developer-tools

Prompts.chat

f

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

0 commentsdiscussion

Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.

Remote server option — zero setupThousands of curated promptsTemplate variable support

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

prompts.chat MCP Server

Access thousands of AI prompts directly in your AI coding assistant

Website NPM Version License

--- ## 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"] } } } } ```
## ⚙️ Configuration The local server supports the following environment variables: | Variable | Description | |----------|-------------| | `PROMPTS_API_KEY` | Optional API key for authenticated requests | | `PROMPTS_QUERY` | Optional query string to filter prompts (e.g., `users=a,b&categories=c,d&tags=e,f`) | ### Example with Environment Variables ```json { "mcpServers": { "prompts-chat": { "command": "npx", "args": ["-y", "@fkadev/prompts.chat-mcp"], "env": { "PROMPTS_API_KEY": "your-api-key", "PROMPTS_QUERY": "users=username&categories=coding&tags=productivity" } } } } ``` ## 🔨 Available Tools | Tool | Description | |------|-------------| | `search_prompts` | Search for AI prompts by keyword. Supports filtering by type, category, and tag. | | `get_prompt` | Get a prompt by ID. Supports variable elicitation for prompts with template variables. | | `save_prompt` | Save a new prompt to your account. **Requires `PROMPTS_API_KEY`.** | ## 📚 MCP Prompts This server exposes all public prompts from prompts.chat as MCP prompts. Use `prompts/list` to browse available prompts and `prompts/get` to retrieve them with variable substitution. ## 📖 Example Usage Ask your AI assistant: ``` Search for prompts about code review ``` ``` Get the prompt for "act as a linux terminal" ``` ## 🔗 Links - [prompts.chat](https://prompts.chat) - Browse all prompts - [API Documentation](https://prompts.chat/docs/api) - API reference - [GitHub](https://github.com/f/prompts.chat) - Source repository ## 📄 License ISC

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. 1.Install MCP server: npm install -g [package-name] or via GitHub
  2. 2.Add server configuration to ~/.claude/mcp.json
  3. 3.Provide required credentials and configuration
  4. 4.Restart Claude Desktop to load new server
  5. 5.Test basic functionality with simple prompts
  6. 6.Explore capabilities and experiment with use cases
  7. 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

4.642 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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