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leejersey

Hexo Blog MCP Server

by leejersey

search_posts

Search Hexo blog posts by keyword to find specific articles in titles and content using this MCP server tool.

Instructions

按关键词搜索文章标题和正文内容

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes搜索关键词

Implementation Reference

  • The core logic for searching posts, which iterates through markdown files and checks if the title or content contains the query string.
    export async function searchPosts(query: string): Promise<PostMeta[]> {
        const files = await fs.readdir(POSTS_DIR);
        const mdFiles = files.filter((f) => f.endsWith(".md"));
        const q = query.toLowerCase();
        const results: PostMeta[] = [];
    
        for (const file of mdFiles) {
            const fullPath = path.join(POSTS_DIR, file);
            const raw = await fs.readFile(fullPath, "utf-8");
            const { data, content } = matter(raw);
    
            if (
                (data.title && String(data.title).toLowerCase().includes(q)) ||
                content.toLowerCase().includes(q)
            ) {
                results.push({
                    title: data.title || file.replace(/\.md$/, ""),
                    date: data.date ? String(data.date) : "未知",
                    tags: Array.isArray(data.tags) ? data.tags : data.tags ? [data.tags] : [],
                    filename: file,
                    wordCount: content.length,
                });
            }
        }
    
        return results;
    }
  • Tool registration for "search_posts" which uses the Zod schema for input validation and calls the handler from `post-manager.ts`.
    server.tool(
        "search_posts",
        "按关键词搜索文章标题和正文内容",
        { query: z.string().describe("搜索关键词") },
        async ({ query }) => {
            try {
                const results = await searchPosts(query);
                if (results.length === 0) {
                    return { content: [{ type: "text" as const, text: `未找到包含 "${query}" 的文章。` }] };
                }
                const summary = results
                    .map((p, i) => `${i + 1}. 【${p.title}】 (${p.date}) - ${p.filename}`)
                    .join("\n");
                return {
                    content: [
                        { type: "text" as const, text: `找到 ${results.length} 篇相关文章:\n\n${summary}` },
                    ],
                };
            } catch (e: any) {
                return { content: [{ type: "text" as const, text: `错误: ${e.message}` }], isError: true };
            }
        }
    );
Behavior2/5

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

No annotations are provided, so the description carries full burden for behavioral disclosure. It states what the tool does but doesn't describe how it behaves: no information on search scope (e.g., partial/full matches), result format, pagination, sorting, error handling, or performance characteristics. For a search tool with zero annotation coverage, this leaves significant gaps.

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 extremely concise—a single sentence in Chinese that directly states the tool's function. It's front-loaded with the core action and resource, with no wasted words or redundant information. This is efficient and easy to parse.

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?

Given the tool's complexity (search functionality with one parameter) and lack of annotations and output schema, the description is incomplete. It doesn't explain what the tool returns, how results are structured, or any behavioral nuances. For a search tool, this leaves the agent guessing about output and usage details.

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 description adds minimal value beyond the input schema. Schema description coverage is 100%, with the single parameter 'query' documented as '搜索关键词' (search keyword). The description implies the parameter is used for searching titles and bodies but doesn't provide additional syntax, format, or constraint details. Baseline 3 is appropriate when the schema does the heavy lifting.

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: searching posts by keyword in both title and body content. It uses specific verbs ('搜索' - search) and resources ('文章标题和正文内容' - post titles and body content). However, it doesn't explicitly differentiate from sibling tools like 'list_posts' or 'read_post', 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 when search is preferable to listing posts, when to use it versus 'read_post' for specific content, or any prerequisites or constraints. The agent must infer usage from context alone.

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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