Prompts.chat▌
by f
Prompts.chat — proxy to the prompts.chat API offering a searchable prompt library with filtering by keyword, type, categ
Proxy server that forwards requests to the prompts.chat API, providing access to a curated collection of prompts with search and filtering capabilities by keyword, type, category, and tag.
github stars
★ 25
Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.
best for
- / Developers looking for coding prompts and templates
- / AI users building prompt libraries
- / Teams sharing and discovering prompt collections
capabilities
- / Search AI prompts by keyword, category, or tag
- / Retrieve specific prompts by ID with variable substitution
- / Save new prompts to your prompts.chat account
- / Browse prompts using MCP prompts capability
- / Filter prompts by type and category
what it does
Provides access to a curated collection of AI prompts from prompts.chat with search functionality and template variable support. Lets you discover, retrieve, and save prompts directly in your AI coding assistant.
about
Prompts.chat is a community-built MCP server published by f that provides AI assistants with tools and capabilities via the Model Context Protocol. Prompts.chat — proxy to the prompts.chat API offering a searchable prompt library with filtering by keyword, type, categ It is categorized under developer tools. This server exposes 3 tools that AI clients can invoke during conversations and coding sessions.
how to install
You can install Prompts.chat 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 supports remote connections over HTTP, so no local installation is required.
license
MIT
Prompts.chat is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
readme
prompts.chat MCP Server
Access thousands of AI prompts directly in your AI coding assistant
--- ## Features - **MCP Prompts** - Browse and use prompts directly via MCP prompts capability - **Search Prompts** - Search for AI prompts by keyword, category, or tag - **Get Prompt** - Retrieve prompt details by ID with variable substitution - **Variable Support** - Prompts with `${variable}` syntax are automatically handled ## 🛠️ Installation ### Requirements - Node.js >= v18.0.0 - An MCP-compatible client (Cursor, Windsurf, VS Code, Claude Code, etc.)Install in Cursor
Add this to your Cursor MCP config file (`~/.cursor/mcp.json`): #### Remote Server (Recommended) ```json { "mcpServers": { "prompts-chat": { "url": "https://prompts.chat/api/mcp" } } } ``` #### Local Server ```json { "mcpServers": { "prompts-chat": { "command": "npx", "args": ["-y", "@fkadev/prompts.chat-mcp"] } } } ```Install in Windsurf
Add this to your Windsurf MCP config file: #### Remote Server (Recommended) ```json { "mcpServers": { "prompts-chat": { "serverUrl": "https://prompts.chat/api/mcp" } } } ``` #### Local Server ```json { "mcpServers": { "prompts-chat": { "command": "npx", "args": ["-y", "@fkadev/prompts.chat-mcp"] } } } ```Install in VS Code
Add this to your VS Code MCP settings: #### Remote Server (Recommended) ```json "mcp": { "servers": { "prompts-chat": { "type": "http", "url": "https://prompts.chat/api/mcp" } } } ``` #### Local Server ```json "mcp": { "servers": { "prompts-chat": { "type": "stdio", "command": "npx", "args": ["-y", "@fkadev/prompts.chat-mcp"] } } } ```Install in Claude Code
#### Remote Server (Recommended) ```sh claude mcp add --transport http prompts-chat https://prompts.chat/api/mcp ``` #### Local Server ```sh claude mcp add prompts-chat -- npx -y @fkadev/prompts.chat-mcp ```Install in Zed
Add this to your Zed `settings.json`: ```json { "context_servers": { "prompts-chat": { "command": { "path": "npx", "args": ["-y", "@fkadev/prompts.chat-mcp"] } } } } ```FAQ
- What is the Prompts.chat MCP server?
- Prompts.chat 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 Prompts.chat?
- This profile displays 42 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.6 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
4.6★★★★★42 reviews- ★★★★★Liam Johnson· Dec 28, 2024
I recommend Prompts.chat for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
- ★★★★★Liam Smith· Dec 16, 2024
According to our notes, Prompts.chat benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
- ★★★★★Pratham Ware· Dec 8, 2024
Prompts.chat has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
- ★★★★★Aanya Nasser· Dec 8, 2024
Prompts.chat is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
- ★★★★★Yash Thakker· Nov 27, 2024
According to our notes, Prompts.chat benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
- ★★★★★Aarav Iyer· Nov 27, 2024
I recommend Prompts.chat for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
- ★★★★★Olivia Iyer· Nov 23, 2024
Strong directory entry: Prompts.chat surfaces stars and publisher context so we could sanity-check maintenance before adopting.
- ★★★★★Aarav Gupta· Nov 19, 2024
Prompts.chat is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
- ★★★★★Liam Reddy· Nov 7, 2024
Prompts.chat has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
- ★★★★★Michael Huang· Oct 26, 2024
We evaluated Prompts.chat against two servers with overlapping tools; this profile had the clearer scope statement.
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