save the merged output shapefile. how: Type of merge. One of 'left', 'right', 'outer', 'inner'. Defaults to 'inner'. on: Column name to join on. Must be found in both shapefiles. left_on: Column name to join on in the left shapefile. right_on: Column name to join on in the right shapefile. suffixes: Suffix to apply to overlapping column names.overlay_gpdOverlay two GeoDataFrames using geopandas.overlay. Args: gdf1_path: Path to the first geospatial file. gdf2_path: Path to the second geospatial file. how: Overlay method ('intersection', 'union', 'identity', 'symmetric_difference', 'difference'). output_path: Optional path to save the result. Returns: Dictionary with status, message, and output info.dissolve_gpdDissolve geometries by attribute using geopandas.dissolve. Args: gdf_path: Path to the geospatial file. by: Column to dissolve by (optional). output_path: Optional path to save the result. Returns: Dictionary with status, message, and output info.explode_gpdSplit multi-part geometries into single parts using geopandas.explode. Args: gdf_path: Path to the geospatial file. output_path: Optional path to save the result. Returns: Dictionary with status, message, and output info.clip_vectorClip vector geometries using geopandas.clip. Args: gdf_path: Path to the input geospatial file. clip_path: Path to the clipping geometry file. output_path: Optional path to save the result. Returns: Dictionary with status, message, and output info.sjoin_gpdSpatial join between two GeoDataFrames using geopandas.sjoin. Args: left_path: Path to the left geospatial file. right_path: Path to the right geospatial file. how: Type of join ('left', 'right', 'inner'). predicate: Spatial predicate ('intersects', 'within', 'contains', etc.). output_path: Optional path to save the result. Returns: Dictionary with status, message, and output info.sjoin_nearest_gpdNearest neighbor spatial join using geopandas.sjoin_nearest. Args: left_path: Path to the left geospatial file. right_path: Path to the right geospatial file. how: Type of join ('left', 'right'). max_distance: Optional maximum search distance. output_path: Optional path to save the result. Returns: Dictionary with status, message, and output info.point_in_polygonCheck if points are inside polygons using spatial join (predicate='within'). Args: points_path: Path to the point geospatial file. polygons_path: Path to the polygon geospatial file. output_path: Optional path to save the result. Returns: Dictionary with status, message, and output info.write_file_gpdExport a GeoDataFrame to a file (Shapefile, GeoJSON, GPKG, etc.). Args: gdf_path: Path to the input geospatial file. output_path: Path to save the exported file. driver: Optional OGR driver name (e.g., 'ESRI Shapefile', 'GeoJSON', 'GPKG'). Returns: Dictionary with status and message.bufferCreate a buffer around a geometry.- +75 more on the listing page
Ready-to-paste client configs
Paste either block (or both) into your client config, e.g. claude_desktop_config.json or ~/.cursor/mcp.json. We only show a config when the install command is confirmed.
Geocoding
{
"mcpServers": {
"geocoding": {
"command": "npx",
"args": [
"-y",
"geocode-mcp"
]
}
}
}
Gis MCP
{
"mcpServers": {
"mahdin75-gis-mcp": {
"command": "uvx",
"args": [
"gis-mcp"
]
}
}
}
Frequently asked questions
Geocoding is categorized under Location Services and uses a local stdio subprocess. Gis MCP belongs to Location Services and uses a local stdio subprocess. Pick Geocoding for location services work and Gis MCP for location services.
Copy the mcpServers block from the config section on this page into your client's config (for example claude_desktop_config.json or ~/.cursor/mcp.json), then fully restart the client.
Geocoding has no declared pricing — check the project's own site. Gis MCP has no declared pricing — check the project's own site. If a server needs environment variables such as API keys, define them under the env key in your client's MCP config.
Yes. MCP clients support multiple servers: add geocoding and mahdin75-gis-mcp as separate keys in the same mcpServers object, and your assistant will call tools from either one.
On AllMCPs, Geocoding has a quality signal of 59/100 (Good) with 4 views, 0 installs and 1 GitHub stars. Gis MCP has 63/100 (Good) with 1 views, 0 installs and 198 GitHub stars.