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Glama
Nishant-IIT

small-mcp

by Nishant-IIT

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault

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

CapabilityDetails
tools
{
  "listChanged": true
}
logging
{}
prompts
{
  "listChanged": false
}
resources
{
  "subscribe": false,
  "listChanged": false
}
extensions
{
  "io.modelcontextprotocol/ui": {}
}
experimental
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
search_toolsA

Search for tools using natural language.

Returns matching tool definitions ranked by relevance, in the same format as list_tools.

call_toolA

Call a tool by name with the given arguments.

Use this to execute tools discovered via search_tools.

list_resourcesA

List all available resources and resource templates.

Returns JSON with resource metadata. Static resources have a 'uri' field, while templates have a 'uri_template' field with placeholders like {name}.

read_resourceA

Read a resource by its URI.

For static resources, provide the exact URI. For templated resources, provide the URI with template parameters filled in.

Returns the resource content as a string. Binary content is base64-encoded.

list_promptsA

List all available prompts.

Returns JSON with prompt metadata including name, description, and optional arguments.

get_promptA

Get a prompt by name with optional arguments.

Returns the rendered prompt as JSON with a messages array. Arguments should be provided as a dict mapping argument names to values.

Prompts

Interactive templates invoked by user choice

NameDescription
summarizeGenerate a prompt that asks for a summary of the given text.
code_reviewGenerate a code-review prompt for the supplied code snippet.
explain_conceptGenerate a prompt that explains a concept to the target audience.

Resources

Contextual data attached and managed by the client

NameDescription
server_infoReturn basic information about this MCP server.
hello_world_snippetA simple Hello World Python snippet.

TDQS

A4.2/5.0

Scored across 6 tools

Disambiguation5/5

Each tool has a clear, distinct role: search vs call, list vs read, list vs get. There is no overlap in purpose.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern (search_tools, call_tool, list_resources, read_resource, list_prompts, get_prompt).

Tool Count5/5

With 6 tools covering three resource types (tools, resources, prompts), the count is well-scoped and appropriate for a small MCP utility server.

Completeness3/5

The server covers tools, resources, and prompts, but misses a list_tools tool, which is a notable gap since search_tools cannot enumerate all tools. This could cause agent failures when trying to discover the full tool surface.

Maintenance

ActivityInactive
ResponsivenessNo issues