geolens-mcp
OfficialRelated Servers
Alternatives to geolens-mcp
No user-submitted related servers found.
Related Servers
- FlicenseBqualityBmaintenanceProvides read-only query tools over OpenStreetMap data in PostGIS, enabling natural language queries for features, categories, and spatial analysis.7-
- FlicenseNot gradedqualityFmaintenanceProvides read-only SQL query access to Postgres and DuckDB databases via MCP tools, with extensive security hardening for public endpoints.1-
- FlicenseNot gradedqualityDmaintenanceProvides read-only access to PostgreSQL databases with schema inspection, query execution in multiple formats (JSON, CSV, Markdown), and query history tracking with built-in security features.-
- AlicenseAqualityBmaintenanceEnables read-only PostgreSQL interaction with enforced SQL security policies, including query validation, row limits, and timeouts.4MIT
- AlicenseNot gradedqualityCmaintenanceProvides access to City of Salem GIS open geospatial data (ArcGIS), enabling search, query, and schema retrieval of datasets such as parcels, zoning, and public works.3 npmMIT
- FlicenseNot gradedqualityBmaintenanceProvides read-only SQL query access to PostgreSQL mirrors of Vizru spreadsheets on Neon, exposing REST endpoints and MCP tools for relational filtering and schema discovery.-
TDQS
Scored across 6 tools
Each tool has a clear, distinct target: dataset discovery, schema/trust metadata, feature retrieval, SQL querying, and map metadata. There is potential overlap between get_features and query for reading data, but the descriptions frame them as different access modes (GeoJSON features vs. read-only SQL) so an agent can choose intentionally.
Most tools follow a consistent verb_noun pattern (search_datasets, get_features, get_dataset_schema, list_maps, get_map). The bare `query` tool is the only deviation, but it is a recognizable verb and does not clash with the others.
Six tools is well-scoped for a geospatial catalog and map metadata server: three for dataset introspection/access, two for saved maps, and one for SQL. Each tool fills a distinct role without redundancy or sprawl.
The read-only dataset workflow is well covered: discover, inspect schema, fetch features, or run SQL. Minor gaps exist, such as no explicit list-all-datasets or per-feature lookup endpoint, but agents can work around them with search and query.