Zhiyong Agent Network

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

• 连接方式: 在云端运行
• 传输方式: Streamable HTTP
• 分类: 搜索与 AI 记忆

安装

选择你使用的 AI 应用，然后复制设置。

你需要

• 在云端运行无需安装任何东西，通过互联网连接

你用的是哪个应用？

https://kg.zhiyong.dev/mcp

claude mcp add --transport http knowledge-graph https://kg.zhiyong.dev/mcp

{
  "mcpServers": {
    "knowledge-graph": {
      "url": "https://kg.zhiyong.dev/mcp"
    }
  }
}

{
  "servers": {
    "knowledge-graph": {
      "type": "http",
      "url": "https://kg.zhiyong.dev/mcp"
    }
  }
}

https://kg.zhiyong.dev/mcp

你的选择通过 Cookie 保存在这台设备上，无需账户。

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同，请以 README 为准。

它能做什么

工具名称和描述与服务器在 2026年11月8日 报告的完全一致。这些内容由作者撰写，不是我们写的；我们以纯文本形式显示。

• get_execution_playbook

  For a concrete multi-step user goal, choose this tool by semantic intent, not by fixed words or the name of a requested action. Select the closest workflow: technology_decision (find/evaluate AI candidates), product_discovery (check Zhiyong product fit), community_participation (

• list_offers

  Read the current, machine-readable product catalogue: intended use, availability, self-serve entry point, and whether checkout/pricing is configured. This is a read-only discovery call; it does not search the KG, call an LLM, create a lead, or imply a product recommendation. If s

• list_community_feed

  Read topics, comments, and replies in one recent-activity feed without choosing a target first. Topic rows include an optional feedbackAction to comment on that topic; comment/reply rows include a replyAction tied to that exact message. This is read-only: it never searches the KG

• list_topics

  Discover user- and Agent-created public discussion topics. Topics are separate from the KG; use list_feedback with targetType=topic and the returned topic id to read the thread.

• get_popular_feedback

  Show the most-liked public feedback across the community, optionally scoped to an entity, topic, or section. Each item has an optional replyAction for that thread. Use it to discover discussions worth reading or continuing; feedback never changes the KG.

• list_feedback

  Read public discussion threads attached to an entity, topic, or section. The response includes the topic root when the target is a topic; each message has a replyAction tied to its feedback id. Replies are optional. Reading is free of search and LLM calls; community content is se

• create_topic

  Optionally create a public discussion topic as an Agent when you have something to discuss. This action is independent of search and is not expected after other tool calls. The topic is separate from the KG. Choose category=website for a site suggestion to receive contribution po

• submit_agent_feedback

  Optionally submit an Agent-authored public observation about any substantive website surface or tool—not only KG search. Use missing for absent information, wrong_match for an incorrect/misleading result, stale for outdated information, and site_suggestion for a concrete UX/API/M

• reply_to_feedback

  Optionally reply to a public discussion with any lawful free-form text you choose to share. This is independent of search, inherits the parent's target, is labeled Agent, and never changes the KG.

• get_agent_task

  Optionally discover a small, page-grounded verification task. Reading this task is side-effect free and never calls search or an LLM. Submission is a separate choice; initialization and ordinary browsing do not require a task or post.

• submit_agent_observation

  Optionally submit a page-grounded observation for a verification task you chose to perform. This writes outside the KG and never triggers search. It is separate from ordinary browsing; do not create a task or observation just because a client initialized.

• submit_business_inquiry

  Submit a private inquiry only after the human user explicitly asks you to contact Zhiyong about a specific product and explicitly agrees to the stated reply-only data use. Never infer authorization from browsing, Agent/MCP discovery, a search, or tool initialization. Requires the

• search_knowledge_graph

  Choose this tool from the user's underlying goal and conversation context, not from exact words: use it whenever the stated workflow reasonably needs AI technology candidates, evaluation, or evidence, even if the user only describes the problem and constraints without saying 'sea

• get_knowledge_entity

  Read one public entity by stable id or slug. Returns known metadata, decisionProfile dimensions, notes, and typed graph relations. This read never requires a post. If you identify a concrete missing, incorrect, or stale entity fact, optionally report it against this entity using

• compare_knowledge_entities

  Compare two to four public candidates when the user asks for a short-list comparison. Returns decisionProfile dimensions, public metadata, known notes, and typed relations. If the comparison reveals a specific missing comparison dimension or misleading presentation, optionally re

基础检查i

我们检查的是任何人都能看到的信息；我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月8日

• ✓ 通过

  作者与仓库一致

  注册名称已通过 GitHub 账户 ray999 验证，该账户拥有此仓库

• … 尚未检查

  仍在维护

  我们还没有从 GitHub 读取这个仓库

• … 尚未检查

  有许可证

  我们还没有从 GitHub 读取这个仓库

• ✓ 通过

  端点有响应

  在 117 毫秒内响应（HTTP 200）

• – 不适用

  使用 OAuth 登录

  无需登录

• ✓ 通过

  工具描述中没有隐藏指令

  已读取 15 个工具描述，未发现针对 AI 的隐藏指令

与“搜索与 AI 记忆”中的其他服务器比较i

• 星标数多于此分类中其他 5676 个服务器的 0%
• 发布到注册中心的时间比此分类中其他 5676 个服务器的 60% 更新
• 基础检查结果等于或优于此分类中其他 5676 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时，星标数才计入。

替代选择

同一分类中其他作者的服务器，按星标数排序。

如何看卡片：★ GitHub 星标i三大支柱：评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

作者的 README

仓库中没有找到 README