Skip to main content
Glama

Geocode names in batch

geocode_batch
Read-onlyIdempotent

Geocode up to 20 free-text queries at once, returning the top match with coordinates for each, while keeping results in input order. Unmatched queries return errors without stopping the batch.

Instructions

Geocode up to 20 free-text queries in one call, one best match each.

Cuts N round-trips of geocode() into one and, more importantly,
shares ONE local divisions name table across the batch (#329) so a
two-name walk is not N cold S3 scans. For each query, keeps only
the top candidate.
Returns {"results": [{"query", "name", "type", "lat", "lon", "id"
(GERS), "rank_score"}, ...]}, one row per query, in input order — a
query with no match gets the standard error envelope {"query",
"error": "not_found", "detail"} instead, and does not fail the rest of
the batch. queries is capped at 20; a longer list returns a structured
{"error": ...} rather than truncating silently. Budgeted like every
other tool. Returns a structured {"error": ...} instead of raising if
the remote scan itself fails.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queriesYes
limit_per_queryNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Install Server

TDQS

A3.7/5.0
Behavior3/5

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

The description adds substantial behavioral context beyond the readOnly/idempotent annotations: per-query error envelopes, batch cap at 20, structured errors instead of raising, and non-failing of the rest of the batch. However, it states 'keeps only the top candidate' while the input schema includes limit_per_query with a default of 3, and that parameter's behavior is never explained, creating an incomplete and potentially misleading behavioral model.

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

Conciseness4/5

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

The description is long but organized and mostly information-dense: purpose, motivation, output format, then failure behavior. The implementation-specific notes like '#329' and 'cold S3 scans' add useful rationale, though 'Budgeted like every other tool' is vague and earns little weight. Overall it stays front-loaded and readable.

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

Completeness3/5

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

The description is quite complete for a read-only batch operation: it covers input cap, output shape, per-query error isolation, and remote failure behavior. The major gap is the undocumented limit_per_query parameter, which affects actual behavior and is central to calling the tool correctly.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must carry the full semantic burden for parameters. It does explain that queries are free-text and capped at 20, but it never mentions limit_per_query, its default, or the effect it has on the returned candidates. With a parameter silently left unexplained, agents cannot correctly tune or even predict the tool's output.

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 opens with a specific verb and resource: 'Geocode up to 20 free-text queries in one call, one best match each.' It explicitly contrasts with geocode() by framing itself as the batched replacement, so an agent can tell it apart from both geocode and the other sibling tools without inspecting the schema.

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

Usage Guidelines4/5

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

The description clearly motivates when to use this tool: when you have N free-text names to geocode, it cuts N round-trips to one and avoids repeated cold S3 scans. It does not explicitly say 'use geocode for a single query' or list exclusion cases, but the batching rationale makes the intended usage clear enough.

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

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/chuofringer/placeroot'

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