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Vancam MCP Server

Vancam MCP Server

by shughestr
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

get_nearest_cameras

Find the nearest traffic cameras to any latitude/longitude point. Returns cameras sorted by distance, with optional limit and active-only filters.

Instructions

Get the nearest traffic cameras to a geographic point.

Nearest-neighbor search. Use when the user asks for the closest camera(s) to a location.

Parameters: lat, lon: Query point (WGS84) limit: Number of cameras (1–100, default 5) active_only: If true, only camera_class=open

Returns: JSON with type nearest_search and cameras[] ordered by distance_meters.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "lat": "<lat>",
      "lon": "<lon>"
    },
    "name": "get_nearest_cameras"
  }
}

Input Schema

NameRequiredDescriptionDefault
latYes
lonYes
limitNo
active_onlyNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.6/5.0
Behavior4/5

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

With no annotations, the description carries the full burden. It discloses behavioral traits such as nearest-neighbor search, the active_only filtering (camera_class=open), and the ordering by distance_meters. It does not mention auth or rate limits, but for a read-only query tool these are not critical gaps.

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?

The description is compact and structured with purpose, usage, parameters, and return sections. Every sentence adds value; the front-loaded purpose and bullet-like parameter list make it easy to scan.

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 the tool's simplicity, four parameters, and an output schema, the description covers all necessary context: when to use, what parameters mean, and what the response contains. The sibling tool names clarify the alternative spatial queries, making the tool complete within its context.

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

Parameters5/5

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

All four parameters are explained beyond the schema: lat/lon as query point in WGS84, limit with range 1–100 and default 5, active_only with the meaning of filtering to camera_class=open. Schema coverage is 0%, so this description fully compensates.

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 'Get the nearest traffic cameras to a geographic point,' which clearly states the verb (get), resource (traffic cameras), and scope (nearest to a point). It distinguishes itself from siblings like 'get_cameras_by_radius' and 'get_cameras_along_route' by focusing on nearest-neighbor semantics.

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 explicitly says 'Use when the user asks for the closest camera(s) to a location,' providing a clear when-to-use context. It does not list exclusions or alternative tools, but the context is specific enough to guide selection among sibling tools.

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

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