AI Workstation Open Source Intelligence

io.github.zxhwolfe-devPublished by GitHub account zxhwolfe-devv0.3.3Updated Oct 24, 2026

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

The publisher's own server: Source

VerifiedStreamable HTTPWeb executableKnowledge & MemoryDeveloper Tools

Overview

AI-generated overview

A read-only remote MCP server for researching open-source AI projects: searching, verifying facts and licenses, comparing, and planning stacks.

What you can do
Search and verify open-source AI projects from explicit requirements, and retrieve evidence-backed public facts for a named project, including observed license evidence (not legal advice). Compare two to five projects in a stated decision context, or find verified alternatives while keeping hard constraints. Compose a candidate open-source AI stack and surface unknown compatibility. Browse the Radar's rankings, collections, categories, scenarios, topics and filters, and browse or open entries in the Radar Skills library. Results separate verified facts, recommendations, unknowns and risks.
When to use it
Useful when you need to shortlist, compare or sanity-check open-source AI projects against deployment, privacy, integration, budget or license requirements, or to assemble a candidate stack without installing or running any third-party code.
Requirements
A remote streamable HTTP endpoint; no authentication, API keys or environment variables are declared. The README notes anonymous per-IP rate limits (for example 60 requests per minute short-window and 10 per minute sustained) and a 256 KB request body cap. A local Python package variant is also described for development.
Before you install
Read-only and data-only: it does not execute or install third-party repository code, and no server-side model calls or checkout are exposed. License output is technical evidence, not legal advice, and a missing license should not be read as permission. Compatibility claims may be unverified and are reported as unknowns; results include publisher links that should not be treated as verified facts.

Installation

In SourceWeft

  1. Open AI Workstation Open Source Intelligence in the dashboard and add it to a workspace.
  2. Enable the server for the chats that should use its tools.

Web executable via Streamable HTTP. Remote servers run from the web runtime once configured in a workspace.

Use with an agent

Paste this prompt into Claude Code, Codex, Cursor or another agent — or into SourceWeft chat. The agent reads this server's install guide, shows you its publisher, endpoint and sign-in, and adds it to your client once you agree. Keys never go into a command.

Read https://sourceweft.com/mcp/io.github.zxhwolfe-dev%2Faiworkstation-open-source-intelligence/install.md and connect the MCP server it describes to my client. Before changing any config, show me its publisher, endpoint and sign-in method and wait for my OK. Never put an API key in a command or in a file I would commit; ask me where it should come from.

Read the install guide the agent follows

Other MCP clients

Add this to your client's mcpServers config.

{
  "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.

Source: README.md at commit 73ada4a

Tools

9

search_ai_projects

Search open-source AI projects

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

Parametersqueryrequiredlocalerequest_idconstraints

get_project_facts

Get verified project facts

Get current evidence-backed public facts for one project.

Parameterslocaleproject_idrequiredrequest_id

get_license_evidence

Get project license evidence

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

Parameterslocaleproject_idrequiredrequest_id

compare_ai_projects

Compare open-source AI projects

Compare two to five projects in one explicit decision context.

Parameterslocalecontextcriteriarequest_idproject_idsrequired

find_alternatives

Find open-source project alternatives

Find verified candidate alternatives while preserving constraints.

Parameterslocaleproject_idrequiredrequest_idconstraints

compose_ai_stack

Compose an open-source AI stack

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

Parameterslocalerequest_idconstraintsbusiness_goalrequiredexisting_stack

get_radar_overview

Get AI Open Source Radar overview

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

Parameterslocalerequest_id

browse_radar_projects

Browse AI Open Source Radar projects

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

Parametersrolelayerlimitquerytopiclocaleoffsetlicenserankingcategoryscenariouse_case+6 more

browse_radar_skills

Browse AI Open Source Radar Skills

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

Parameterskindsortlimitquerylocaleoffsetlicensecategoryskill_idrequest_idinstallable

Version history

1
  1. v0.3.3LatestSep 16, 2026

Score

100% of the applicable checks met

How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.

  • Reached in the last 30 daysRequired25 pts
  • Auth declaredRequired10 pts
  • Tools listedRequired15 pts
  • DescriptionRequired15 pts
  • Logo10 pts
  • Documentation15 pts
  • License10 pts

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