Query the project mind map with enhanced semantic search, context-aware relevance scoring, and intelligent routing. Supports file path queries, function/class name searches, semantic concept matching, and multi-modal confidence fusion.

Update the mind map with new knowledge from completed tasks, errors encountered, or solutions found

Get contextual information about the current project state and previous interactions

Get intelligent suggestions for where to look or what to explore based on a task description

Perform a fresh scan of the project to update the mind map with current file structure. Supports multiple project contexts via project_root parameter or MCP_PROJECT_ROOT environment variable.

Get statistics about the current mind map and project analysis

Analyze code patterns and predict potential errors before they occur based on historical data and code analysis

Get intelligent fix suggestions for errors based on historical data, error patterns, and contextual analysis

Analyze the project architecture and detect design patterns, architectural styles, and structural insights

Get performance statistics and identify slow operations in the mind map system

Execute advanced Cypher-like graph queries with complex filtering, aggregation, and pattern matching

Query code evolution over time, track changes, and analyze trends

Execute aggregate queries for project insights, statistics, and analytics

Generate comprehensive project insights and analytics with actionable recommendations

Save a query template for reuse with parameters

Execute a previously saved query template with optional parameter overrides

Detect cross-language dependencies and communication patterns in polyglot projects

Analyze project structure for multi-language patterns, architecture style, and language interoperability

Generate intelligent refactoring suggestions for multi-language codebases

Detect available development tools across all languages in the project

Execute a specific development tool and return results with issue analysis

Get intelligent recommendations for missing or beneficial development tools

Run multiple development tools and aggregate results for comprehensive analysis

Comprehensive framework detection across web, mobile, desktop, game, ML/AI, and cloud categories

Get intelligent recommendations based on detected frameworks and project patterns

Get query cache statistics including hit rate, memory usage, and performance metrics

Clear the query cache to free memory and force fresh results

Get brain-inspired inhibitory learning statistics including pattern counts, strength distribution, and learning effectiveness

Get Hebbian learning statistics showing associative connections, co-activation patterns, and neural-inspired relationship strengthening

Get multi-modal confidence fusion statistics showing evidence combination, modality reliability, and advanced confidence calibration

Get hierarchical context system statistics showing multi-level context awareness, context distribution, and brain-inspired context management

Get current context summary across all hierarchical levels (immediate, session, project, domain) with most relevant context items

Get brain-inspired attention system statistics showing attention allocation, modality distribution, focus efficiency, and cognitive load metrics

Dynamically allocate attention to specific nodes based on context and cognitive load theory

Update attention system from user activity (file access, edits, errors, successes) for dynamic attention learning

Get bi-temporal knowledge model statistics showing valid time vs transaction time tracking, context windows, and temporal relationship analysis

Create a temporal context window for grouping related changes and relationships within a specific time period

Query relationships with temporal constraints - valid time, transaction time, and context windows

Create a temporal snapshot of the current knowledge state for analysis and comparison

Mark a relationship as no longer valid (set valid time end)

Get pattern prediction engine statistics showing emerging patterns, predictions, and trend analysis

Get specific pattern predictions with probability, timeframe, and confidence analysis

Get patterns that are emerging but not yet fully established, with emergence stage and confidence

Predict when a specific pattern will emerge with detailed analysis and alternatives

Trigger immediate pattern analysis and prediction generation based on current project state

Analyze function call patterns, method invocations, and code relationships within TypeScript/JavaScript files. Creates a comprehensive call graph with complexity metrics, recursion detection, and cross-file relationship mapping.

Update ignore patterns for file scanning with support for .gitignore and .mindmapignore files

Test ignore patterns against project files to see what would be ignored

Get statistics about currently active ignore patterns and their effectiveness

Get comprehensive setup instructions and configuration guidance for integrating Mind Map MCP with Claude Code

Analyze all documentation files in the project including markdown, restructured text, and configuration files. Provides comprehensive documentation analysis with brain-inspired relationship learning.

Analyze a specific document file for structure, links, code relationships, and documentation quality

Get comprehensive statistics about project documentation including word counts, link analysis, and coverage metrics

Get intelligent insights about documentation quality, coverage gaps, broken links, and improvement recommendations

Get relationships between documentation and code files, including implementation mappings and cross-references

Detect API endpoints, services, and schemas across all supported languages. Identifies REST APIs, GraphQL schemas, gRPC services, WebSocket endpoints, and WebAssembly modules with framework-specific pattern recognition.

Analyze test coverage by mapping test files to their corresponding implementation files. Identifies test-to-code relationships through naming patterns, imports, and code references with 95% accuracy target.

Analyze configuration file relationships and dependencies across the project. Tracks package.json, tsconfig.json, .env files, and other configuration files to understand project setup and dependencies.

Analyze error handling patterns and exception propagation flows across the codebase. Identifies unhandled errors, error handling coverage, and vulnerable areas for improved error resilience.