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PopNx MCPAIを使う人のためのMCPサーバー · やさしい言葉で解説

Worklore

作者:workloreバージョン 0.9.0i★ –iクラウドで動く
レジストリ名io.github.worklore/worklore

インストール

概要

作者による説明(英語の原文)

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

PopNx MCPの3つの柱

この3つを1つのスコアにまとめることはしません。意見、測定、人気はそれぞれ別のものだからです。

できること

このサーバーのやさしい解説はまだ書いていません。以下はレジストリから読み取った事実です。

  • 接続方法: クラウドで動く
  • トランスポート: Streamable HTTP
  • カテゴリ: 検索・AIの記憶

インストール

使っているAIアプリを選んで、設定をコピーしてください。

インストールの前に

必要なもの

どのアプリを使っていますか?

上でアプリを選んでください。選んだアプリを覚えておくので、次からはボタンに「…にインストール」と表示されます。

ウェブ、デスクトップ、モバイルのClaudeで使えます:

  1. Settings → Connectors を開く
  2. Add custom connector を押す
  3. 下のアドレスを貼り付けて Add を押す
  4. サインインを求められたら、作者のサービスにサインインする
SettingsConnectors1+ Add2https://…3
https://worklore.dev/mcp

ターミナルでこれを実行します

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

Cursorで開く

または、設定を自分でコピーする

プロジェクトの .cursor/mcp.json、または ~/.cursor/mcp.json に貼り付けます

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

ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。

VS Codeで開く

または、設定を自分でコピーする

プロジェクトの .vscode/mcp.json に貼り付けます

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

ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。

ChatGPTがつなげるのは、インターネット上のサーバーだけです:

  1. ウェブ版のChatGPTを開き → Settings → Connectors (Apps)
  2. Create または Add を押す(プランによっては、先に Advanced で Developer mode をオンにする必要があります)
  3. 下のアドレスを貼り付け、名前を付けて保存する
  4. サインインを求められたら、作者のサービスにサインインする
SettingsConnectors1+ Create2https://…3
https://worklore.dev/mcp

メニューの名前は、プランや時期によって少し違うことがあります。

選んだアプリは、この端末のCookieに保存されます。アカウントは不要です。

この設定は、作者のレジストリ登録情報から作成しています。READMEと違う場合は、READMEに従ってください。

できること

ツールの名前と説明は、サーバーが2026年11月7日に返したそのままの内容です。書いたのは作者で、私たちではありません。プレーンテキストとして表示しています。

  • 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).

基本チェックi

誰でも見られる情報をチェックしており、コードは読んでいません。当てはまらない項目は数に入れていません。 · 2026年11月7日にチェック

  • ✓ 合格

    作者とリポジトリが一致

    レジストリ名は、リポジトリを所有するGitHubアカウント worklore で確認済みです

  • … 未チェック

    今もメンテナンスされている

    このリポジトリはまだGitHubから読み取っていません

  • … 未チェック

    ライセンスがある

    このリポジトリはまだGitHubから読み取っていません

  • ✓ 合格

    エンドポイントが応答する

    393ミリ秒で応答(HTTP 200)

  • – 対象外

    OAuthでサインイン

    サインイン不要

  • ✓ 合格

    ツールの説明に隠れた指示がない

    10件のツールの説明を読み、AIへの隠れた指示は見つかりませんでした

検索・AIの記憶のほかのサーバーとの比較i

  • このカテゴリのほかの7282件のうち0%よりスターが多い
  • このカテゴリのほかの7282件のうち76%より最近レジストリに公開
  • 基本チェックの結果が、このカテゴリのほかの7282件のうち100%と同じかそれ以上

レジストリでこのカテゴリにある有効なすべてのサーバーと比較しています。スターは、公開者がリポジトリの所有者である場合だけ数えます。

よくある質問

Workloreは安全ですか?

当てはまる基本チェック3項目のうち3項目に合格しました。コードは読んでいません。キーやトークンを追加する前に、サーバーがどんなアクセスを求めているかを確認し、必要な権限だけを持つキーを使ってください。

どんなキーやコードが必要ですか?

レジストリには必須のキーは載っていません。ただし、最初に使うときにサインインを求めるサーバーもあります。

パソコンで動きますか、それともクラウドですか?

作者のクラウドで動きます。インストール不要でインターネット経由でつながりますが、送った内容は作者のサーバーを通ります。

今もメンテナンスされていますか?

GitHubリポジトリの最終更新は–、最新バージョン(0.9.0)がレジストリに届いたのは11 日前です。

どのアプリで使えますか?

Claude Desktop、Claude Code、Cursor、VS CodeなどのMCP対応アプリで使えます。URLでつながるので、リモートMCPサーバーに対応したアプリ(開発者モードのChatGPTなど)でも使えます。

代わりに使えるものは?

同じカテゴリには:Context7, Codebase Memory, Exa

代わりの候補

同じカテゴリで、ほかの作者が作ったサーバー。スターの多い順。

カードの見方:★ GitHubスターi3つの柱:レビュー · チェック · 利用状況i更新=最新バージョンをレジストリに公開した日i

Context7

作者:upstash

Up-to-date docs for AI agents

パソコンでもクラウドでも★ 64,224MIT昨日更新
インストール

Codebase Memory

作者:DeusData

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

パソコンで動く★ 48,148MIT21 日前更新
インストール

Exa

作者:exa-labs

Connect AI agents to Exa for web search, content fetching, and multi-step research.

クラウドで動く★ 5,213MIT先月更新
インストール

作者のREADME

READMEを開く

作者のリポジトリから書かれたとおりにコピーしたものです。PopNx MCPは内容を確認・推奨していません。HTML、画像、スクリプトは取り除いています。リンクはこのサイトの外へ移動します。

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

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