# Content Extract MCP

Python MCP scaffold for article content extraction, structured summary validation, deterministic filtering, and Markdown sink output.

## Run

```bash
pip install -e .
summary-mcp
```

The server exposes three tools:

- `extract_url_content`
- `extract_item_content`
- `filter_summary_result`

Validate an LLM summary result:

```bash
validate-llm-result outputs/result.json --extracted outputs/read-flow-2026.extracted.json
```

Run the minimal extraction-to-summary loop:

```bash
python scripts/run_summary_loop.py ^
  --extracted outputs/read-flow-2026.extracted.json ^
  --prompt outputs/llm-summary-prompt.txt ^
  --output outputs/result.json
```

Pull FreshRSS entries and map them into normalized `item` objects:

```bash
set FRESHRSS_API_BASE_URL=http://127.0.0.1:8081/api/greader.php
set FRESHRSS_USERNAME=bot
set FRESHRSS_API_PASSWORD=your-api-password
python scripts/pull_freshrss_items.py --limit 5
```

The script writes:

- `outputs/freshrss.raw.json`
- `outputs/freshrss.items.json`

Pull FreshRSS entries and run content extraction for each mapped item:

```bash
set FRESHRSS_API_BASE_URL=http://127.0.0.1:8081/api/greader.php
set FRESHRSS_USERNAME=osiman
set FRESHRSS_API_PASSWORD=your-api-password
python scripts/run_freshrss_extract.py --limit 1
```

The script writes:

- `outputs/freshrss.raw.json`
- `outputs/freshrss.items.json`
- `outputs/freshrss.extracted.json`

Run deterministic filter rules against a structured summary result:

```bash
python scripts/run_filter_rules.py ^
  --summary outputs/result.json ^
  --extracted outputs/read-flow-2026.extracted.json ^
  --output outputs/filter-decision.json
```

You can optionally pass a context file to inject interest topics or source tags:

```bash
python scripts/run_filter_rules.py ^
  --summary outputs/result.json ^
  --extracted outputs/read-flow-2026.extracted.json ^
  --context outputs/filter-context.json ^
  --output outputs/filter-decision.with-context.json
```

Write a filtered result into the Markdown sink:

```bash
python scripts/run_markdown_sink.py ^
  --summary outputs/result.json ^
  --extracted outputs/read-flow-2026.extracted.json ^
  --filter outputs/filter-decision.json
```

The script writes markdown notes under `knowledge-base/`.