Sleep▌
by agentsworkingtogether
Sleep enables AI systems to add timed pauses with configurable limits for time-based coordination and rate limiting via
Enables AI systems to introduce timed pauses in execution flow, supporting both stdio and SSE transport methods with configurable timeout limits for time-based coordination and rate limiting.
Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.
best for
- / Workflow automation requiring timed delays
- / Rate limiting API calls or operations
- / Sequential task execution with waiting periods
capabilities
- / Pause execution for specified duration
- / Control workflow timing and sequencing
- / Add delays between automated actions
- / Implement rate limiting in agent workflows
what it does
Adds a simple sleep function that pauses AI execution for a specified number of seconds. Useful for controlling timing and flow in automated workflows.
about
Sleep is a community-built MCP server published by agentsworkingtogether that provides AI assistants with tools and capabilities via the Model Context Protocol. Sleep enables AI systems to add timed pauses with configurable limits for time-based coordination and rate limiting via It is categorized under developer tools. This server exposes 1 tool that AI clients can invoke during conversations and coding sessions.
how to install
You can install Sleep in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
license
Apache-2.0
Sleep is released under the Apache-2.0 license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
readme
Sleep MCP Server
This MCP server attempts to pause execution for a specified duration to control the flow of your agents. Enhance your automation by introducing timed delays, ensuring tasks are executed in the desired sequence. Ideal for managing workflows that require waiting periods between actions.
<a href="https://glama.ai/mcp/servers/@AgentsWorkingTogether/mcp-sleep"> <img width="380" height="200" src="https://glama.ai/mcp/servers/@AgentsWorkingTogether/mcp-sleep/badge" alt="Sleep MCP Server" /> </a>Setup
Installation
Using MCP package managers
Smithery
To install Sleep MCP for Claude Desktop automatically via Smithery:
npx @smithery/cli install @AgentsWorkingTogether/mcp-sleep --client claude
mcp-get
You can install the Sleep MCP server using mcp-get:
npx @michaellatman/mcp-get@latest install mcp-sleep
Prerequisites
MCP is still very new and evolving, we recommend following the MCP documentation to get the MCP basics up and running.
You'll need:
Configuration
1. Configure Claude Desktop
Create the following file depending on your OS:
On MacOS: ~/Library/Application\ Support/Claude/claude_desktop_config.json
On Windows: %APPDATA%/Claude/claude_desktop_config.json
Paste this template in the file
{
"mcpServers": {
"mcp-sleep": {
"command": "uvx",
"args": [
"mcp-sleep"
],
}
}
}
Optionally, it replace <MCP_SLEEP_TIMEOUT> with your timeout ( maximum time allowed to wait, default 60 seconds ):
{
"mcpServers": {
"mcp-sleep": {
"command": "uvx",
"args": [
"mcp-sleep"
],
"env": {
"MCP_SLEEP_TIMEOUT": "<MCP_SLEEP_TIMEOUT>"
}
}
}
}
2. Restart Claude Desktop
SSE mode
Alternatively, you can run the MCP server in SSE mode by running the following command:
uvx mcp-sleep --transport sse
This mode is useful to integrate with an MCP client that supports SSE (like a web app).
Tools
sleep- Pause execution for a specified duration to control the flow of your agents.
- Inputs:
seconds(number, max timeout config value): Seconds it will take me to tell you to continue
- Returns: You will receive the sentence after {seconds} "You can continue to do your task after you've been waiting {seconds} seconds". If you enter a waiting time greater than the maximum time the result will be "My configuration does not allow me to make you wait more than {ctx.sleep.config.timeout} seconds"
Usage with Claude Desktop
To use this with Claude Desktop, add the following to your claude_desktop_config.json:
Docker
{
"mcpServers": {
"mcp-sleep": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"-e",
"MCP_SLEEP_TIMEOUT",
"mcp/sleep"
],
"env": {
"MCP_SLEEP_TIMEOUT": "<MCP_SLEEP_TIMEOUT>"
}
}
}
}
Development
Config
If you are working locally add two environment variables to a .env file in the root of the repository:
MCP_SLEEP_TIMEOUT=
For local development, update your Claude Desktop configuration:
{
"mcpServers": {
"mcp-sleep_local": {
"command": "uv",
"args": [
"run",
"--directory",
"/path/to/your/mcp-sleep",
"run",
"mcp-sleep"
]
}
}
}
<details>
<summary>Published Servers Configuration</summary>
"mcpServers": {
"mcp-sleep": {
"command": "uvx",
"args": [
"mcp-sleep"
]
}
}
</details>
Building and Publishing
To prepare the package for distribution:
- Sync dependencies and update lockfile:
uv sync
- Build package distributions:
uv build
This will create source and wheel distributions in the dist/ directory.
- Publish to PyPI:
uv publish
Note: You'll need to set PyPI credentials via environment variables or command flags:
- Token:
--tokenorUV_PUBLISH_TOKEN - Or username/password:
--username/UV_PUBLISH_USERNAMEand--password/UV_PUBLISH_PASSWORD
Docker build:
docker build -t mcp/sleep -f Dockerfile .
Debugging
Since MCP servers run over stdio, debugging can be challenging. For the best debugging experience, we strongly recommend using the MCP Inspector.
You can launch the MCP Inspector via npm with this command:
npx @modelcontextprotocol/inspector uv --directory /path/to/your/mcp-sleep run mcp-sleep
Upon launching, the Inspector will display a URL that you can access in your browser to begin debugging.
FAQ
- What is the Sleep MCP server?
- Sleep is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
- How do MCP servers relate to agent skills?
- Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
- How are reviews shown for Sleep?
- This profile displays 32 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.7 out of 5—verify behavior in your own environment before production use.
Use Cases▌
Extended AI Capabilities
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Context Enhancement
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Workflow Automation
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Implementation Guide▌
Prerequisites
- ›Claude Desktop 0.7.0+ or Cursor IDE with MCP support
- ›Basic understanding of MCP architecture and capabilities
- ›Access credentials for integrated services (if required)
- ›Willingness to experiment and iterate on configuration
Time Estimate
15-60 minutes depending on server complexity
Installation Steps
- 1.Install MCP server: npm install -g [package-name] or via GitHub
- 2.Add server configuration to ~/.claude/mcp.json
- 3.Provide required credentials and configuration
- 4.Restart Claude Desktop to load new server
- 5.Test basic functionality with simple prompts
- 6.Explore capabilities and experiment with use cases
- 7.Document successful patterns for reuse
Troubleshooting
- ⚠MCP server not loading: Check config syntax, verify installation
- ⚠Connection errors: Check network, firewall, credentials
- ⚠Feature not working: Read server docs, check required parameters
- ⚠Performance issues: Monitor resource usage, check for network latency
- ⚠Conflicts with other servers: Check port assignments, namespace collisions
Best Practices▌
✓ Do
- +Read server documentation thoroughly before setup
- +Start with simple use cases to validate functionality
- +Test in non-production environment first
- +Monitor resource usage and performance
- +Keep servers updated for bug fixes and new features
- +Document configuration for team members
- +Use environment variables for sensitive configuration
✗ Don't
- −Don't grant overly permissive access to MCP servers
- −Don't skip reading security considerations in docs
- −Don't expose sensitive data without proper controls
- −Don't run untrusted MCP servers without code review
- −Don't ignore error messages—investigate root cause
💡 Pro Tips
- ★Combine multiple MCP servers for powerful workflows
- ★Create custom MCP servers for your specific needs
- ★Share successful configurations with team
- ★Use MCP inspector for debugging
- ★Join MCP community for tips and troubleshooting
Technical Details▌
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
- Model Context Protocol (MCP)
- JSON-RPC 2.0
- stdio or HTTP transport
Compatibility
- Claude Desktop
- Cursor IDE
- Custom MCP clients
When to Use This▌
✓ Use When
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid When
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.
Integration▌
- →Tool composition: Chain multiple MCP tools in workflows
- →Context augmentation: Provide AI with relevant external data
- →Action delegation: Let AI execute tasks on external systems
- →Bidirectional sync: Keep AI context and external systems in sync
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
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Ratings
4.7★★★★★32 reviews- ★★★★★Evelyn Huang· Dec 28, 2024
Sleep has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
- ★★★★★Min Robinson· Dec 16, 2024
Sleep reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
- ★★★★★Zaid Rao· Nov 19, 2024
Sleep is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
- ★★★★★Valentina Thomas· Nov 7, 2024
I recommend Sleep for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
- ★★★★★Diya Thompson· Oct 26, 2024
Strong directory entry: Sleep surfaces stars and publisher context so we could sanity-check maintenance before adopting.
- ★★★★★Zaid Srinivasan· Oct 10, 2024
We wired Sleep into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
- ★★★★★Aisha Anderson· Sep 21, 2024
We evaluated Sleep against two servers with overlapping tools; this profile had the clearer scope statement.
- ★★★★★Oshnikdeep· Sep 17, 2024
Useful MCP listing: Sleep is the kind of server we cite when onboarding engineers to host + tool permissions.
- ★★★★★Mia Anderson· Sep 17, 2024
Sleep is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
- ★★★★★Kabir Patel· Aug 12, 2024
Sleep is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
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