Logseq Knowledge Graph
Summary
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.
Available Actions(11)
getAllPages
Retrieves a list of all pages in your Logseq graph.
getPage
Gets the content of a specific page. Parameters: pageName (string) - The name of the page to retrieve.
getJournalSummary
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.
createPage
Creates a new page in your Logseq graph. Parameters: pageName (string) - Name for the new page, content (optional string) - Initial content for the page.
searchPages
Searches for pages by name. Parameters: query (string) - Search query to filter pages by name.
getBacklinks
Finds all pages that reference a specific page. Parameters: pageName (string) - The page name for which to find backlinks.
analyzeGraph
Performs a comprehensive analysis of your knowledge graph. Parameters: daysThreshold (optional number) - Number of days to look back for 'recent' content (default: 30).
findKnowledgeGaps
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).
analyzeJournalPatterns
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).
smartQuery
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.
suggestConnections
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.
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