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Vancam MCP Server

Vancam MCP Server

by shughestr
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

get_cameras_by_radius

Find traffic cameras within a specified radius of any latitude/longitude point. Search by coordinates and distance to get nearby live camera feeds.

Instructions

Get traffic cameras within a radius (km) of a lat/lon point.

Radius search. Use when the user asks for cameras near a place, within X km of coordinates, or around an address they geocoded.

Parameters: lat, lon: Center point (WGS84) radius: Search radius in kilometers (default 1.0, max 50 per API) limit: Max cameras (1–100, default 50) active_only: If true, only camera_class=open

Returns: JSON with type radius_search, count, radius_km, cameras[].

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_cameras_by_radius"
  }
}

Input Schema

NameRequiredDescriptionDefault
latYes
lonYes
limitNo
radiusNo
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 transparency burden. It discloses important behavior such as the maximum radius ('max 50 per API'), the meaning of active_only ('only camera_class=open'), and the JSON return structure ('type radius_search, count, radius_km, cameras[]'). This goes beyond the schema and gives the agent actionable expectations, though it stops short of covering error cases or sorting details.

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 efficiently structured: a one-sentence summary, a usage line, a parameter list, and a return format. No fluff or redundancy; every section serves a purpose and information is front-loaded.

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 moderate complexity (5 params, output schema present), the description provides complete operational context: purpose, when to use, parameter semantics, and return shape. The output schema covers detailed field structure, so the description need not repeat it, but it still gives a high-level return summary. It is fully adequate for an agent to select and invoke correctly.

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?

Schema description coverage is 0%, so the description must provide parameter meaning. It does so thoroughly: lat/lon identified as center point with WGS84, radius with units/default/max, limit with range/default, and active_only with a clear filter explanation. This fully compensates for the schema's lack of descriptions.

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?

Description opens with 'Get traffic cameras within a radius (km) of a lat/lon point,' which clearly states the action, resource, and scope. It distinguishes from sibling tools by focusing on radius-based search, setting it apart from list_cameras or get_nearest_cameras.

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 states when to use the tool: 'Use when the user asks for cameras near a place, within X km of coordinates, or around an address they geocoded.' This provides clear trigger contexts, though it does not explicitly mention alternatives or exclusions.

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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