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items.","maintainers":[{"name":"chanmeng666","email":"chanmeng.dev@gmail.com"}],"readme":"# @chanmeng666/femtech-radar-mcp\r\n\r\nAn MCP (Model Context Protocol) server that fetches, deduplicates, and scores FemTech / women's-health signal across five sections — industry news, research, opportunities, community discussions, and a China-focused \"China Watch\" lens — from public sources, ready to plug into any MCP-compatible AI client.\r\n\r\n## Installation\r\n\r\nNo global install required. Run directly with `npx`:\r\n\r\n```bash\r\nnpx @chanmeng666/femtech-radar-mcp\r\n```\r\n\r\nRequires **Node.js >= 20**.\r\n\r\n## Usage with GitHub Actions Workflow (gh aw)\r\n\r\nAdd the following to your `mcp.json` or `mcp-servers` block:\r\n\r\n```yaml\r\nmcp-servers:\r\n  femtech-radar:\r\n    command: npx\r\n    args: [\"-y\", \"@chanmeng666/femtech-radar-mcp\"]\r\n```\r\n\r\n## Usage with Claude Desktop\r\n\r\nAdd to `~/Library/Application Support/Claude/claude_desktop_config.json` (macOS) or `%APPDATA%\\Claude\\claude_desktop_config.json` (Windows):\r\n\r\n```json\r\n{\r\n  \"mcpServers\": {\r\n    \"femtech-radar\": {\r\n      \"command\": \"npx\",\r\n      \"args\": [\"-y\", \"@chanmeng666/femtech-radar-mcp\"]\r\n    }\r\n  }\r\n}\r\n```\r\n\r\n## Tools\r\n\r\n### `radar_collect`\r\n\r\nFetch, deduplicate, and score FemTech items for a given section and time window.\r\n\r\n| Parameter | Type | Required | Description |\r\n|-----------|------|----------|-------------|\r\n| `section` | `string` | Yes | One of `\"industry\"`, `\"research\"`, `\"opportunities\"`, `\"discussions\"`, `\"china\"`. All five sections have live adapters. |\r\n| `since`   | `string` | No | ISO 8601 date string. Defaults to 7 days ago. |\r\n| `limit`   | `number` | No | Maximum items to return. Defaults to `15`. |\r\n\r\n**Returns:** `{ items: RadarItem[], warnings: string[] }`\r\n\r\nEach `RadarItem` has: `id`, `section`, `title`, `url`, `source`, `summary`, `score` (0–100), `published_at`, and an optional `raw_metrics` (`points`, `comments`, `citations`). Sources with engagement signals populate `raw_metrics` and feed the `popularity` term of the score — e.g. Hacker News (points/comments) and Mastodon (favourites/replies) in the `discussions` section; feed/RSS sources without engagement data score on relevance + freshness only.\r\n\r\n**Example prompt:**\r\n\r\n> \"Call `radar_collect` with section=industry to get the latest FemTech industry news.\"\r\n\r\n---\r\n\r\n### `radar_sources`\r\n\r\nList all configured data sources grouped by section.\r\n\r\nNo parameters required.\r\n\r\n**Returns:** `Array<{ section: string, sources: string[] }>`\r\n\r\n**Example prompt:**\r\n\r\n> \"Call `radar_sources` to see which data sources the radar monitors.\"\r\n\r\n## Data Sources\r\n\r\n| Section | Sources |\r\n|---------|---------|\r\n| `industry` | Google News (RSS search) |\r\n| `research` | arXiv API (femtech / women's-health / maternal query) |\r\n| `opportunities` | LinkedIn Jobs guest endpoint (default) · SerpAPI Google Jobs (opt-in via `SERP_API_KEY`) |\r\n| `discussions` | Hacker News (Algolia) · Mastodon public hashtag timelines |\r\n| `china` | Google News 中文 · 36氪 · 新浪财经 (women's-health-filtered) · PubMed (China-affiliated) · ClinicalTrials.gov (China-located) |\r\n\r\nAll sources are free and keyless except the opt-in SerpAPI path. Every source degrades gracefully to `[]` (with a warning) if unavailable, so one dead source never zeroes a section.\r\n\r\n## License\r\n\r\nMIT\r\n","readmeFilename":"README.md"}