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Find a street intersection

geocode_intersection
Read-onlyIdempotent

Locate where two named streets cross: "5th Avenue", "Main Street", "Portland".

Instructions

Locate where two named streets cross: "5th Avenue", "Main Street", "Portland".

Resolves the city anchor, loads the street walk graph around its center
(the city's extent, up to 5 km from its center), and finds the junctions
inside it where an edge of one street meets an edge of the other.

Street names match case-insensitively and through the same USPS abbreviation
set as geocode_address (Avenue/Ave, Parkway/Pkwy, West/W, NW/Northwest,
5th/Fifth), plus a directional suffix the caller left off ("Pennsylvania
Avenue" finds "Pennsylvania Avenue NW").

Returns {"results": [{"lat": ..., "lon": ..., "streets": [name_a, name_b]}, ...],
"anchor": {"name": ..., "id": ..., "country": ..., "admin_context": [...]},
"note": ...}. `streets` is the map's own spelling of the two streets at that
crossing, in street_a/street_b order — not an echo of the inputs. When
multiple crossings exist, results are ordered nearest to the city center
first and capped at 5. If one or both streets do not resolve in the city,
returns empty results and a note naming the unresolved street; "truncated":
true means the street graph hit its size cap and may be missing some.

Input Schema

NameRequiredDescriptionDefault
cityYes
street_aYes
street_bYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.11.0

TDQS

A4.2/5.0
Behavior5/5

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

Goes well beyond the annotations (which already cover readOnly/idempotent/openWorld=false) by disclosing the resolution algorithm, the ~5 km city-graph scope, USPS/directional matching rules, nearest-to-center ordering, a 5-result cap, empty-result behavior with an unresolved-street note, and a 'truncated' flag. This is exactly the kind of behavioral context annotations cannot express.

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?

Front-loaded with the one-line purpose plus example, then algorithm, matching rules, and return shape. Dense and largely justified, though the algorithm walkthrough is verbose relative to what an agent needs to call it correctly.

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?

With an output schema already present, return values need not be explained, yet the description still documents ordering, caps, empty/truncated cases, and the streets spelling caveat. Nothing needed to call this correctly or interpret its output is missing.

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

Parameters3/5

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

Schema description coverage is 0%, so the description carries the burden: it explains street-name matching (case-insensitive, USPS abbreviations, optional directional suffix), the city anchor concept, and confirms street_a/street_b ordering. It never explicitly defines each parameter (e.g. what 'city' accepts), leaving the semantics inferable rather than stated.

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?

States a precise verb+resource ('Locate where two named streets cross') with a concrete example, and its intersection-specific scope is immediately distinguishable from single-point siblings like geocode_address, geocode, or reverse_geocode. An agent can tell exactly what this returns without opening 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 Guidelines3/5

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

Usage is implied by the intersection framing (supply two streets plus a city), and geocode_address is mentioned only as a reference for the abbreviation set, not as an alternative to route away from. There is no explicit when-to-use / when-not, no guidance on choosing this over geocode or resolve_place.

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