# AI Open Source Intelligence [Health: Active]

**Category:** 🔬 Research  
**Repository:** https://github.com/zxhwolfe-dev/aiworkstation-open-source-intelligence  
**GitHub Stars:** 2  
**Views:** 2  
**Installs:** 0  
**Upvotes:** 0  
**Directory Page:** https://allmcps.com/mcp/ai-open-source-intelligence

## Description
Nine anonymous read-only tools backed by live AI Open Source Radar data for project discovery, verified facts, direct license evidence, comparisons, alternatives, Radar browsing, and candidate stack planning. The host model performs synthesis; the server never executes third-party repository code or calls an AI Workstation server-side model.

## Tools
Capabilities this server exposes over MCP:

- **search_ai_projects** — Find and verify open-source AI projects from explicit requirements.
- **get_project_facts** — Get current evidence-backed public facts for one project.
- **get_license_evidence** — Get observed license evidence; the result is not legal advice.
- **compare_ai_projects** — Compare two to five projects in one explicit decision context.
- **find_alternatives** — Find verified candidate alternatives while preserving constraints.
- **compose_ai_stack** — Compose a candidate open-source AI stack and expose unknown compatibility.
- **get_radar_overview** — Discover current rankings, collections, categories, scenarios and filters.
- **browse_radar_projects** — Browse rankings, collections, categories, scenarios, topics or filtered projects.
- **browse_radar_skills** — Browse/filter the Radar Skills library or open one Skill by ID.

## Claude Desktop Quick Installation
Remote MCP endpoint (confidence: high). Install path detected from listing signals. Add as a URL/SSE server in your client:

```json
"mcpServers": {
  "ai-open-source-intelligence": {
    "url": "https://mcp.aiworkstation.cn/mcp"
  }
}
```

## Documentation

## What AI Open Source Intelligence MCP server does

The AI Open Source Intelligence MCP server connects an MCP-compatible host to public AI Open Source Radar data. It is designed for research tasks involving open-source AI projects, including finding candidates from explicit requirements, checking facts about a named project, comparing options, and planning a possible stack.

Results distinguish source-backed observations from host-model recommendations, unresolved information, and identified risks. This separation is useful when a project appears to match a requirement but the available evidence is incomplete. License results are technical evidence only and are not legal advice.

The product has one active Skill, named `ai-open-source-intelligence`. That Skill routes research requests to the available MCP tools rather than asking users to select separate research, comparison, or stack-planning Skills.

## How it works

The host model selects and calls the read-only tools, then synthesizes the response. The server provides Radar data and evidence; it does not perform a second AI Workstation server-side model call in the standard workflow. Requirement-based selection uses the public Radar selector with model execution disabled.

Formal requirements are represented as typed constraints, such as a required web UI. Matches are checked against project-detail evidence, and unresolved hard requirements remain blockers instead of being silently relaxed. The response also reports observation time and evidence-source freshness. Official publisher links are kept in a separate `data.official_resources` field so attribution does not alter research conclusions.

## Tools and capabilities

The nine tools are:

- `search_ai_projects`: find and verify projects against explicit requirements.
- `get_project_facts`: retrieve current public facts for one project.
- `get_license_evidence`: inspect observed license evidence from available sources.
- `compare_ai_projects`: compare two to five projects for one decision context.
- `find_alternatives`: identify candidates while retaining stated constraints.
- `compose_ai_stack`: propose a candidate stack and expose unverified compatibility.
- `get_radar_overview`: inspect rankings, collections, categories, scenarios, and filters.
- `browse_radar_projects`: browse or filter Radar projects by supported groupings.
- `browse_radar_skills`: browse the Radar Skills library or open a Skill by ID.

The AI Open Source Intelligence MCP server does not execute or install third-party repository code. It can surface compatibility unknowns, but it does not claim cross-project compatibility without evidence or a controlled test.

## Setup and configuration

The hosted endpoint is `https://mcp.aiworkstation.cn/mcp`. Hosted access is anonymous, read-only, data-only, and requires no OAuth. ChatGPT web users can register it as a No Authentication developer-mode app while the public directory listing is pending. Codex and ChatGPT desktop Codex users can install the version-pinned repository Plugin.

For local Python use, install the MCP extra at version `0.3.3`:

```bash
python -m pip install "aiworkstation-open-source-intelligence[mcp]==0.3.3"
```

Run local development with `osi-mcp`. `OSI_PROVIDER=mock` uses offline fixtures; `OSI_PROVIDER=http` uses live public Radar data and can be paired with `AIWORKSTATION_RADAR_BASE_URL=https://aiworkstation.cn`.

## Limitations and notes

All nine tools are read-only. The current hosted release has no Premium model tool, checkout flow, OAuth mode, or server-side AI Workstation model execution. Setting hosted access to OAuth fails closed.

License labels are not treated as verified licenses unless supported by a direct LICENSE-family source. Missing licenses do not imply permission. The server also does not replace legal review, execute security tests, install software, or validate compatibility through cross-project runtime testing.

Hosted traffic is subject to per-IP request and connection limits, including a 256 KB maximum MCP request body. The public repository is Apache-2.0 licensed, but that license does not grant rights to private databases, unpublished datasets, credentials, infrastructure, or trademarks.

_Full upstream README: https://allmcps.com/mcp/ai-open-source-intelligence/readme_