RAT (Retrieval Augmented Thinking)
This RAT (Retrieval Augmented Thinking) MCP server, developed by Skirano, implements a two-stage reasoning process combining DeepSeek's analysis capabilities with various response models. Built with TypeScript and leveraging the Model Context Protocol SDK, it offers flexible model selection, persistent conversation context, and customizable reasoning visibility. The implementation focuses on enhancing AI responses through structured reasoning, with features like context management and multi-model support. It's particularly useful for developers and researchers working on improving AI conversation quality, enabling use cases such as more thoughtful chatbots, enhanced question-answering systems, and AI-assisted analysis tasks without directly dealing with individual API complexities.
Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately. Last scanned 2026-09-28.
Scan details: Circle-IR · 2026-09-28 · Appeal
View full trust & usage report →Metadata
- Version
- 1.0.0
- Skill type
- atomic
- Execution layer
- mcp-remote
- Category
- productivity
- Source
- PulseMCP
- Author type
- human
- Last scanned
- 2026-09-28
- Updated
- 2026-09-28
Use via MCP
Resolve RAT (Retrieval Augmented Thinking) from your agent
Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.
One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp--scope user for --scope project to commit it to .mcp.json.