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daedalus

mcp-registry

by daedalus

get_mcp_server

Retrieve detailed configuration and version information for a specific MCP server from the registry to enable integration and usage.

Instructions

Get detailed information about a specific MCP server by name.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesThe name of the server to retrieve.
registry_urlNoBase URL of the MCP Registry API (default: production).https://registry.modelcontextprotocol.io

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves 'detailed information,' but doesn't specify what that includes (e.g., metadata, configurations, status), whether it's a read-only operation, potential errors (e.g., if the server doesn't exist), or any rate limits. For a tool with no annotation coverage, this leaves significant gaps in understanding its behavior.

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, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded with the core action and resource, making it easy to parse quickly. Every part of the sentence earns its place by conveying essential information.

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?

Given the tool's moderate complexity (2 parameters, 1 required), 100% schema coverage, and the presence of an output schema, the description is minimally adequate. It covers the basic purpose but lacks behavioral details and usage guidance. With an output schema handling return values, the description doesn't need to explain outputs, but it should provide more context on when and how to use the tool effectively.

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 has 100% description coverage, with clear documentation for both parameters ('name' and 'registry_url'). The description adds no additional parameter semantics beyond what's in the schema, such as format examples or constraints. Given the high schema coverage, a baseline score of 3 is appropriate, as the schema already provides adequate parameter information.

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 tool's purpose: 'Get detailed information about a specific MCP server by name.' It specifies the verb ('Get'), resource ('MCP server'), and key constraint ('by name'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'get_server_versions' or 'list_mcp_servers', which prevents a perfect score.

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 sibling tools like 'list_mcp_servers' (for listing servers) or 'get_server_versions' (for version details), nor does it specify prerequisites or exclusions. This lack of contextual guidance makes it harder for an agent to choose correctly among available options.

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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