Schema | small-mcp

small-mcp

Describes the environment variables required to run the server.

Name	Required	Description	Default
No arguments

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.

Features and capabilities supported by this server

Protocol revision2025-11-25

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

Functions exposed to the LLM to take actions

Name	Description
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.

Interactive templates invoked by user choice

Name	Description
`summarize`	Generate a prompt that asks for a summary of the given text.
`code_review`	Generate a code-review prompt for the supplied code snippet.
`explain_concept`	Generate a prompt that explains a concept to the target audience.

Contextual data attached and managed by the client

Name	Description
`server_info`	Return basic information about this MCP server.
`hello_world_snippet`	A simple Hello World Python snippet.

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Nishant-IIT/smallmp'

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