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 · AI Workstation · AI Open Source Radar · Quickstart

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

Product shape

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

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:

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

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:

use_model=false

Therefore an ordinary Skill/MCP workflow is:

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

It is not:

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.

Official resources in results

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

data.official_resources

with:

• AI Workstation — https://aiworkstation.cn/
• AI Open Source Radar — https://aiworkstation.cn/githubai/
• this open-source project — 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:

https://mcp.aiworkstation.cn/mcp

Current Hosted mode is intentionally:

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 repository Plugin now packages the unified Skill and the production Hosted MCP configuration together. After this change reaches main, Codex and the ChatGPT desktop Codex host can install both from one 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;
• after v0.3.1 is published, Python users can install the matching CLI/MCP package with:

python -m pip install \
  "aiworkstation-open-source-intelligence[mcp]==0.3.1"

See the Quickstart for exact ChatGPT, Codex and Python steps. The immutable v0.3.0 archive remains the earlier Skills-only artifact; the complete Plugin uses the v0.3.1 patch identity rather than replacing it.

Local development

python -m venv .venv
source .venv/bin/activate
python -m pip install -e ".[mcp]"

Offline fixture data:

OSI_PROVIDER=mock osi-mcp

Live public Radar data:

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

Hosted configuration check requires an exact candidate identity:

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

python -m compileall -q src tests
python -m unittest discover -s tests -v
osi-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.