MCP server providing official Google and Anthropic prompting guides for meta-prompt generation.
Most AI and media services work still happens through a UI a human drives. Meta MCP server moves it into the conversation instead. MCP server providing official Google and Anthropic prompting guides for meta-prompt generation.
Meta-Prompt MCP is an MCP server that surfaces official prompting best practices from Google and Anthropic directly within your LLM workflow. Instead of searching documentation or guessing how to instruct an LLM, you can query expert guides on-demand.
The server publishes 1 tool. What each one is for:
Cursor — The Cursor tool exposed by this serverConfiguration is passed through the environment: OPENROUTER_API_KEY. Treat anything key-shaped as a real credential — scope it to the minimum the server needs, and rotate it if it ever lands in a shared config.
meta-prompt-mcp on PyPI is all you need. Most clients run it directly, so configuration is a few lines and a restart.
Plenty of AI and media services servers cover similar ground. The differences that matter in practice are scope of access and how much setup stands between you and a working tool call. Meta's toolset — Cursor — is a fair guide to whether it matches your workflow. It is maintained by kapillamba4; worth a glance at recent repository activity before you build anything load-bearing on it.
SyncDev reviews every entry in this directory against the project's own documentation before publishing, and revisits them as servers change.
| Tool | What it does |
|---|---|
| Cursor | The Cursor tool exposed by this server. |
{
"mcpServers": {
"meta-prompt-mcp": {
"command": "uvx",
"args": ["meta-prompt-mcp"]
}
}
}Configuration as documented by the project. Restart the client after saving.
| Variable | Description | Required |
|---|---|---|
| OPENROUTER_API_KEY | Credential the server authenticates with. | Yes |
Build a programmable telecommunications stack for connecting telephony services with the Internet via a cloud-based utility.
Search built for AI, not humans — semantic web search that returns model-ready content, plus code context.
Answers, not links — delegate questions to Perplexity's search-grounded models and get cited responses back.
Give your assistant a voice — text-to-speech, voice cloning and audio tools from the ElevenLabs API.
Give your assistant a real code sandbox — isolated cloud VMs for actually running the code it writes.
The ML hub in your context window — search models, datasets, papers and run Spaces from the official server.