Metadata-Version: 2.4
Name: alpha-terminal-mcp
Version: 0.1.0
Summary: Alpha Terminal MCP Server - the governance layer for the AI economy
Project-URL: Homepage, https://alpha.ac
Project-URL: Repository, https://github.com/alpha-ac/alpha-terminal-mcp
Project-URL: Documentation, https://alpha.ac/institute/methodology
Project-URL: Issue Tracker, https://github.com/alpha-ac/alpha-terminal-mcp/issues
Project-URL: Changelog, https://github.com/alpha-ac/alpha-terminal-mcp/releases
Author-email: Alpha <institute@alpha.ac>
License: Proprietary
License-File: LICENSE
Keywords: ai-governance,board-directors,corporate-governance,esg,mcp,model-context-protocol,ratings,regulatory,sec-filings
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Financial and Insurance Industry
Classifier: Intended Audience :: Legal Industry
Classifier: License :: Other/Proprietary License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Topic :: Office/Business
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Typing :: Typed
Requires-Python: >=3.11
Requires-Dist: httpx>=0.27.0
Requires-Dist: mcp[cli]>=1.0.0
Requires-Dist: pydantic>=2.0.0
Requires-Dist: python-dotenv>=1.0.0
Description-Content-Type: text/markdown

# Alpha Terminal MCP Server

Alpha Terminal is the domain-specific MCP server for board-level AI governance. Built by Alpha, The AI Governance Company.

## What It Does

Enables any AI system to:
- **Understand board composition** - Directors, committees, AI expertise, independence
- **Evaluate AI governance maturity** - The Alpha Standard dimension scoring under The Alpha Standard
- **Detect governance risks** - Red flags, governance debt, regulatory exposure
- **Benchmark companies** - Peer comparison, sector rankings, percentile analysis
- **Generate board-ready outputs** - Briefs, memos, gap analyses, defense assessments

## Data Coverage

| Data | Count |
|------|-------|
| Companies | 9,700+ |
| Directors | 2,200+ |
| SEC Filings | 345 |
| Governance Ratings | 56+ (growing) |
| AI Regulations | 50+ jurisdictions |

## Quick Start

### Install

```bash
cd alpha_mcp_server
pip install -e .
```

### Configure

```bash
cp .env.example .env
# Edit .env with your Alpha tenant API key
```

### Run

```bash
# stdio mode (for Claude Desktop, Claude Code, etc.)
alpha-terminal-mcp

# Backward-compatible alias for existing clients
alpha-governance-mcp

# Or run directly
python -m alpha_governance_mcp.server
```

### Publish to Smithery

The remote MCP endpoint is the deployed Supabase Edge Function:

```bash
npx -y smithery@latest mcp publish \
  "https://api.alpha.ac/functions/v1/mcp-server" \
  -n alpha-ac/alpha-terminal-mcp \
  --config-schema ./smithery.config.schema.json
```

The Smithery config schema forwards the user-provided Alpha key as `x-api-key`.

For the local Python stdio package, build and publish an MCPB bundle:

```bash
uv lock
npx -y @anthropic-ai/mcpb@latest validate ./manifest.json
npx -y @anthropic-ai/mcpb@latest pack . ./dist/alpha-terminal-mcp-0.1.0.mcpb
npx -y smithery@latest mcp publish ./dist/alpha-terminal-mcp-0.1.0.mcpb -n alpha-ac/alpha-terminal-mcp
```

### Publish to PyPI

PyPI publishing uses GitHub Actions trusted publishing. Configure the PyPI
project `alpha-terminal-mcp` with:

- Owner: `wolfepereira`
- Repository: `alpha-platform`
- Workflow: `publish-alpha-terminal-mcp.yml`
- Environment: `pypi`

Then publish a GitHub release or run the workflow manually from `main`.

### Claude Desktop Configuration

Add to `~/Library/Application Support/Claude/claude_desktop_config.json`:

```json
{
  "mcpServers": {
    "alpha-terminal": {
      "command": "alpha-terminal-mcp",
      "env": {
        "ALPHA_API_KEY": "your_alpha_api_key_here"
      }
    }
  }
}
```

### Claude Code Configuration

Add to `.claude/settings.json`:

```json
{
  "mcpServers": {
    "alpha-terminal": {
      "command": "alpha-terminal-mcp",
      "env": {
        "ALPHA_API_KEY": "your_alpha_api_key_here"
      }
    }
  }
}
```

## MCP Resources

| URI | Description |
|-----|-------------|
| `alpha://company/{ticker}/board` | Board composition |
| `alpha://company/{ticker}/committees` | Committee structure |
| `alpha://company/{ticker}/ai-governance-profile` | Full governance profile |
| `alpha://company/{ticker}/risk-score` | AI governance risk score |
| `alpha://company/{ticker}/proxy/latest` | Latest parsed DEF 14A |
| `alpha://regulations/{region}` | Regulatory intelligence |
| `alpha://benchmark/{sector}` | Sector benchmarking |

## MCP Tools

| Tool | Description |
|------|-------------|
| `get_board_profile` | Full board composition and director profiles |
| `parse_def14a` | Parse latest DEF 14A proxy filing |
| `score_ai_governance_risk` | Score governance risk (Alpha Governance Scale) |
| `compare_companies` | Compare governance across 2-10 companies |
| `find_ai_governance_signals` | Detect AI governance signals in filings |
| `get_regulatory_intelligence` | Regulatory obligations and timelines |
| `generate_board_brief` | Board-ready governance brief |
| `benchmark_board_ai_readiness` | Peer benchmarking and percentile ranking |
| `search_companies` | Search by name or ticker |
| `get_platform_stats` | Platform data coverage statistics |

## MCP Prompts (Workflows)

| Prompt | Description |
|--------|-------------|
| `ai_governance_board_brief` | Comprehensive board brief |
| `proxy_change_analysis` | Proxy filing change detection |
| `audit_committee_ai_risk_memo` | Audit committee risk memo |
| `director_gap_analysis` | Board expertise gap analysis |
| `activist_defense_readiness` | Activist defense assessment |

## Architecture

```
MCP Client (Claude, etc.)
    |
    v
Alpha Terminal MCP Server (FastMCP)
    |
    v
Alpha API Gateway (tenant API key)
    |
    v
PostgreSQL (alpha.ac production database)
    - companies (9,700+)
    - directors (2,200+)
    - board_seats (committee assignments)
    - governance_ratings (Alpha Governance Scale + D1-D12)
    - edgar_filings (SEC EDGAR)
    - ai_regulations (regulatory intelligence)
```

## Methodology

All ratings are issued under **The Alpha Standard** by the Alpha Institute for AI Governance.

- **Alpha Governance Scale**: AAA to D (plus NR)
- **The Alpha Standard**: 8 governance dimensions scored independently
- **Alpha Materiality Profile**: 4-dimension materiality assessment
- **Alpha Integrity Screen**: Negative screening with ceiling logic
- **Public scores**: Capped at BB+ (59) - public data cannot verify implementation
- **Assessed scores**: Full AAA-D range via alpha.ac/assessment

## License

Proprietary. Copyright Alpha, The AI Governance Company.
