Retrieve and organize all available tools from connected MCP servers for toolset creation. Access detailed metadata and reference tools using 'namespacedName' or 'refId' for streamlined integration.
Extract structured data or text from web pages using specific instructions. Define what information to collect from the current page for automated data extraction.
Export chat data in JSON, CSV, or Graph formats for analysis, visualization, or integration. Filter by projectPath for codebase-specific insights, generate datasets for ML, or prepare data for tools like Tableau.
Retrieve structured data from Google search results to extract information for research, analysis, or content creation. Supports country-specific searches for localized data.
Enforces disciplined programming practices by requiring AI assistants to audit their work and produce verified outputs at each phase of development, following structured workflows for refactoring, feature development, and testing.
MCP-ORTools integrates Google's OR-Tools constraint programming solver with Large Language Models through the MCP, enabling AI models to:
Submit and validate constraint models
Set model parameters
Solve constraint satisfaction and optimization problems
Retrieve and analyze solution
Make it easy for agents to build their context about your projects over time
The server provides a set of tools to help agents accumulate knowledge about a project over time in a structured way.