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.md skills/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_projects get_project_facts get_license_evidence compare_ai_projects find_alternatives compose_ai_stack get_radar_overview browse_radar_projects browse_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** โ source-backed observations that crossed the evidence boundary; 2. **recommendations** โ host-model/rules analysis; 3. **unknowns** โ unavailable or unverified information; 4. **risks** โ 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: - AI Workstation โ https://aiworkstation.cn/ - AI Open Source Radar โ https://aiworkstation.cn/githubai/ - this open-source project โ https://github.com/zxhwolfe-dev/aiworkstation-open-source-intelligence 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 anonymous read-only data-only 9 tools no OAuth no WorkOS dependency no 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](https://github.com/zxhwolfe-dev/aiworkstation-open-source-intelligence/blob/HEAD/docs/QUICKSTART.md) for exact ChatGPT, Codex and Python steps and the [v0.3.3 Release](https://github.com/zxhwolfe-dev/aiworkstation-open-source-intelligence/releases/tag/v0.3.3) 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 .venv source .venv/bin/activate python -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=