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MCP Inspector as MCP Server

by esinecan

insp_prompts_get

Retrieve specific prompts from MCP servers by name to test and inspect server functionality across different transport protocols.

Instructions

Get a specific prompt from an MCP server.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
commandNoCommand to run the MCP server (e.g., 'node', 'python')
argsNoArguments to pass to the command (e.g., ['build/index.js'])
urlNoURL for SSE/HTTP transport (alternative to command)
transportNoTransport type (auto-detected if not specified)
headersNoHTTP headers for SSE/HTTP transport
prompt_nameYesName of the prompt to get
prompt_argsNoArguments to pass to the prompt
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure but offers minimal information. It states the tool retrieves a prompt but doesn't describe what happens if the prompt doesn't exist, whether authentication is required, if there are rate limits, what format the prompt returns in, or whether this is a read-only operation. The description is too basic for a tool with 7 parameters and server interaction.

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 a single, clear sentence that gets straight to the point with zero wasted words. It's appropriately sized for a retrieval operation and front-loads the essential information. Every word earns its place in communicating the core functionality.

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

Completeness2/5

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

For a tool with 7 parameters, server communication, and no output schema, the description is insufficiently complete. It doesn't explain what constitutes a 'prompt' in this system, what the return format looks like, error handling, or authentication requirements. The combination of complex parameters and no annotations means the description should provide more contextual information about the operation.

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?

Schema description coverage is 100%, so the schema already documents all 7 parameters thoroughly. The description adds no additional parameter information beyond what's in the schema - it doesn't explain relationships between parameters (like command/args vs url/transport), provide examples of prompt_name formats, or clarify when prompt_args are needed. This meets the baseline for high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Get') and resource ('a specific prompt from an MCP server'), making the purpose immediately understandable. It distinguishes from sibling tools like 'insp_prompts_list' by specifying retrieval of a single prompt rather than listing multiple. However, it doesn't explicitly mention what 'prompt' refers to in this context (e.g., AI prompt templates, system prompts).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention when to choose this over 'insp_prompts_list' (for listing all prompts) or 'insp_tools_call' (which might handle different operations). There's no discussion of prerequisites, error conditions, or typical use cases for prompt retrieval.

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

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