Skip to main content
Glama
Nishant-IIT

small-mcp

by Nishant-IIT

call_tool

Execute any discovered tool by providing its name and arguments. Enables dynamic tool invocation for automated workflows.

Instructions

Call a tool by name with the given arguments.

Use this to execute tools discovered via search_tools.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesThe name of the tool to call
argumentsNoArguments to pass to the tool
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description must carry the transparency burden. It clearly states the dispatch operation but does not disclose potential side effects of arbitrary tool execution, error behavior for unknown tool names, or argument validation requirements. It does mention discovered tools as a boundary, but lacks safety/behavioral warnings.

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 two sentences long, front-loads the action, and contains no filler. Every phrase contributes to understanding the tool's purpose and usage.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a generic dispatcher with 2 parameters and no output schema, the description plus schema are minimally usable. However, it lacks mention of what happens after execution (e.g., return of the nested tool's result) and does not specify that arguments must conform to the called tool's schema. The search_tools context partially compensates but doesn't fully cover these gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema already covers 100% of the parameters, naming both 'name' and 'arguments' with descriptions. The description adds no parameter details beyond 'given arguments,' so the schema-based baseline of 3 is appropriate. Additional guidance about aligning arguments with the target tool's schema would improve this score.

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?

The description opens with 'Call a tool by name with the given arguments,' which is a specific verb plus resource. It also says 'Use this to execute tools discovered via search_tools,' distinguishing this execution tool from sibling discovery/resource/prompt tools.

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 second sentence explicitly guides the agent to use call_tool after search_tools discovers a tool. It implies the execution role of the tool relative to discovery, though it doesn't explicitly exclude resource/prompt tools or state when not to use it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

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'

If you have feedback or need assistance with the MCP directory API, please join our Discord server