get_mcp_server
Retrieve the configuration of a specific MCP server by providing its name.
Instructions
Get the configuration of a specific MCP server by name.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| server_name | Yes | MCP server name |
Retrieve the configuration of a specific MCP server by providing its name.
Get the configuration of a specific MCP server by name.
| Name | Required | Description | Default |
|---|---|---|---|
| server_name | Yes | MCP server name |
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 only states 'Get the configuration' (a read operation) but does not mention authorization requirements, error handling (e.g., what if the server does not exist), performance characteristics, or any side effects. This is insufficient for a tool with no annotation support.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is short and front-loaded with the key action and resource. Every word serves a purpose; there is no redundancy or unnecessary elaboration. This is an exemplary concise description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given there is no output schema, the description should hint at what constitutes the 'configuration' (e.g., fields returned). It only says 'configuration' without elaboration. Additionally, error cases or prerequisites are not mentioned. While the tool is simple, the description could provide a bit more context, such as typical usage context, but it is not severely lacking.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% with the parameter 'server_name' described as 'MCP server name'. The description adds 'by name' reinforcing the parameter's role. However, since the schema already conveys the same information clearly, the description adds minimal additional meaning beyond confirming the parameter's purpose. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and the resource 'configuration of a specific MCP server', using the parameter 'by name' to identify the server. This distinguishes it from sibling tools like list_mcp_servers (list all) and create_mcp_server (create new), making the purpose highly clear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not provide any guidance on when to use this tool versus alternatives. It lacks explicit 'when to use' or 'when not to use' instructions, nor does it reference sibling tools. Without such context, an agent may struggle to choose the correct tool among similar options.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/nobrainer-tech/langflow-mcp'
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