multiluca2020/visum-thinker-mcp-server
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Visum Thinker MCP Server is a Model Context Protocol server designed to enhance AI assistants' problem-solving and analytical capabilities through structured sequential thinking.
sequential_thinking
Main tool for step-by-step reasoning process.
load_pdf
Load a PDF file to provide context for analysis.
analyze_pdf_section
Analyze specific sections of the loaded PDF.
reset_thinking
Clears the current thinking state to start fresh.
get_thinking_summary
Returns a summary of the current thinking session including PDF context if loaded.
export_knowledge
Export the current thinking state and PDF knowledge to a file.
import_knowledge
Import thinking state and PDF knowledge from an exported file.
Visum Thinker MCP Server
A Model Context Protocol (MCP) server that provides structured sequential thinking capabilities for problem-solving and analysis. This server enables AI assistants to break down complex problems into manageable steps, revise thoughts, and explore alternative reasoning paths.
Features
- Step-by-step reasoning: Break down complex problems into sequential thoughts
- Dynamic revision: Revise and refine thoughts as understanding deepens
- Branching logic: Branch into alternative reasoning paths
- Adaptive planning: Adjust the total number of thoughts dynamically
- State management: Maintain thinking context across multiple tool calls
- Progress tracking: Monitor completion status and thought progression
- PDF Analysis: Load and analyze PDF documents for problem-solving context
- Content Search: Find relevant sections in PDFs based on queries and search terms
- Persistent Storage: Auto-save state to disk, survive server restarts
- Knowledge Transfer: Export/import thinking sessions between servers
- š Visum Integration: Complete PTV Visum COM API integration for transportation planning
- Smart Path Learning: Automatically discovers and remembers custom Visum installation paths
- Zero Configuration: Once set up, works seamlessly across server restarts
- Demo Mode: Full functionality testing without requiring Visum installation
- Transportation Analysis: Load models, run calculations, analyze networks and matrices
Installation
Quick Installation
# Option 1: Install from NPM
npm install -g visum-thinker-mcp-server
# Option 2: Use with npx (no installation)
npx visum-thinker-mcp-server
# Option 3: Clone from GitHub
git clone https://github.com/yourusername/visum-thinker-mcp-server.git
cd visum-thinker-mcp-server
npm install && npm run build
See for detailed setup instructions.
Prerequisites
- Node.js 16 or higher
- npm or yarn
Usage
With Claude Desktop
Add to your Claude Desktop configuration (claude_desktop_config.json
):
{
"mcpServers": {
"visum-thinker": {
"command": "node",
"args": ["/absolute/path/to/sequential_thinking/build/index.js"]
}
}
}
With VS Code
The project includes a .vscode/mcp.json
configuration file for VS Code MCP integration.
Direct Usage
npm run dev
Tools
sequential_thinking
Main tool for step-by-step reasoning process.
Parameters:
thought
(string): The current thinking stepnextThoughtNeeded
(boolean): Whether another thought step is neededthoughtNumber
(integer): Current thought numbertotalThoughts
(integer): Estimated total thoughts neededisRevision
(boolean, optional): Whether this revises previous thinkingrevisesThought
(integer, optional): Which thought is being reconsideredbranchFromThought
(integer, optional): Branching point thought numberbranchId
(string, optional): Branch identifierneedsMoreThoughts
(boolean, optional): If more thoughts are needed
load_pdf
Load a PDF file to provide context for analysis.
Parameters:
filePath
(string): Absolute path to the PDF file
analyze_pdf_section
Analyze specific sections of the loaded PDF.
Parameters:
query
(string): What to look for or analyze in the PDFstartPage
(integer, optional): Starting page number (1-based)endPage
(integer, optional): Ending page number (1-based)searchTerms
(array of strings, optional): Specific terms to search for
reset_thinking
Clears the current thinking state to start fresh.
get_thinking_summary
Returns a summary of the current thinking session including PDF context if loaded.
export_knowledge
Export the current thinking state and PDF knowledge to a file.
Parameters:
exportPath
(string): Absolute path where to save the exported knowledge file
import_knowledge
Import thinking state and PDF knowledge from an exported file.
Parameters:
importPath
(string): Absolute path to the exported knowledge file to import
š Visum Transportation Planning Tools
The server includes comprehensive PTV Visum integration with intelligent path learning:
check_visum
: Check Visum availability and learn custom installation pathsload_visum_model
: Load transportation models (.ver files)run_visum_calculation
: Execute transportation calculations and analysesget_network_statistics
: Analyze network topology and characteristicsanalyze_visum_matrices
: Examine demand and flow matricesexport_visum_results
: Export analysis results to various formats
Key Features:
- š§ Smart Path Learning: Automatically remembers custom Visum installation paths
- š Zero Setup: Works seamlessly after initial path discovery
- šÆ Demo Mode: Full testing capability without Visum installation
- š Complete Analysis: All major transportation planning workflows supported
See for detailed information about the intelligent path learning system.
š¤ GitHub Copilot Integration
The Sequential Thinking MCP Server includes comprehensive GitHub Copilot integration for enhanced AI-assisted development:
š Quick Start with Copilot
- Server Status: Ensure MCP server is running (
npm run dev
) - Open Copilot Chat:
Ctrl+Shift+I
in VS Code - Test Integration: Ask
@copilot List available MCP tools
- Start Solving:
@copilot Use sequential thinking to solve [your problem]
šÆ Copilot Capabilities
- š§ Sequential Thinking: AI-guided step-by-step problem solving
- š PDF Analysis: Intelligent document processing and analysis
- š Transportation Planning: Expert Visum integration and workflow automation
- š§ Smart Configuration: Automatic Visum path learning and persistence
- š” Context-Aware Suggestions: Code completion with domain knowledge
š¬ Example Copilot Interactions
@copilot Can you use sequential thinking to analyze this transportation network problem?
@copilot Check if Visum is available and help me load a network model
@copilot Use the PDF analysis tools to extract data from this traffic report
@copilot Create a complete workflow for transportation demand analysis
See for comprehensive setup and usage guide.
Development
Project Structure
sequential_thinking/
āāā src/
ā āāā index.ts # Main server implementation
āāā build/ # Compiled JavaScript output
āāā .vscode/
ā āāā mcp.json # VS Code MCP configuration
āāā .github/
ā āāā copilot-instructions.md
āāā package.json
āāā tsconfig.json
āāā README.md
Scripts
npm run build
: Compile TypeScript to JavaScriptnpm run dev
: Build and run the servernpm test
: Run tests (placeholder)
Debugging
The server logs to stderr for compatibility with STDIO transport. Use VS Code's debugging features or add console.error statements for debugging.
Architecture
The server maintains a global thinking state that tracks:
- All thoughts in the current session
- Current progress and estimated completion
- Revision and branching relationships
- Session completion status
Each tool call updates this state and provides formatted responses that help users follow the thinking process.
License
MIT