Skip to main content
Glama

geocode_batch_csv

Bulk-geocode addresses from a CSV file and add the results as a point layer, preserving original columns and match status.

Instructions

Bulk-geocode a CSV file of addresses and add the results as a point layer.

geocoder is "gugik" (default - GUGiK UUG, free with no documented rate limit, capped at 500 rows) or "nominatim" (capped at 50 rows, with a forced ~1.1s delay between requests - Nominatim's usage policy explicitly discourages bulk geocoding, so prefer "gugik" for anything but small batches). address_column names the CSV column holding the full address string. Every original CSV column is kept as a feature attribute on the resulting layer, plus match_status ("ok"/"not_found"). Only a count summary and a small sample are returned here, never the full geocoded table - inspect the layer with get_layer_sample.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYes
geocoderNogugik
max_rowsNo
layer_nameNo
address_columnNoaddress

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided. Description discloses creation of a point layer, retention of CSV columns, addition of match_status, return of only summary/sample, and geocoder-specific behaviors (rate limits, caps). Lacks explicit statement on non-destructiveness, but otherwise thorough.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Well-structured, front-loaded with main purpose, followed by parameter details and output notes. Every sentence adds value, no fluff. Length is appropriate for the complexity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 5 parameters, 0% schema coverage, and no annotations, the description provides nearly all necessary context: purpose, geocoder options, output format, and link to related tool. Output schema exists (though not shown) so return values are covered.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%. Description explains geocoder options and address_column in detail, and implicitly covers path. However, max_rows and layer_name are not explicitly described, though caps are mentioned under geocoders. Good compensation but not exhaustive.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool bulk-geocodes a CSV file and adds results as a point layer. It uses specific verbs and resources ('geocode', 'CSV file', 'point layer') and is distinct from sibling geocoding tools like geocode_reverse and geocode_nominatim.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly compares geocoder options (gugik vs nominatim) with recommendations, mentions row caps and rate limits, and advises to use get_layer_sample for the full table, providing clear when-to-use and when-not-to-use guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/piatkowski/qgis-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server