AI Workstation Open Source Intelligence

io.github.zxhwolfe-dev由 GitHub 帳號 zxhwolfe-dev 發布v0.3.3更新於 Oct 24, 2026

Read-only AI project discovery, verification, comparison, shortlisting, and stack planning.

發布方自己的服務：Source

已驗證Streamable HTTP可網頁執行知識與記憶開發者工具

概覽

AI 產生的概覽

唯讀的遠端 MCP 伺服器，用來調研開源 AI 專案：搜尋、核實事實與授權、比較專案並規劃技術堆疊。

可以做什麼
依明確需求搜尋並核實開源 AI 專案，取得指定專案有證據支撐的公開事實，包括觀測到的授權證據（不構成法律意見）。在明確的決策情境下比較二到五個專案，或在保留硬性限制的前提下尋找經過核實的替代方案。組合候選開源 AI 技術堆疊並揭露未知的相容性。瀏覽 Radar 的排名、合集、分類、情境、主題與篩選條件，並瀏覽或依 ID 開啟 Radar Skills 資料庫中的項目。結果會區分已核實事實、建議、未知項目與風險。
適用情境
當你需要依部署、隱私、整合、預算或授權要求篩選、比較或核查開源 AI 專案，或在不安裝、不執行任何第三方程式碼的情況下擬定候選技術堆疊時適用。
執行需求
遠端 streamable HTTP 端點；未宣告需要身分驗證、API 金鑰或環境變數。README 說明匿名存取有依 IP 的速率限制（例如短時間視窗每分鐘 60 次請求、持續每分鐘 10 次）以及 256 KB 請求內容上限。另提供供開發使用的本機 Python 套件方式。
安裝前請注意
唯讀且僅提供資料：不會執行或安裝第三方儲存庫程式碼，也不提供伺服器端模型呼叫或結帳功能。授權輸出屬於技術證據而非法律意見，缺少授權不應視為取得許可。相容性結論可能未經核實，會以未知項目呈現；結果包含發布方連結，不應視為已核實事實。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 AI Workstation Open Source Intelligence，將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Web executable，透過 Streamable HTTP。 遠端服務在工作區中設定後即可從網頁執行環境執行。

交給代理程式安裝

把這段提示詞貼上到 Claude Code、Codex、Cursor 等代理程式，或 SourceWeft 對話中。代理程式會讀取該伺服器的安裝指南，先向你展示發布者、端點和登入方式，經你同意後再把它新增到你的客戶端。金鑰不會寫進任何命令。

閱讀 https://sourceweft.com/mcp/io.github.zxhwolfe-dev%2Faiworkstation-open-source-intelligence/install.md，並按其中說明把這個 MCP 伺服器接入我的客戶端。修改任何設定之前，先告訴我它的發布者、端點和登入方式，等我確認。不要把 API 金鑰寫進命令或我會提交的檔案；問我金鑰應從哪裡取得。

檢視代理程式所依據的安裝指南

其他 MCP 客戶端

把它新增到你客戶端的 mcpServers 設定中。

{
  "mcpServers": {
    "ai-workstation-open-source-intelligence": {
      "type": "http",
      "url": "https://mcp.aiworkstation.cn/mcp"
    }
  }
}

README

AI Open Source Intelligence

One Skill. Nine live read-only Radar tools. Evidence-backed open-source AI research without a second server-side model call.

简体中文 · Product page · AI Open Source Radar · Quickstart

AI Open Source Intelligence is the Skills/MCP product layer for AI Open Source Radar.

[AI Open Source Radar production homepage showing rankings, project cards, and the AI Open Source Intelligence product entry]

Production screenshot captured 2026-08-29. Rankings and project data update with Radar snapshots.

Product shape

text
User in ChatGPT / Codex / compatible host                 |                 v      1 unified product Skill                 |                 v      9 read-only MCP tools                 |                 v     AI Workstation public Radar

The user does not choose separate research/comparison/stack Skills. The single Skill routes the task internally.

The host model performs natural-language reasoning and synthesis. The AI Workstation server provides data/evidence only on this product path.

One active Skill

text
ai-open-source-intelligence

It handles:

  • browsing rankings, collections, categories, scenarios and the Radar Skills library;
  • finding projects from deployment, privacy, integration, budget and license requirements;
  • verifying named-project facts and license evidence;
  • comparing two to five projects for a concrete use case;
  • finding alternatives while preserving hard requirements;
  • planning candidate open-source AI stacks and exposing unverified compatibility.

The only product Skill is packaged from:

text
skills/ai-open-source-intelligence/SKILL.mdskills/ai-open-source-intelligence/agents/openai.yaml

agents/openai.yaml makes the Skill's dependency on the canonical ai_open_source_intelligence Hosted MCP explicit while keeping automatic invocation enabled. This is the Skill-level dependency contract; .mcp.json is the matching Plugin-level connection contract.

The previous split research/comparison/stack Skill files are removed from the current product and distribution bundle.

Nine standard MCP tools

text
search_ai_projectsget_project_factsget_license_evidencecompare_ai_projectsfind_alternativescompose_ai_stackget_radar_overviewbrowse_radar_projectsbrowse_radar_skills

All nine are read-only. They do not execute or install third-party repository code.

No AI Workstation server-model execution

This is a hard product boundary for the current release.

The Hosted MCP exposes no Premium model tool, no checkout tool and no runtime OAuth/Premium switch. Requirement-based selection calls the public Radar selector with:

text
use_model=false

Therefore an ordinary Skill/MCP workflow is:

text
ChatGPT/Codex host model        -> chooses/read tools        -> AI Workstation public Radar data/evidence        -> host model synthesizes the final answer

It is not:

text
host model -> AI Workstation model -> second model bill

If member-linked server-model capabilities are added later, they must ship as a new reviewed product version rather than being enabled through a hidden environment variable.

Evidence model

Every tool result separates:

  1. verified facts — source-backed observations that crossed the evidence boundary;
  2. recommendations — host-model/rules analysis;
  3. unknowns — unavailable or unverified information;
  4. risks — license, maintenance, deployment, security and integration limits.

A value in data is not automatically a verified fact. License evidence is deliberately stricter and is technical evidence, not legal advice.

Requirement tools publish the actual typed constraint contract through MCP:

json
{"id":"web_ui","value":true,"polarity":"required"}

Formal matches are revalidated against project-detail evidence. README excerpts may directly verify narrow Docker, self-hosting, browser UI and low/no-code claims; unresolved hard requirements become near-match blockers. A License label is exposed only as observed_license_label until a direct LICENSE-family source supports a verified license fact. Response observation time and evidence-source freshness are reported separately.

Official resources in results

MCP tool results include canonical, non-tracking publisher links under:

text
data.official_resources

with:

The unified Skill may show these once at the end of a normal user-facing answer. They are kept separate from verified facts so publisher attribution never changes a research conclusion.

Hosted MCP

Canonical endpoint:

text
https://mcp.aiworkstation.cn/mcp

Current Hosted mode is intentionally:

text
anonymousread-onlydata-only9 toolsno OAuthno WorkOS dependencyno Premium/server model

The container stays on host loopback 127.0.0.1:8001 behind Nginx/TLS.

Anonymous abuse controls

The gateway uses two per-IP request windows plus a connection cap:

  • short-window: 60 requests/minute, burst 30;
  • sustained: 10 requests/minute, burst 300;
  • concurrent connections: 10 per IP;
  • MCP request body: 256 KB maximum;
  • unrelated paths on the dedicated MCP hostname return 404.

This is intentionally request-based rather than token-based because the nine data tools do not consume AI Workstation model tokens.

Use it now

The published v0.3.3 Plugin packages the unified Skill and the production Hosted MCP configuration together. Codex and the ChatGPT desktop Codex host can install both from one version-pinned marketplace entry. The public ChatGPT directory listing is still pending review. Today:

  • Codex / ChatGPT desktop users can install the complete repository Plugin;
  • ChatGPT web users can register https://mcp.aiworkstation.cn/mcp as a No Authentication developer-mode app while the public listing is pending;
  • Python users can install the matching CLI/MCP package from PyPI with:
bash
python -m pip install \  "aiworkstation-open-source-intelligence[mcp]==0.3.3"

See the Quickstart for exact ChatGPT, Codex and Python steps and the v0.3.3 Release for signed-off assets and checksums. The immutable v0.3.0 archive remains the earlier Skills-only artifact; the complete Plugin uses the current v0.3.3 patch identity rather than replacing it.

Local development

bash
python -m venv .venvsource .venv/bin/activatepython -m pip install -e ".[mcp]"

Offline fixture data:

bash
OSI_PROVIDER=mock osi-mcp

Live public Radar data:

bash
OSI_PROVIDER=http \AIWORKSTATION_RADAR_BASE_URL=https://aiworkstation.cn \osi-mcp

Hosted configuration check requires an exact candidate identity:

bash
OSI_PROVIDER=http \OSI_HOSTED_ACCESS_MODE=public \OSI_RELEASE_COMMIT=<exact-40-char-sha> \OSI_IMAGE_COMMIT=<same-exact-40-char-sha> \osi-mcp-hosted --check-config

Setting OSI_HOSTED_ACCESS_MODE=oauth fails closed in the current release.

Safety rules

  • never execute third-party repository code as part of research;
  • never infer permission from a missing license;
  • never silently weaken a hard requirement to manufacture a match;
  • never claim cross-project compatibility without evidence or a controlled test;
  • never substitute model memory for unavailable live evidence;
  • never enable AI Workstation server-side model execution in the current standard Skill/MCP path.

Development checks

bash
python -m compileall -q src testspython -m unittest discover -s tests -vosi-validate-plugin --root .osi-readiness --root .

CI covers Python 3.10 and 3.12, deterministic Skill packaging, MCP round trips, data-only Hosted configuration and container packaging.

License

The public repository is licensed under Apache-2.0. That does not grant rights to private AI Workstation databases, unpublished datasets, credentials, infrastructure or trademarks.

來源：README.md，提交 73ada4a

工具

9

search_ai_projects

Search open-source AI projects

Find and verify open-source AI projects from explicit requirements.

輸入參數query必填localerequest_idconstraints

get_project_facts

Get verified project facts

Get current evidence-backed public facts for one project.

輸入參數localeproject_id必填request_id

get_license_evidence

Get project license evidence

Get observed license evidence; the result is not legal advice.

輸入參數localeproject_id必填request_id

compare_ai_projects

Compare open-source AI projects

Compare two to five projects in one explicit decision context.

輸入參數localecontextcriteriarequest_idproject_ids必填

find_alternatives

Find open-source project alternatives

Find verified candidate alternatives while preserving constraints.

輸入參數localeproject_id必填request_idconstraints

compose_ai_stack

Compose an open-source AI stack

Compose a candidate open-source AI stack and expose unknown compatibility.

輸入參數localerequest_idconstraintsbusiness_goal必填existing_stack

get_radar_overview

Get AI Open Source Radar overview

Discover current rankings, collections, categories, scenarios and filters.

輸入參數localerequest_id

browse_radar_projects

Browse AI Open Source Radar projects

Browse rankings, collections, categories, scenarios, topics or filtered projects.

輸入參數rolelayerlimitquerytopiclocaleoffsetlicenserankingcategoryscenariouse_case另有 6 個

browse_radar_skills

Browse AI Open Source Radar Skills

Browse/filter the Radar Skills library or open one Skill by ID.

輸入參數kindsortlimitquerylocaleoffsetlicensecategoryskill_idrequest_idinstallable

版本歷史

1
  1. v0.3.3最新Sep 16, 2026

評分

已滿足適用檢查項的 100%

該評分衡量此收錄條目的完整程度，依據註冊中心條目、端點與公開來源計算得出。它不是對伺服器本身的評價，也不表示伺服器安全或目前可用：可連通性是帶日期的檢查結果，評分也不包含安裝量或使用者評價。

  • 近 30 天內可連通必需25 分
  • 已宣告認證方式必需10 分
  • 已列出工具必需15 分
  • 描述必需15 分
  • 圖示10 分
  • 文件15 分
  • 授權條款10 分

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