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kongyo2

Glama MCP Server Search

get_mcp_server_details

Read-only

Retrieve detailed information about a specific MCP server by providing its namespace and slug, enabling efficient server exploration and selection using the Glama MCP API.

Instructions

Get detailed information about a specific MCP server by namespace and slug

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
namespaceYesThe namespace/organization of the MCP server (e.g., 'microsoft', 'openai')
slugYesThe slug/name of the MCP server (e.g., 'playwright-mcp', 'gpt-mcp')

Implementation Reference

  • The execute handler function that fetches detailed information about the MCP server from the Glama API using namespace and slug.
    execute: async (args) => {
      try {
        const result = await makeGlamaRequest(
          `/v1/servers/${args.namespace}/${args.slug}`,
        );
        return JSON.stringify(result, null, 2);
      } catch (error) {
        return `Error getting MCP server details: ${error instanceof Error ? error.message : String(error)}`;
      }
    },
  • Zod schema defining the required input parameters: namespace and slug.
    parameters: z.object({
      namespace: z
        .string()
        .describe(
          "The namespace/organization of the MCP server (e.g., 'microsoft', 'openai')",
        ),
      slug: z
        .string()
        .describe(
          "The slug/name of the MCP server (e.g., 'playwright-mcp', 'gpt-mcp')",
        ),
    }),
  • src/server.ts:89-120 (registration)
    The server.addTool call that registers the 'get_mcp_server_details' tool, including annotations, description, handler, name, and parameters schema.
    server.addTool({
      annotations: {
        openWorldHint: true,
        readOnlyHint: true,
        title: "Get MCP Server Details",
      },
      description:
        "Get detailed information about a specific MCP server by namespace and slug",
      execute: async (args) => {
        try {
          const result = await makeGlamaRequest(
            `/v1/servers/${args.namespace}/${args.slug}`,
          );
          return JSON.stringify(result, null, 2);
        } catch (error) {
          return `Error getting MCP server details: ${error instanceof Error ? error.message : String(error)}`;
        }
      },
      name: "get_mcp_server_details",
      parameters: z.object({
        namespace: z
          .string()
          .describe(
            "The namespace/organization of the MCP server (e.g., 'microsoft', 'openai')",
          ),
        slug: z
          .string()
          .describe(
            "The slug/name of the MCP server (e.g., 'playwright-mcp', 'gpt-mcp')",
          ),
      }),
    });
  • Shared helper function used by the tool to make HTTP requests to the Glama MCP API.
    async function makeGlamaRequest(
      endpoint: string,
      params?: Record<string, string>,
    ) {
      const url = new URL(`${GLAMA_API_BASE}${endpoint}`);
    
      if (params) {
        Object.entries(params).forEach(([key, value]) => {
          if (value) {
            url.searchParams.append(key, value);
          }
        });
      }
    
      const response = await fetch(url.toString());
    
      if (!response.ok) {
        throw new Error(
          `API request failed: ${response.status} ${response.statusText}`,
        );
      }
    
      return response.json();
    }
Behavior3/5

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

Annotations provide readOnlyHint=true and openWorldHint=true, indicating safe read operations and potential for unknown data. The description adds value by specifying the retrieval scope ('detailed information') and identification method, but doesn't disclose behavioral traits like error handling, rate limits, or response format. With annotations covering safety, a baseline of 3 is appropriate as the description offers some context without rich behavioral details.

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 front-loads the core purpose ('Get detailed information') and includes essential specifics ('about a specific MCP server by namespace and slug'). There is no wasted text, and every word contributes to clarity, making it appropriately sized and well-structured.

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

Completeness4/5

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

Given the tool's low complexity (2 required parameters, no output schema), the description is mostly complete. It clearly states the purpose and parameters, but lacks details on return values (e.g., what 'detailed information' includes) and error cases. With annotations providing safety context, it's adequate, though could be slightly enhanced for full completeness.

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%, with clear descriptions for both parameters (namespace and slug). The description adds marginal value by reinforcing the purpose of these parameters ('by namespace and slug') but doesn't provide additional semantics beyond what the schema already documents, such as format constraints or examples. Baseline 3 is correct when the schema handles most of the parameter documentation.

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 clearly states the specific action ('Get detailed information') and resource ('about a specific MCP server'), with precise identification criteria ('by namespace and slug'). It distinguishes from sibling tools like 'search_mcp_servers' (which likely returns multiple servers) and 'get_mcp_server_attributes' (which might return specific attributes rather than comprehensive details).

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 description implies usage context by specifying 'by namespace and slug,' suggesting this tool is for retrieving details of a known, specific server. However, it doesn't explicitly state when to use this versus alternatives like 'search_mcp_servers' (for unknown servers) or 'get_mcp_server_attributes' (for partial data), nor does it mention prerequisites or exclusions, leaving some guidance gaps.

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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