TypeScript MCP Server Boilerplate
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
Server capabilities have not been inspected yet.
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| greetingB | Greet a user in their specified language |
| calculatorC | Perform basic arithmetic operations |
| image_generationC | Generate an image from a text prompt using AI |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
| code_review | Generate a detailed code review prompt for the provided code |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
| server-info | Current MCP server information |
TDQS
Scored across 3 tools
Each tool has a clearly distinct and non-overlapping purpose: calculator for arithmetic, greeting for language-based salutations, and image_generation for AI-based visual creation. There is no ambiguity in tool selection as they target completely different domains and use cases.
The naming is mixed with 'calculator' and 'greeting' as nouns and 'image_generation' as a verb_noun pattern, lacking a uniform convention. However, all names are readable and descriptive, avoiding chaotic styles like camelCase or abbreviations.
With only 3 tools, the set feels thin and under-scoped for a 'TypeScript MCP Server Boilerplate,' which typically implies a broader utility or domain coverage. The tools are disparate and do not form a coherent surface for any specific purpose, making the count too low for effective agent workflows.
The tool set is severely incomplete for a boilerplate server, lacking core operations like CRUD, configuration, or domain-specific functions. There are significant gaps as the tools are unrelated and do not cover a coherent domain, leading to potential agent failures in structured tasks.