thriya

thriya is an MCP server in the Healthcare category: thriya is a judgment and operating-memory layer for AI-native work. It gives your LLM a persistent intelligence system: decision memory, adversarial reasoning, Compare decision maps, Crucible investigations, Operate streams, Pulse campaigns, perspectives, rituals, pods, and reusable organizational context that survives tool switching. What you can do with Thriya via MCP: Think with memory Ask Quick Think questions grounded in your saved perspectives, decision history, workspaces, and Operate streams. Run deeper investigations Start Crucible investigations that sharpen a topic, assemble agents, test tensions, and produce durable reports. Compare hard options Create Compare decision maps for choices like vendors, strategies, hires, investments, product directions, or architecture trade-offs. Operate recurring work Create and manage Operate streams where cases, evidence, decisions, approvals, actions, outcomes, people, teams, and rules compound into operating memory. Capture judgment and outcomes Save decisions, track what happened later, extract doctrine, and reuse proven judgment in future work. Use perspectives List, apply, train, and refine perspectives so analysis reflects the user’s own lenses, domain context, and learned decision patterns. Launch Pulse campaigns Ask targeted judgment or insight questions to users, teams, customers, or external respondents, then deliver the synthesis back into the relevant stream. Coordinate human-in-the-loop work Create tasks, approvals, escalations, notes, mentions, and follow-ups across shared workspaces and Operate streams. Connect capability providers Attach external MCP servers, SaaS apps, model providers, and execution tools so Thriya can use evidence and take governed actions. Reuse intelligence everywhere Bring outputs from Crucible, Compare, Quick Think, North Stars, perspectives, reports, and prior decisions back into Operate streams instead of losing them in chat history. Thriya is built for founders, operators, teams, investors, advisors, and organizations that make recurring high-judgment decisions and do not want their reasoning to disappear across Claude, ChatGPT, Cursor, Slack, email, documents, and meetings. Instead of treating every AI conversation as disposable, Thriya turns judgment into a reusable asset: what you decided, why you decided it, what challenged it, who approved it, what happened afterward, and what should be learned for next time.