Streamline MCP

Streamline MCP

Enables AI assistants to access and manage Streamline tasks, notes, tags, and workspaces via a Supabase-powered backend. It supports full CRUD operations, allowing users to search, create, update, and organize their productivity data through natural language.

Category
访问服务器

README

Streamline MCP

MCP server that gives AI assistants access to your Streamline tasks, notes, tags, and workspaces.

Setup

1. Configure credentials

Create ~/.config/streamline-mcp/config.json:

{
  "projectURL": "https://YOUR_PROJECT_ID.supabase.co",
  "apiKey": "YOUR_SERVICE_ROLE_KEY",
  "userID": "YOUR_USER_UUID"
}

Where to get these:

  • apiKey: Supabase Dashboard → Settings → API → service_role key
  • userID: Supabase Dashboard → Authentication → Users → Your user ID

2. Add to Claude Code

Edit ~/.claude.json:

{
  "mcpServers": {
    "streamline": {
      "command": "npx",
      "args": ["github:YOUR_USERNAME/streamline-mcp"]
    }
  }
}

Or run locally:

{
  "mcpServers": {
    "streamline": {
      "command": "node",
      "args": ["/path/to/streamline-mcp/dist/index.js"]
    }
  }
}

3. Restart Claude Code

The tools will now be available.


Tools

Tasks

Tool Description
search_tasks Search by name, tags, due date, status, or workspace
read_task Get full details by UUID
create_task Create a new task
update_task Update name, notes, due date, urgency
complete_task Mark completed or uncompleted
delete_task Move to trash or delete permanently

Notes

Tool Description
search_notes Search by title, content, tags, or workspace
read_note Get full content by UUID
create_note Create with markdown content
update_note Replace content or append
delete_note Move to trash or delete permanently

Tags

Tool Description
list_tags List all tags
create_tag Create a new tag
tag_item Add tag to a task or note
untag_item Remove tag from a task or note

Workspaces

Tool Description
list_workspaces List all workspaces with filtering rules
read_workspace Get workspace details (by UUID or name)

Examples

# Create a task with tags and due date
create_task(name: "Review PR", due_date: "tomorrow", tags: ["work"], is_urgent: true)

# Search tasks due today
search_tasks(due_before: "today", include_completed: false)

# Search tasks in a specific workspace
search_tasks(workspace: "Work", due_before: "today")

# Search notes in a workspace
search_notes(workspace: "Projects", query: "meeting notes", limit: 10)

# List workspaces with their filtering rules
list_workspaces(include_rules: true)

# Get workspace details by name
read_workspace(name: "Work")

# Complete a task
complete_task(uuid: "550e8400-e29b-41d4-a716-446655440000")

# Append to a note
update_note(uuid: "...", append: "\n\n## Follow-up\nNew content here")

Workspace Filtering

Workspaces in Streamline are defined by tag-based filtering rules. When you filter by workspace, the MCP applies those rules to return only matching items.

Example workspace rules:

  • "Work": Show items with "Work" or "Project" tags, exclude "Personal"
  • "Trove": Show items with all of "Trove" AND "Active" tags

The list_workspaces tool shows a summary of each workspace's rules, and read_workspace provides the full rule structure.


Environment Variables

You can use environment variables instead of a config file:

SUPABASE_URL=https://YOUR_PROJECT_ID.supabase.co
SUPABASE_API_KEY=your_service_role_key
SUPABASE_USER_ID=your_user_uuid

Or in Claude Code config:

{
  "mcpServers": {
    "streamline": {
      "command": "npx",
      "args": ["github:YOUR_USERNAME/streamline-mcp"],
      "env": {
        "SUPABASE_API_KEY": "...",
        "SUPABASE_USER_ID": "..."
      }
    }
  }
}

Development

npm install
npm run build
npm start

推荐服务器

Baidu Map

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。

官方
精选
JavaScript
Playwright MCP Server

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。

官方
精选
TypeScript
Magic Component Platform (MCP)

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。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

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。

官方
精选
本地
TypeScript
VeyraX

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。

官方
精选
本地
graphlit-mcp-server

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。

官方
精选
TypeScript
Kagi MCP Server

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。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

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。

官方
精选