Logseq MCP Tools provides AI assistants with structured access to Logseq knowledge graphs through a comprehensive set of tools for retrieving, analyzing, and manipulating data. Built with TypeScript using the Model Context Protocol SDK, it enables capabilities like retrieving page content, generating journal summaries, analyzing graph connections, identifying knowledge gaps, and suggesting potential connections between concepts. The implementation includes sophisticated natural language date parsing, DataScript query capabilities, and detailed content analysis features. It's particularly valuable for users who want to leverage AI assistants to explore, organize, and gain insights from their personal knowledge bases without leaving their conversational interface.
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Retrieves a list of all pages in your Logseq graph.
Gets the content of a specific page. Parameters: pageName (string) - The name of the page to retrieve.
Generates a summary of journal entries for a specified date range. Parameters: dateRange (string) - Natural language date range like 'today', 'this week', 'last month', 'this year', etc.
Creates a new page in your Logseq graph. Parameters: pageName (string) - Name for the new page, content (optional string) - Initial content for the page.
Searches for pages by name. Parameters: query (string) - Search query to filter pages by name.
Finds all pages that reference a specific page. Parameters: pageName (string) - The page name for which to find backlinks.
Performs a comprehensive analysis of your knowledge graph. Parameters: daysThreshold (optional number) - Number of days to look back for 'recent' content (default: 30).
Analyzes your knowledge graph to identify potential gaps and areas for improvement. Parameters: minReferenceCount (optional number) - Minimum references to consider (default: 3), includeOrphans (optional boolean) - Include orphaned pages in analysis (default: true).
Analyzes patterns in your journal entries over time. Parameters: timeframe (optional string) - Time period to analyze (e.g., 'last 30 days', 'this year'), includeMood (optional boolean) - Analyze mood patterns if present (default: true), includeTopics (optional boolean) - Analyze topic patterns (default: true).
Executes natural language queries using Logseq's DataScript capabilities. Parameters: request (string) - Natural language description of what you want to find, includeQuery (optional boolean) - Include the generated Datalog query in results, advanced (optional boolean) - Use advanced analysis features.
Uses AI to analyze your graph and suggest interesting connections. Parameters: minConfidence (optional number) - Minimum confidence score for suggestions (0-1, default: 0.6), maxSuggestions (optional number) - Maximum number of suggestions to return (default: 10), focusArea (optional string) - Topic or area to focus suggestions around.
