FreshRSS MCP Server
Enables interaction with FreshRSS RSS feed readers through the Google Reader compatible API. Supports feed management, article reading/searching, and marking articles as read or starred.
README
FreshRSS MCP Server
A Model Context Protocol (MCP) server for interacting with FreshRSS via its Google Reader compatible API. This server provides tools for browsing feeds, reading articles, and managing subscriptions. Authentication is handled during server startup.
Features
User Information
get_user_info()- Get authenticated user information
Feed Management
list_subscriptions()- List all RSS feed subscriptionsadd_subscription()- Add new RSS feed subscriptionlist_categories()- List all categories/tags with unread counts
Article Reading
get_articles()- Get articles from feeds, categories, or reading listsearch_articles()- Search articles by keywordsget_starred_articles()- Get all starred articlesget_unread_counts()- Get unread article counts by feed/category
Article Management
mark_article_read()- Mark specific article as readmark_article_starred()- Star/unstar articlesmark_all_as_read()- Mark all articles in a stream as read
Installation
- Install dependencies:
pip install -r requirements.txt
- Run the MCP server with your FreshRSS credentials:
# Using command line arguments
python freshrss_mcp_server.py --url https://your-freshrss-server.com --email your-email@example.com --password your-password
# Or using environment variables
export FRESHRSS_EMAIL="your-email@example.com"
export FRESHRSS_PASSWORD="your-password"
python freshrss_mcp_server.py --url https://your-freshrss-server.com
Usage
Once the server is running and authenticated, you can use the available tools:
Basic Operations
# List subscriptions
subscriptions = await list_subscriptions()
# Get recent articles
articles = await get_articles(count=10)
# Search for articles
results = await search_articles("python", count=5)
# Mark article as read
await mark_article_read("article-id-here")
# Get unread counts
unread = await get_unread_counts()
Stream IDs
Common stream IDs for getting articles:
user/-/state/com.google/reading-list- All articlesuser/-/state/com.google/starred- Starred articlesuser/-/state/com.google/read- Read articlesfeed/[feed-url]- Specific feeduser/-/label/[category]- Specific category
Command Line Options
--url(required): FreshRSS server URL--email: Email address for authentication (can also use FRESHRSS_EMAIL env var)--password: Password for authentication (can also use FRESHRSS_PASSWORD env var)
API Compatibility
This server implements the Google Reader API endpoints that FreshRSS supports:
- Authentication (
/accounts/ClientLogin) - handled at startup - User info (
/reader/api/0/user-info) - Subscriptions (
/reader/api/0/subscription/list,/reader/api/0/subscription/quickadd) - Articles (
/reader/api/0/stream/contents/) - Tagging (
/reader/api/0/edit-tag) - Unread counts (
/reader/api/0/unread-count) - Categories (
/reader/api/0/tag/list)
Requirements
- Python 3.7+
- FastMCP library
- aiohttp for async HTTP requests
- FreshRSS server with API access enabled
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。