What is a grounded answer layer?
A grounded answer layer retrieves from real source material—such as PDFs, docs, or screenshots—rather than relying on generic model memory, so responses are source-backed, explainable, and production-ready.
@calypso-so
基本信息
Launch a hosted Gemini File Search true multimodal RAG layer that answers from your PDFs, docs, screenshots, charts, diagrams, help center, FAQs, and images with citations people can verify.
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"calypso-mcp": {
"command": "npx",
"args": [
"-y",
"calypso-mcp"
],
"env": {
"CALYPSO_API_KEY": "YOUR_CALYPSO_API_KEY",
"CALYPSO_API_BASE_URL": "https://api.calypso.so/v1"
}
}
}
}工具列表暂未提供
当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。
点击上方按钮,在临时沙箱中运行此服务器并实时获取工具列表。
Calypso Multimodal RAG is an MCP server that brings multimodal Retrieval-Augmented Generation (RAG) to AI tools and workflows, providing a grounded answer layer for websites, AI agents, support copilots, internal knowledge assistants, and product experiences. It retrieves from actual source materials—PDFs, docs, screenshots, diagrams, charts, help content, and structured knowledge—to ensure answers remain source-backed, explainable, and production-ready.
After configuring the Calypso MCP server in your MCP client (e.g., Claude Desktop), you can invoke three tools: calypso-rag-agent to query the RAG agent for grounded answers, calypso-upload-agent-file to upload a file into the agent store, and calypso-upload-knowledge-file to upload a file into the durable knowledge store.
rag_policy on agent file attachments.A grounded answer layer retrieves from real source material—such as PDFs, docs, or screenshots—rather than relying on generic model memory, so responses are source-backed, explainable, and production-ready.
Calypso supports PDFs, documentation, help center content, screenshots, diagrams, charts, images, internal files, and structured knowledge.
The server provides two upload tools: `calypso-upload-agent-file` puts content into the agent store for retrieval-backed RAG chat, and `calypso-upload-knowledge-file` ingests content into a durable knowledge store for shared corpus indexing.
Calypso is designed as a multimodal grounded answer layer with reuse across multiple surfaces, retrieval over real source material, and strong fit for operational and customer-facing AI systems.

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