CaaS is a new category of software — private MCP servers that give AI agents live, persistent, structured context. Not a plugin. Not a prompt template. A dedicated data layer your AI actually calls.
Every other AI tool assumes you'll supply the context yourself — paste it in, re-explain your preferences, rebuild the background every session. CaaS inverts that. A private MCP server holds structured context and serves it to your AI on demand, the moment it's relevant. Your AI doesn't wait for you to catch it up. It already knows.
What makes CaaS different from any other software is that the context is live and queryable — not a static document, not a system prompt you manage, not a RAG pipeline you built. It's an MCP server your AI calls directly, with purpose-built tools for specific domains: memory across sessions, financial intelligence, and more. Each server is private, isolated, and yours. The longer you use it, the more precise it gets.
Every session starts cold. You re-explain your business, paste in reports, rebuild the context from scratch. Your AI gives generic answers because it doesn't know what you actually need — and every token spent re-explaining is a token not spent doing the work.
Your AI calls your private MCP server at the start of every session and gets exactly what it needs — your preferences, your data, your history. Zero re-explanation. Zero pasting. Domain-specific intelligence that no generic AI model ships with by default.
Each server is a standalone CaaS product — purpose-built for a specific type of context. Connect one or both to any MCP-compatible AI agent.
Persistent memory across every AI session. What your AI learns about your business — decisions, preferences, client context — carries forward automatically. The longer you use it, the sharper it gets.
Live SEC EDGAR data — income statements, balance sheets, cash flow — queryable by your AI in natural language. No spreadsheets. No API wrangling. Just ask, and your AI delivers institutional-grade financial intelligence.
No. Each CaaS server is fully isolated per client. Your memory store, your queries, and your data never touch another user's instance and are never used for model training. Private means private.
No. If you use Claude.ai, you connect by pasting your server endpoint under Settings → Connectors. No code, no API keys, no configuration required. Salt Creative handles the server setup — you just connect.
Yes. Both servers connect independently via MCP. Your AI can call memory tools from CognitionMCP and financial data tools from the SEC Server in the same session — they operate in parallel without conflict.
A system prompt is static text you manage manually and pay for in tokens every session. A CaaS server is a live tool your AI calls on demand — it surfaces only what's relevant, updates automatically, and costs zero tokens when it's not needed. It compounds over time. A system prompt doesn't.