Silverbullet AI MCP server

SilverBullet AI Plug

This plug integrates various LLMs (Large Language Models) into SilverBullet, the markdown-based note taking tool, allowing users to perform various AI-related tasks directly within their notes. It requires SilverBullet to work, and also access to either a self-hosted or SaaS LLM such as Ollama, OpenAI (ChatGPT), Google Gemini, etc.

silverbullet-ai is very new and is still in early development. It may not work as expected. Please report any issues you encounter, or feature ideas.

If you are new here, start with either the AI: Chat on current page command or the custom templated prompts!

Warning: Please backup your notes before using this plug. It inserts and replaces text at certain points and isn't well-tested yet, so back up your data!

Features

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• Interactive Chat: Multi-turn conversations using the current note as the chat interface
• AI Assistant Panel: Right-side chat panel for persistent conversations across pages
• RAG (Retrieval Augmented Generation): Automatic vector embedding search for relevant context
• Context Enrichment: Wiki-link parsing, template expansion, and custom enrichment functions
• AI Agents: Create specialized AI personas with custom system prompts, tool filtering, and page or Lua-based definitions
• AI Tools: Built-in tools (read, create, update notes; search, navigate; execute Lua) with custom tool support and approval gates
• Templated Prompts: Define custom prompts as pages or in Space Lua with multiple insertion modes
• Vector Embeddings: Chunk-based embeddings stored in SilverBullet's datastore for semantic search
• Note Summaries: Experimental - Generate and index page summaries
• Image Generation: DALL-E integration with auto-upload and caption insertion
• Bundled Prompts: Generate tags, suggest page names, generate frontmatter, enhance notes
• Provider Support: OpenAI, Google Gemini, Ollama, Mistral AI, Perplexity AI, OpenRouter, any OpenAI-compatible API

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Available commands

The list below are the commands available in this plugin.

Shortened. The full README is on GitHub.