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PopNx MCP为使用 AI 的人准备的 MCP 服务器 · 用大白话讲清楚

Worklore

作者:worklore版本 0.9.0i★ 0i在云端运行
注册名称io.github.worklore/worklore

安装方法

What it does

Search worklore stories and x-ray any skill or story capability tier (T0-T4) before you run it.

  • Connects 在云端运行
  • Account or key No key needed
  • Category 搜索与 AI 记忆

安装

选择你使用的 AI 应用,然后复制设置。

通过 4/5 项检查 · 你的提问会经过开发者的服务器(worklore.dev) · ✓ 命令已检查 2026年11月13日

第一步:你用哪个 AI?

选择你用的应用,步骤会显示在下方。

可连接 Claude · 约 2 分钟

不需要密钥,不用安装程序 · 在 claude.ai 或桌面应用设置一次,即可在聊天中使用 · 免费账户可添加 1 个 · Team/Enterprise 方案由所有者(Owner)添加

  1. 打开 Claude 的 Connectors 页面

    CustomizeConnectors

    CustomizeConnectors1Add2https://…3Add4
  2. 点击“Add” → “Custom” → “Web”,填写这 2 项

    把这里的内容复制到 Claude 中同名的输入框,然后点击 Continue

    Name · 名称Worklore
    Remote MCP server URL · 地址https://worklore.dev/mcp

    在 Claude 检测到的登录设置页点击 Continue · Authentication 按作者说明选择(Sign in now、Sign in when needed 或 No sign in),然后点击 Add

  3. 在聊天中开启

    +ConnectorsWorklore

  4. 试一试

    用 Worklore 告诉我你能帮我做什么,然后做一件给我看

    ✓ 如果 Claude 说正在使用 Worklore,或回答中出现 Worklore 的工具名称,就表示连接成功

菜单名称已于 2026年11月11日 对照 Anthropic 帮助页面核实 · 你的界面可能因版本略有不同

能否连接 ChatGPT 取决于方案

完整 MCP:网页版 ChatGPT Business、Enterprise 或 Edu · Pro:以读取/获取权限连接,修改数据的工具可能用不了 · Plus:官方文档尚未确认,如果在插件页看到添加自定义 MCP 的选项可以试试 · 仅限网页

  1. 在网页版 ChatGPT 打开添加 MCP 的页面

    Plugins+Add custom MCP server

    ChatGPTPlugins1+2https://…3Create4
  2. 填写名称和地址

    输入名称,在 Connection 下粘贴地址,勾选风险提示,然后点击 Create as a plugin

    Name · 名称Worklore
    Connection · 地址https://worklore.dev/mcp
  3. 在聊天中选择 Worklore

    开启新聊天,输入前先从插件列表中选择 Worklore

  4. 试一试

    用 Worklore 告诉我你能帮我做什么,然后做一件给我看

    ✓ 如果 ChatGPT 说正在使用 Worklore,或回答中出现 Worklore 的工具名称,就表示连接成功

菜单名称已于 2026年11月11日 对照 OpenAI 帮助页面核实 · 你的界面可能因版本略有不同

可连接 Claude Code · 约 2 分钟

不需要密钥,不用安装程序

  1. 打开终端

    Mac:按 Command+空格,输入 Terminal · Windows:打开 PowerShell

  2. 粘贴这条命令并按 Enter

    claude mcp add --transport http --scope user worklore https://worklore.dev/mcp
  3. 在 Claude Code 中输入 /mcp

    应能看到 Worklore 在列表中并显示已连接

  4. 试一试

    用 Worklore 告诉我你能帮我做什么,然后做一件给我看

    ✓ 如果 Claude Code 说正在使用 Worklore,或回答中出现 Worklore 的工具名称,就表示连接成功

菜单名称已于 2026年11月11日 对照 Anthropic 帮助页面核实 · 你的界面可能因版本略有不同

可连接 Cursor · 约 2 分钟

不需要密钥,不用安装程序

  1. 点击这个按钮打开 Cursor

    在 Cursor 中打开

    Cursor 会请你确认安装,点击 Install

  2. 在 Cursor 中以 Agent 模式打开 AI 聊天

  3. 试一试

    用 Worklore 告诉我你能帮我做什么,然后做一件给我看

    ✓ 如果 Cursor 说正在使用 Worklore,或回答中出现 Worklore 的工具名称,就表示连接成功

菜单名称已于 2026年11月11日 对照 Cursor 帮助页面核实 · 你的界面可能因版本略有不同

可连接 VS Code · 约 2 分钟

不需要密钥,不用安装程序

  1. 点击这个按钮打开 VS Code

    在 VS Code 中打开

    VS Code 会请你确认安装,点击 Install

  2. 在 VS Code 中以 Agent 模式打开 AI 聊天

  3. 试一试

    用 Worklore 告诉我你能帮我做什么,然后做一件给我看

    ✓ 如果 VS Code 说正在使用 Worklore,或回答中出现 Worklore 的工具名称,就表示连接成功

菜单名称已于 2026年11月11日 对照 VS Code 帮助页面核实 · 你的界面可能因版本略有不同

其他支持 MCP 的应用(如 Windsurf、Zed、Gemini CLI)添加方式各不相同,请在应用列表中查看

查看所有支持 MCP 的应用 →

通过网页连接的应用使用的地址

地址https://worklore.dev/mcp

JSON 设置在下方“开发者专用”中

卡住了?问问正在用 Worklore 的人💬 讨论 →
开发者专用:终端命令和 JSON 设置

通过网页连接

Claude Code

claude mcp add --transport http --scope user worklore https://worklore.dev/mcp

Cursor (~/.cursor/mcp.json)

{
  "mcpServers": {
    "worklore": {
      "url": "https://worklore.dev/mcp"
    }
  }
}

VS Code (mcp.json)

{
  "servers": {
    "worklore": {
      "type": "http",
      "url": "https://worklore.dev/mcp"
    }
  }
}

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。

一览

每周下载量i
不在 npm/PyPI 上
许可证i
未注明许可证
连接方式
在云端运行
传输方式
streamable-http
最新版本i
0.9.0
发布到注册中心i
2026年10月27日
代码最后更新i
2026年11月10日
作者
worklore
注册状态
活跃

哪些应用可以使用它

依据这个服务器的连接方式和各应用自己的文档,检查于 2026年11月10日。

通过互联网连接,适用于

ClaudeChatGPTGooseLM StudioMsty StudioCherry StudioCursorVS Code + GitHub CopilotVisual StudioWindsurf (Devin Desktop)ZedKiroClineContinueJetBrains AI AssistantClaude CodeCodex CLIGemini CLIOpenCodenodecodeWarpLibreChatOpen WebUIRaycast

全部应用及其优缺点 →

它能做什么

工具名称和描述与服务器在 2026年11月12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。

  • check_capability

    Disclose what an agent Skill or worklore story CAN DO before you run it: a capability tier T0-T4 bound to a content sha256, with findings that carry file:line evidence, PLUS a separate list of behavioral red flags (prompt-injection / deception / exfiltration-intent / safety-bypas

  • get_story

    Fetch one worklore story by slug — its full markdown (narrative + the 'Reproduce this' contract your agent would run) WITH its capability disclosure attached (tier + findings), so you see what it can do before applying it. Read the capability first; run check_capability on the li

  • search_stories

    Search worklore stories by keyword across title, summary, tags and stack. Returns matches with their capability tier.

  • explore_keywords

    The worklore keyword map: every story tag with its story count, in four editorial groups (tools and agents, building blocks, practices, off the clock), plus the stories under one keyword when you name it. Use it when the user asks what worklore has on a topic, or wants to browse

  • suggest_for_project

    Given a short description of the current project (stack, what you're building, recent problems), suggest up to 3 worklore stories worth reproducing here, with why each fits and its tier.

  • report_reproduction

    Call this right after you apply a worklore story's steps to the user's own task, to record the reproduction (attributed to the signed-in account). Use an honest result: 'worked', 'partial' (you produced the output but it isn't verified yet), or 'failed' — all are useful. One coun

  • report_check

    Record the result of a story's read-only 'Check if this applies to you' section, run in the user's own project (attributed to the signed-in account). Run ONLY that check — change nothing, apply no fix. First decide whether it applies at all: if the project does not match the chec

  • publish_story

    Publish a NEW worklore story as the signed-in account. worklore stories are PUBLIC and honest, so before you call this you MUST show the human the complete draft — the title, the first-person narrative, and the 'Reproduce this' contract — and get their EXPLICIT approval. Never pu

  • edit_story

    Revise a worklore story the signed-in account PUBLISHED — only its author can edit it. Call get_story first, then show the human a before/after diff of your change and get their EXPLICIT approval before calling this; never edit on your own initiative. Send the COMPLETE revised st

  • suggest_edit

    Propose a revision of a worklore story written by SOMEONE ELSE, for its author to accept or decline — worklore's pull request. Use it when, while reproducing a story, a step turned out wrong, outdated or missing (a library changed, the docs caught up, a command no longer exists).

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14日

  • ✓ 通过

    作者与仓库一致

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

  • ✓ 通过

    仍在维护

    代码最后更新于4天前

  • ✕ 未通过

    有许可证

    仓库中没有找到许可证文件

  • ✓ 通过

    端点有响应

    在 466 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 10 个工具描述,未发现针对 AI 的隐藏指令

讨论

提问、分享技巧或报告无法使用。按“有帮助”数量排序。

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此处内容由用户撰写,不代表 PopNx 团队。

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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 6117 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 6117 个服务器的 67% 更新
  • 基础检查结果等于或优于此分类中其他 6117 个服务器的 56%

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。

常见问题

Worklore 安全吗?

它在 5 项适用的基础检查中通过了 4 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。

它需要哪些密钥或代码?

注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。

它在我的电脑上运行还是在云端?

它在作者的云端运行。通过互联网连接,无需安装,但你发送的内容会经过作者的服务器。

它还在维护吗?

GitHub 仓库最后更新于4天前,最新版本(0.9.0)于18天前进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。它通过 URL 连接,因此也能用于接受远程 MCP 的应用,例如网页版 ChatGPT(Business 及以上为完整 MCP;Pro 为只读)。

有什么可以替代它?

同一分类中有:Context7, Codebase Memory, OpenSEO

同类别的其他选择

同一分类中其他作者的服务器,按星标数排序。

如何看卡片:↓ 每周下载量i★ 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

Context7

Up-to-date docs for AI agents

作者:upstash广泛使用↓ 125万/周★ 6.5万前天更新

电脑或云端

Codebase Memory

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

作者:DeusData广泛使用↓ 1.7万/周★ 4.9万28天前更新

在你的电脑上运行

OpenSEO

Keyword research, site audits, rank tracking and AI visibility for your AI agent.

作者:every-app广泛使用★ 2.8万今天更新

在云端运行✓ everyapp.com

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

worklore-mcp

An MCP (Model Context Protocol) connector for worklore.dev — it lets any MCP-capable agent (Claude, ChatGPT, Cursor, …) search worklore's developer stories, read one with its capability disclosure attached, x-ray any skill or story before running it — all without an account — and, once you've signed in, record how a reproduction went, publish a story of your own, or revise one you published.

  • Endpoint: https://worklore.dev/mcp (Streamable HTTP, JSON-RPC over POST)
  • Auth: none to search and read public stories. Writes (and your private stories) use OAuth 2.1 (PKCE + dynamic client registration). Sign-in is with your GitHub public profile only — worklore sees your handle and avatar, no scopes, no email, no repositories.
  • Listed on: the official MCP Registry as io.github.worklore/worklore, and Smithery
  • Roadmap / progress: Project #1 (a "Relay Board" — the human does the site actions, the agent writes the code)

What it's for

worklore stories are text your agent *executes*. This connector brings them — and their capability tier — into your agent, so you can find relevant work and see what it can touch before you run it. Tiers describe reach (blast radius), not virtue, and this is never a "safe" verdict. See the write-up: Stop asking "is this skill safe?" — ask "what can it do?" and the tool it wraps, skill-xray.

Capability tiers: T0 inert · T1 local · T2 network · T3 elevated (secrets / persistence / privilege) · T4 opaque (fetches/runs code at runtime).

Tools

Read-only — no sign-in needed (public stories only; check_capability with a url needs sign-in, because the server fetches it for you):

ToolArgumentsReturns
check_capabilitytext or urltier (T0–T4) + sha256 + findings (file:line) + endpoints, plus behavioral red flags — capability disclosure
get_storyslugthe story's full markdown (narrative + "Reproduce this" contract) with its capability tier + findings
search_storiesquery *(optional)*matching stories (title/summary/tags/stack), each with its capability string
suggest_for_projectcontextup to 3 stories worth reproducing here, with why + tier

Write — these act as you, and need your authenticated session:

ToolArgumentsReturns
report_reproductionslug, result (worked/partial/failed), note *(optional)*the recorded reproduction. failed is a useful report and must never be inflated
report_checkslug, result (has_problem/no_problem), note *(optional)*the recorded result of a story's read-only "Check if this applies to you" section, run in your project. Only for stories that have one (get_story says has_check: true). Never record "not applicable" — when your project does not match the check's preconditions, don't call it. One result per person per story; the latest replaces the earlier one
publish_storymarkdown, or the parts (title, narrative, reproduce, tags, type, stack)the published story's slug + URL. Only ever call this with the author's explicit approval of the full draft
edit_storyslug, markdown (the full revised story), kind (rephrase/addition/correction, default rephrase), note *(required for a correction)*, source *(optional https URL)*the slug, URL, the recorded revision (at, kind, note, source) and how many reproducers were notified. Only the story's author can edit it. Show the author a before/after diff and get their approval first. The story's date never changes. If something in the story was wrong, it is a correction — which tells everyone who reproduced it — never a rephrase
suggest_editslug, markdown (the complete story as you propose it), rationale (one or two lines: what was wrong or outdated, what you changed)the suggestion id, its status (open), the story URL and a note. For a story by SOMEONE ELSE — worklore's pull request. Show the user the before/after diff and get their approval first. The story does not change: its author is notified and either accepts it as a credited revision or declines it, optionally handing the text back as a draft of the user's own. One open suggestion per person per story; sending another replaces it. For the user's own story use edit_story

All eight carry MCP annotations (readOnlyHint / openWorldHint / idempotentHint) so a client can tell the user what a call will do before they approve it, and all eight declare an outputSchema and return structuredContent, so a consuming agent can rely on shape instead of parsing prose.

Every result carries a human capability string (e.g. T0 · inert — touches nothing) so a tier code is never shown bare.

Resources

Since 0.6.0 resources/list is a fixed list of three documents — the same for everyone, every day — all readable without an account:

URIWhat it is
worklore://guideHow to use worklore through MCP: search, read a story with the user before acting, reproduce it, report honestly (failed is useful), x-ray unfamiliar skills and prompts with check_capability, publish or edit only with the user's approval
worklore://story-formatThe story format: frontmatter fields, the narrative, the "Reproduce this" contract (prerequisites / your agent will need from you / steps / verify), the optional read-only check, fail stories, proposals, sanitising, the exact-references rule. Read it before drafting a story
worklore://accessWhat answers without a token and what needs sign-in — rendered from the one access table the server enforces

Stories are reached through one resource template, worklore://story/{slug} (resources/templates/list). Public stories read without a token; a private story reads only for its author and answers like a missing one to everyone else. Every worklore://story/… URI that resources/list handed out before 0.6.0 still reads. To *find* a story, use search_stories / suggest_for_project.

Why the stories left the list: a list that changes whenever someone publishes cannot be part of a surface fingerprint — the fingerprint would "break" every day without anything breaking, and teach clients to ignore a mismatch. The contents of the three documents may change between releases; the list entries may not without a new version.

Verify the surface yourself

A version number is a promise that nothing a client depends on changed without it. Since 0.6.0 worklore publishes its surface fingerprint in the shared form `mcp-surface/1` (SPEC, by Sidney Bissoli), so you check worklore exactly the way you check every other server that publishes it. The registry entry carries it in server.json under _meta → io.modelcontextprotocol.registry/publisher-provided → io.github.sidneybissoli/mcp-surface:

  • declared.sha256 — the sha256 of what a client sees before it calls anything: the initialize result (protocol version, capabilities, instructions, serverInfo without its version) and the four lists (tools, resources, resource templates, prompts), normalised and serialised as the SPEC says;
  • anonymous — which methods answer without a token (plus one named, harmless tools/call: check_capability on inline text), and its sha256.

The fastest check is Sidney's dependency-free verify.mjs (Node 18+). It reads the registry entry for the version, makes sure the endpoint can say "no" to a method that does not exist, captures the live surface, and compares:

curl -sO https://raw.githubusercontent.com/SidneyBissoli/mcp-br-commons/main/packages/mcp-surface/exemplos/verify.mjs

node verify.mjs io.github.worklore/worklore 0.7.0

Or in Python, with nothing installed (the declared hash only):

python3 - <<'PY'

import hashlib, json, urllib.request EP = "https://worklore.dev/mcp" def rpc(method, params=None): body = {"jsonrpc": "2.0", "id": 1, "method": method, **({"params": params} if params else {})} req = urllib.request.Request(EP, data=json.dumps(body).encode(), headers={"Content-Type": "application/json", "Accept": "application/json, text/event-stream"}) return json.load(urllib.request.urlopen(req)).get("result") def canon(v): # SPEC §3: keys by UTF-16 code unit, no whitespace, JSON.stringify strings if isinstance(v, dict): return "{" + ",".join(json.dumps(k, ensure_ascii=False) + ":" + canon(v[k]) for k in sorted(v, key=lambda s: s.encode("utf-16-be"))) + "}" if isinstance(v, list): return "[" + ",".join(canon(x) for x in v) + "]" return json.dumps(v, ensure_ascii=False) def listed(method, key): # this server answers each list in one page res = rpc(method) return res.get(key) if isinstance(res, dict) else None def by(items, key): return None if items is None else sorted(items, key=lambda x: str(x.get(key)).encode("utf-16-be")) init = rpc("initialize", {"protocolVersion": "2025-06-18", "capabilities": {}, "clientInfo": {"name": "verify", "version": "1"}}) version = init"serverInfo" surface = {"initialize": {"protocolVersion": init.get("protocolVersion"), "capabilities": init.get("capabilities"), "instructions": init.get("instructions"), "serverInfo": {k: v for k, v in init["serverInfo"].items() if k != "version"}}, "tools": by(listed("tools/list", "tools"), "name"), "resources": by(listed("resources/list", "resources"), "uri"), "resourceTemplates": by(listed("resources/templates/list", "resourceTemplates"), "uriTemplate"), "prompts": by(listed("prompts/list", "prompts"), "name")} live = hashlib.sha256(canon(surface).encode()).hexdigest() entry = json.load(urllib.request.urlopen( "https://registry.modelcontextprotocol.io/v0.1/servers/io.github.worklore%2Fworklore/versions/" + version)) published = entry"server""io.modelcontextprotocol.registry/publisher-provided""declared" print("version", version, "| live", live[:12], "| registry", published[:12], "| match" if live == published else "| DIFFERS") PY

If the version is the same and the hash differs, the server changed without saying so. Tell me in an issue. 0.5.1 published worklore's own per-section hashes under a surface key; 0.6.0 replaced them with this one shared format. The idea of publishing the fingerprint with each release came from a comment by @_firelinks under Sidney Bissoli's Your MCP server changed. Its version didn't.

What answers without a token

Since 0.5.0 one rule decides it, everywhere — the site, the REST API and this server alike. It lives as a single table in worklore's backend (access.py, rendered as docs/ACCESS.md); the summary below is generated from it.

The rule. Anyone can search and read all public stories without signing in — site, REST API and MCP alike. Private stories and every write (publish, edit, report a reproduction or a check, visibility, per-user d

只显示了开头部分;其余内容请在仓库中阅读