Promptise is an open-source Python framework for building Agentic Systems. Turn any LLM into a production-ready agent and skip months of glue code. Five composable modules: the Agent for production-ready agents with zero boilerplate, the Reasoning Engine to design how your agent thinks from the ground up, MCP for scalable, secure and production-ready APIs that agents understand, the Agent Runtime for autonomous agents that run forever and Prompt Engineering for prompts built like software.
I m looking for some guidance on how to use the MCP to create an n8n equivalent to Gemini deep research.
What I m looking for is not the web search aspect since I already have the files I want to analyze, but rather the agentic approach that Gemini deep research uses to create super deep ,insightful reports. I haven t been able to reproduce the same level of clarity and depth, using any of the other LLM singles models , particularly in N8N.
DeepMCPAgent lets you build AI agents that auto-discover and use tools via MCP. No manual wiring—just connect your LangChain model (OpenAI, Anthropic, Ollama, etc.) and the agent dynamically generates typed tools for production-ready workflows.
