"Understanding Browser Usage and Functionality" matching MCP servers:

A Model Context Protocol server that enables LLMs to interact with VS Code's Simple Browser, allowing for browser control, JavaScript execution, console monitoring, and navigation through natural language.

A simple server that acts as a Master Control Program (MCP) for unified interaction with OpenAI and Anthropic (Claude) AI models through a single API endpoint.

A production-ready foundation template for building Model Context Protocol (MCP) servers with FastAPI, featuring modular tools, comprehensive testing, and OpenShift deployment configurations. Includes automated transformation scripts to create custom domain-specific MCP servers.

An MCP server that implements Claude Code-like functionality, allowing the AI to analyze codebases, modify files, execute commands, and manage projects through direct file system interactions.

Provides a headless session runtime for reactive compute graphs, enabling MCP-driven cell operations without a DOM or browser.

Enables execution of TypeScript code to call MCP tools instead of direct tool calls, reducing token usage by up to 98% while orchestrating complex multi-tool workflows through secure sandboxed code execution.

A simple and extendable MCP server that currently provides basic addition functionality and can be easily extended by defining new tools with docstrings.

Orchestrates multiple MCP servers through a Deno sandbox, reducing token usage by 99.7% by processing tool calls and returning only compact results.

A lightweight Model Context Protocol (MCP) orchestrator designed for efficiency at scale. It features TOON compression (reducing token usage by 30-90%) and Lazy Loading, making it the ideal solution for complex, multi-tool agentic workflows.

An MCP server implementing AI-user confirmation protocols, providing tools for LLMs to seek user confirmation when uncertain through yes/no questions, action confirmations, intent clarification, understanding verification, and satisfaction ratings.

A local MCP server that exposes Bazel build system functionality to AI agents, allowing them to build, test, query, and manage Bazel projects through natural language even in environments where Bazel can't be directly accessed.

An MCP server that provides code review functionality using OpenAI, Google, and Anthropic models, serving as a "second opinion" tool that works with any MCP client.

A Model Context Protocol implementation that enables LLMs to execute complex, multi-step workflows combining tool usage with cognitive reasoning, providing structured, reusable paths through tasks with advanced control flow.

Enables automatic generation of complete Maven projects (applications, plugins, libraries) with intelligent package detection, customizable file structure, and integrated ZIP export functionality.

A Model Context Protocol server that enables LLMs to autonomously perform symbolic mathematics and computer algebra through SymPy's functionality for manipulating mathematical expressions and equations.

AI code generation service for KPC component library that solves hallucination problems by providing accurate component APIs, validation rules, and usage examples.

MCP server for agentic interaction with the Lean theorem prover via LSP, providing tools for understanding, analyzing, and interacting with Lean projects.

Extracts minimal, relevant code context from multiple programming languages while analyzing diffs and optimizing imports to reduce token usage for AI assistants. Supports TypeScript/JavaScript, Python, Go, and Rust with token-aware caching.

Exposes TypeScript Language Server Protocol functionality to AI agents, enabling them to query types at specific positions, find definitions and references, get diagnostics, run type tests, and type-check inline code just like in an IDE.

Exposes Arrakis VM sandbox functionality to LLMs, enabling sandbox management and command execution.