mcp-town-explorer
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": false
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| get_housingB | Median home price for one town, in USD. |
| get_distanceC | Straight-line distance from one town to Boston, in miles. |
| get_schoolsB | School rating for one town (GreatSchools district rating, 1-10). |
| get_safetyB | Crime figures for one town: violent crime rate as incidents per 1,000 residents. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 4 tools
Each tool targets a distinct domain dimension: housing, transportation, education, and public safety. There is no overlap between the four tools, and their purposes are clearly separable by the resource type they query.
All tools follow a consistent get_[noun] pattern (get_housing, get_distance, get_schools, get_safety). The only minor deviation is that 'distance' refers to a relationship (distance to Boston) while the others refer to town attributes, but the naming is otherwise uniform and predictable.
Four tools is a borderline-low count. For a town explorer covering four quality-of-life dimensions (housing, commute, schools, safety), it's coherent but thin—a full explorer might also include taxes, weather, demographics, or amenities.
The four tools cover major town-comparison dimensions (housing, distance, schools, crime), but several obvious gaps exist: no property-tax data, no median income, no demographics or unemployment figures. An agent comparing towns would likely need more than these four metrics for a thorough assessment.