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GeoLens

PYPI · GEOLENS-MCP · SCANNED SEP 20

Read-only access to a self-hosted GeoLens spatial catalog: datasets, features, maps, sandboxed SQL.

Available components

+3 this week 79 Trust /100
Trust breakdown (7 categories)

How this component scores in each security and reliability category. Every signal is checked automatically from public evidence about the published package, including repeated runs of it in an isolated sandbox, and we only credit what we can confirm. How we score → Why this is hard to score →

Supply Chain Security100
  • No malware found by supply-chain analysis.Pass
  • No known CVEs affecting this package version or its production dependencies.Pass
  • Runs hatchling.build at install time, a recognised native-build step with no shell scripting around it. View diagnostics → Pass
  • 1 of 35 dependencies flagged as unhealthy. View diagnostics → Partial
Provenance & Transparency48
  • Source repository is publicly reachable at the declared URL. View diagnostics → Pass
  • Provenance check failed: no build-provenance attestation is published. See how to fix → View diagnostics → Fail
  • Clear OSI-approved license (Apache-2.0).Pass
  • Actively maintained (last published 1 days ago).Pass
  • Publishes a security disclosure policy (SECURITY.md).Pass
Schema Quality & AI Usability63
  • AI-judged instruction clarity (good).Pass
  • Context-footprint check failed: tool/resource definitions use about 1067 tokens (~177/item across 6 items; 6 tools + 0 resources), over budget; trim descriptions and params. See how to fix → Fail
  • Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management93
  • Stability observed for 28 of 30 days with no destabilising changes; credit accrues until the full window elapses.Partial
Tool Coverage67
  • 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
  • 0% of tool parameters carry a description.Fail
Tool Safety100
  • No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
  • We read all 6 captured tool definition(s), and no name or description among them implies an irreversible operation.Pass
  • An AI judge read all 6 captured unit(s) of tool text and found none that tries to manipulate the model reading it.Pass
Capabilities100
  • Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.Pass
Install

How do I install the GeoLens MCP server?

GeoLens runs locally as a PyPI package, launched with uvx geolens-mcp. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.

pypi · geolens-mcp

# add to Claude Code
claude mcp add geolens-io-geolens -- uvx geolens-mcp
// .cursor/mcp.json
{
  "mcpServers": {
    "geolens-io-geolens": {
      "command": "uvx",
      "args": [
        "geolens-mcp"
      ]
    }
  }
}
// .vscode/mcp.json
{
  "servers": {
    "geolens-io-geolens": {
      "command": "uvx",
      "args": [
        "geolens-mcp"
      ]
    }
  }
}
# add to Codex CLI
codex mcp add geolens-io-geolens -- uvx geolens-mcp
// opencode.json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "geolens-io-geolens": {
      "type": "local",
      "command": [
        "uvx",
        "geolens-mcp"
      ],
      "enabled": true
    }
  }
}
# add to OpenClaw
openclaw mcp add geolens-io-geolens --command uvx --arg geolens-mcp
# ~/.hermes/config.yaml
mcp_servers:
  geolens-io-geolens:
    command: "uvx"
    args: ["geolens-mcp"]
// ~/.netclaw/config/netclaw.json
{
  "McpServers": {
    "geolens-io-geolens": {
      "Transport": "stdio",
      "Command": "uvx",
      "Arguments": [
        "geolens-mcp"
      ]
    }
  }
}
# add to Vellum
assistant mcp add geolens-io-geolens -t stdio -c uvx -a geolens-mcp
// mcp.json
{
  "mcpServers": {
    "geolens-io-geolens": {
      "command": "uvx",
      "args": [
        "geolens-mcp"
      ]
    }
  }
}
Changelog

Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.

  • 19 Sept 26 +39
    • Injection markers: unverified → pass security
    • Tool coverage: unverified → 100 functional
    • MCP protocol: unverified → pass functional
    • Stability: unverified → 0.90 functional
  • 18 Sept 26 −38
    • Stability: 0.83 → unverified security
    • Tool safety: pass → unverified security
    • Capabilities: pass → unverified functional
    • Tool coverage: 100 → unverified functional
    • Package version: 1.19.1 → 1.20.0 functional
  • 16 Sept 26 +1

    No change was recorded against any check on this day. Stability & Change Management went from 77 to 80. That category is still filling its 30-day observation window: 23 days of observed history at the previous scan, 24 at this one. The score rises as the window fills, whether or not the server changes.

  • 15 Sept 26 +15
    • Malware scan: unverified → pass security
  • 14 Sept 26 −14
    • Malware scan: pass → unverified security
  • 13 Sept 26 +36
    • Injection markers: unverified → pass security
    • Tool coverage: unverified → 100 functional
    • MCP protocol: unverified → pass functional
    • Stability: unverified → 0.70 functional
  • 12 Sept 26 −35
    • Tool safety: pass → unverified security
    • Stability: 0.63 → unverified security
    • Capabilities: pass → unverified functional
    • Tool coverage: 100 → unverified functional
    • Package version: 1.19.0 → 1.19.1 functional
  • 10 Sept 26 +1
    • Tool safety: pass → unverified security
    • Stability: 0.57 → unverified security
    • Capabilities: pass → unverified functional
    • Tool coverage: 100 → unverified functional
    • Package version: 1.18.1 → 1.19.0 functional
Diagnostics

Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.

Captured 20 Sept 2026 · Analysed pypi/geolens-mcp@1.20.0

Provenance No attestation

The registry publishes no build provenance for this version, so there is nothing to verify.

Result No attestation
Ecosystem pypi

Background: How many MCP packages publish verified provenance →

Install scripts 1 script
Hook Tier Command
build_backend allowlisted hatchling.build

Background: Why install scripts are a supply-chain risk →

Dependencies 35 packages
Packages resolved 35
Stale 1
Tree resolution Complete

Background: SBOMs and build attestations, explained →

MCP tools · 6 exposed · ~1,067 tokens

The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability. A tool's description is untrusted text the model reads on every call, which is what makes this list a security surface and not just an inventory: how tool poisoning works →

Tool Tokens
get_dataset_schema ~217

Get a dataset's schema and source trust metadata. Returns columns (name/type/role), geometry type, CRS/SRID, feature count, spatial extent, and the safe `source_origin`. `source_health` is healthy, missing, inaccessible, or unknown: inaccessible means GeoLens could not determine whether the source still exists, while unknown means it was never probed or cannot be probed. `source_health_detail` is a fixed GeoLens reason code, not provider text. `last_checked_at` records the latest probe attempt; `last_refreshed_at` records only the latest successful committed refresh. `source_freshness` is advisory; overdue means two declared update intervals elapsed without a successful refresh. Raw provider URLs, origin pointers, and credentials are excluded. Call this before writing spatial questions so you know both the available columns and whether the source may be stale. Args: dataset_id: Dataset id (e.g. from search_datasets).

NameTypeReqDescription
dataset_idstringyes

No output schema declared.

No examples provided.

get_features ~129

Get GeoJSON features for a dataset (bounded). Returns an OGC-API FeatureCollection. Raster datasets have no features and will error. Results are capped by `limit`; page with `offset`. Args: dataset_id: Dataset id. limit: Max features (1-200, default 10). offset: Feature offset for paging. bbox: Optional bounding box filter "minx,miny,maxx,maxy" (WGS84).

NameTypeReqDescription
bbox
dataset_idstringyes
limitinteger
offsetinteger

No output schema declared.

No examples provided.

get_map ~54

Get one saved map's full metadata, including its layers, view state, basemap, and terrain configuration. Args: map_id: Map id (e.g. from list_maps).

NameTypeReqDescription
map_idstringyes

No output schema declared.

No examples provided.

list_maps ~80

List saved maps (read-only metadata: id, name, visibility, layer count). Args: search: Optional text filter on map name/description. limit: Max results (1-200, default 50). offset: Result offset for paging.

NameTypeReqDescription
limitinteger
offsetinteger
search

No output schema declared.

No examples provided.

query ~309

Run one read-only SQL SELECT against accessible datasets. Executes through the server's hardened SQL sandbox: a single SELECT over `data.*` tables, an allowlisted function set (aggregates, math, string, date, JSON, common PostGIS like ST_Area/ST_DWithin/ST_Intersects), and a strict server-side budget (a few seconds of runtime, a repetition cap on self-joins, and `row_limit` rows). Returns `{columns, rows, row_count, truncated}` with rows as lists in column order. Requires credentials with AI-chat permission — anonymous configurations cannot use this tool. Workflow: `search_datasets` to find a dataset, then `get_dataset_schema` for its `table_name` and columns, then reference it as `data.<table_name>` in the SQL and list the same `table_name` in `restrict_tables`. Every table the query touches must be listed there; the scope can only narrow what your credentials already see. Writes, other schemas, and unlisted functions are rejected with a short reason. Args: sql: A single SELECT statement over `data.*` tables. restrict_tables: Table names (no `data.` prefix) the query may touch. Required and non-empty. row_limit: Max rows to return (1-1000, default 100).

NameTypeReqDescription
restrict_tablesarrayyes
row_limitinteger
sqlstringyes

No output schema declared.

No examples provided.

search_datasets ~278

Search the GeoLens catalog for datasets by free text. Matches title, description, and keywords (semantic ranking is used automatically when the instance has it enabled). Returns a GeoJSON FeatureCollection where each feature is a dataset record; use the feature `id` as the dataset_id for the other tools. Each feature's properties include `source_origin` (upload, postgis, service, stac, created, or null) and `source_freshness` (fresh, due, overdue, or unknown). Freshness is advisory: `due` means one declared update interval has elapsed, while `overdue` means two have elapsed; neither proves that the content is wrong. Search does not make a detail request per result. When the catalog summary has no health/check/refresh value, `source_health`, `source_health_detail`, `last_checked_at`, and `last_refreshed_at` are null. Call `get_dataset_schema` for populated trust metadata. Raw provider URLs and credentials are never included in these source-state fields. Args: query: Search text. limit: Max results (1-200, default 10). offset: Result offset for paging.

NameTypeReqDescription
limitinteger
offsetinteger
querystringyes

No output schema declared.

No examples provided.

Common questions

What is the GeoLens MCP server?

GeoLens is an MCP server listed in the public MCP registry as io.github.geolens-io/geolens. Read-only access to a self-hosted GeoLens spatial catalog: datasets, features, maps, sandboxed SQL. This page covers its PyPI package (geolens-mcp).

Is the GeoLens MCP server safe to use?

GeoLens scores 79 out of 100 on VerifyMCP. We found no known CVEs affecting it as of 20 September 2026. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.

What tools does the GeoLens MCP server expose?

GeoLens exposes 6 tools: search_datasets, get_dataset_schema, get_features, list_maps, get_map, query. Their descriptions and schemas cost roughly 1,067 tokens of context every time the server is loaded.

Is the GeoLens MCP server still maintained?

GeoLens is still listed as active in the MCP registry. We last reached this channel on 20 September 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.

What licence is the GeoLens MCP server under?

GeoLens declares the Apache-2.0 licence, which is OSI-approved. That covers the source only, and says nothing about the cost of any service it calls.