GBP Peak vs Gis MCP

A side-by-side look at the GBP Peak and Gis MCP MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.

GBP Peak logoGBP PeakLocation Services · Local subprocess (stdio)Google Maps geo-grid rank scanning for local SEO. Run scans, read rank maps and competitor stats, check rank at any place, research local keywords. Tools: list_analyses, find_keywords, list_scans, suggest_keywords, keyword_graph_url, get_rank_map, rank_at_point, trigger_scan. Bridges to the hosted GBP Peak MCP endpoint with a bearer API token.78GreatAuth: not declaredGis MCP logoGis MCPLocation Services · Local subprocess (stdio)A Model Context Protocol (MCP) server implementation that connects Large Language Models (LLMs) to GIS operations using GIS libraries, enabling AI assistants to perform accurate geospatial operations and transformations.63GoodAuth: not declared

Verdict: choose GBP Peak 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?

GBP Peak logoChoose GBP Peak when

  • You need dedicated capabilities in the Location Services domain.
  • You prefer a local stdio subprocess transport.
  • You have the keys it needs: GBPPEAK_TOKEN.
  • You want tools like list_analyses, find_keywords, list_scans.
Explore GBP Peak

Gis MCP logoChoose 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.
Explore Gis MCP

Feature & specification comparison

Rows where the two servers differ are marked.

SpecGBP Peak logoGBP PeakGis MCP logoGis MCP
CategoryLocation ServicesLocation Services
Quality signal78/100 · Great63/100 · Good
Install commandConfirmedConfirmed
TransportLocal subprocess (stdio)Local subprocess (stdio)
AuthNot declaredNot declared
PricingNot declaredNot declared
Required env varsGBPPEAK_TOKENNone listed
Verified owner VerifiedCommunity listing
GitHub stars0198
Directory activity 4 views 0 installs 0 upvotes 1 views 0 installs 0 upvotes
Tools887

Tools & capabilities

GBP Peak tools 8

  • list_analysesYour GBP Peak keyword analyses (businesses)
  • find_keywordsLocal keyword research — measured demand × competition × intent scoring
  • list_scansGeo-grid rank scans for one keyword or location
  • suggest_keywordsGenerate new keyword candidates from a seed + research prompt
  • keyword_graph_urlInteractive keyword relationship graph for an analysis
  • get_rank_mapFull geo-grid rank map: stats, competitors, PNG map image
  • rank_at_point"What's my rank at <place>?" — geocodes a place and reads the nearest grid point
  • trigger_scanRun a new geo-grid scan (costs scan points, `confirm: true` required)

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.

GBP Peak

mcpServers (Claude Desktop / Cursor)
{
  "mcpServers": {
    "gbp-peak": {
      "command": "npx",
      "args": [
        "-y",
        "gbppeak-mcp"
      ],
      "env": {
        "GBPPEAK_TOKEN": "YOUR_GBPPEAK_TOKEN_HERE"
      }
    }
  }
}

Gis MCP

mcpServers (Claude Desktop / Cursor)
{
  "mcpServers": {
    "mahdin75-gis-mcp": {
      "command": "uvx",
      "args": [
        "gis-mcp"
      ]
    }
  }
}

Frequently asked questions

GBP Peak is categorized under Location Services and uses a local stdio subprocess. Gis MCP belongs to Location Services and uses a local stdio subprocess. Pick GBP Peak 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.

GBP Peak 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 gbp-peak and mahdin75-gis-mcp as separate keys in the same mcpServers object, and your assistant will call tools from either one.

On AllMCPs, GBP Peak has a quality signal of 78/100 (Great) with 4 views, 0 installs and 0 GitHub stars. Gis MCP has 63/100 (Good) with 1 views, 0 installs and 198 GitHub stars.