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PhialsBasement

GitHub MCP Server Plus

search_repositories

Find GitHub repositories using search queries with pagination support to locate code projects based on specific criteria.

Instructions

Search for GitHub repositories

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesSearch query (see GitHub search syntax)
pageNoPage number for pagination (default: 1)
perPageNoNumber of results per page (default: 30, max: 100)

Implementation Reference

  • The core handler function for the 'search_repositories' tool. It constructs a GitHub search URL with query, page, and per_page parameters, fetches the data using githubRequest, and parses the response with GitHubSearchResponseSchema.
    export async function searchRepositories(
      query: string,
      page: number = 1,
      perPage: number = 30
    ) {
      const url = new URL("https://api.github.com/search/repositories");
      url.searchParams.append("q", query);
      url.searchParams.append("page", page.toString());
      url.searchParams.append("per_page", perPage.toString());
    
      const response = await githubRequest(url.toString());
      return GitHubSearchResponseSchema.parse(response);
    }
  • Zod schema defining the input structure for the 'search_repositories' tool, including query (required), and optional page and perPage parameters.
    export const SearchRepositoriesSchema = z.object({
      query: z.string().describe("Search query (see GitHub search syntax)"),
      page: z.number().optional().describe("Page number for pagination (default: 1)"),
      perPage: z.number().optional().describe("Number of results per page (default: 30, max: 100)"),
    });
  • index.ts:74-77 (registration)
    Registration of the 'search_repositories' tool in the MCP server's listTools response, providing name, description, and input schema.
      name: "search_repositories",
      description: "Search for GitHub repositories",
      inputSchema: zodToJsonSchema(repository.SearchRepositoriesSchema),
    },
  • MCP server dispatch handler for 'search_repositories' tool calls: parses arguments, invokes the repository.searchRepositories function, and formats the response as MCP content.
    case "search_repositories": {
      const args = repository.SearchRepositoriesSchema.parse(request.params.arguments);
      const results = await repository.searchRepositories(
        args.query,
        args.page,
        args.perPage
      );
      return {
        content: [{ type: "text", text: JSON.stringify(results, null, 2) }],
      };
    }
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 provides minimal information. It states this is a search operation but doesn't describe what the search returns (repository metadata, full objects?), authentication requirements, rate limits, error conditions, or whether this is a read-only operation. The agent must infer behavior from the name alone.

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 maximally concise - a single clear sentence that states exactly what the tool does. There's zero wasted language, no redundancy, and it's perfectly front-loaded with the core functionality. Every word earns its place in this minimal description.

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 search tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what format results come in, what fields are returned, whether there are limitations on search scope, or how results are structured. The agent knows what to search for but not what to expect back or under what constraints the search operates.

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 three parameters thoroughly. The description adds no parameter information beyond what's in the schema - it doesn't explain search syntax examples, typical query patterns, or how results are ordered. The baseline of 3 is appropriate when the schema does all the parameter documentation work.

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 ('Search for') and resource ('GitHub repositories'), making the purpose immediately understandable. However, it doesn't differentiate this tool from sibling search tools like 'search_code', 'search_issues', or 'search_users' - all of which also search GitHub but for different resource types.

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 this tool is appropriate compared to other search tools (search_code, search_issues, search_users) or when to use it versus browsing repositories through other means. There's no indication of prerequisites, limitations, or typical use cases.

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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