Provides personalized Data Engineering learning updates by fetching recent news about DE concepts, patterns, and technologies, while tracking user knowledge to present only new information relevant to their learning journey.
A development platform that helps AI developers optimize prompts through intelligent context management, providing tools for analysis, optimization, and template management to reduce costs and improve AI response quality.
An MCP tool enabling structured thinking and analysis across multiple AI platforms through branch management, semantic analysis, and cognitive enhancement.
A Model Context Protocol server that helps users create, validate, manage, and optimize prompts using the RISEN framework (Role, Instructions, Steps, Expectations, Narrowing).
A multi-tool AI assistant system that uses Model Context Protocol to connect language models with various tools, including math calculations and weather information.
A meta-MCP server that acts as a universal gateway, allowing users to discover and execute tools from thousands of other MCP servers through semantic search. It dynamically loads servers on demand and provides standardized functions for searching, discovering, and running tools across the entire MCP ecosystem.
Provides a standardized protocol for tool invocation, enabling an AI system to search the web, retrieve information, and provide relevant answers through integration with LangChain, RAG, and Ollama.
Provides structured dealer brand data including inventory, promotions, reviews, and dealer profile via MCP tools, enabling LLMs to answer accurate brand-related queries.
A Model Context Protocol server that enables AI agents to query a Graphiti knowledge graph and pgvector document store for evidence-backed responses via hybrid search and RAG.
A Compact Knowledge Graph MCP server providing pre-structured domain knowledge as a routing layer for agent stacks, enabling efficient structural queries (e.g., prerequisites, dependency chains) without hallucinations.
PhysBound is a specialized "Physics Linter" for AI that deterministically validates RF and thermodynamic claims against hard physical limits, preventing hallucinations in engineering workflows.
Knot is a semantic and structural codebase indexer designed for AI coding agents and developers navigating large projects. It combines vector search and graph traversal to find code by meaning, analyze impact via reverse dependencies, and explore file architectures.
Exposes an internal engineering knowledge base to AI assistants, allowing users to search and retrieve standards, runbooks, and architecture decisions. It supports RAG-enhanced search, document scraping, and specialized prompts for incident investigation and code reviews.
Structural graph map of any codebase. Scans entities, relationships, and feature flows across 13 languages so LLMs navigate by structure instead of
reading everything.
Universal MCP knowledge server for LLM agents, powered by local RAG, providing domain-specific best practices and playbooks across software engineering, marketing, video editing, and other knowledge areas.
Provides AI agents with structured knowledge about 67+ generative AI models, including model recommendations, prompt formatting, parameter guidance, and validation. It acts as a prompt engineering co-pilot that helps agents use their existing tools more effectively.
An MCP server that integrates the SearXNG API for web search and URL content extraction with advanced features like pagination, caching, and proxy support.