"Kit" matching MCP servers:

All-in-one 24-tool MCP runtime and 180-skill library providing protocol-level C4 workflow gates, cognitive reasoning engines, and safe execution for AI coding agents.

Agent development tool-kit

Enables users to attach child MCP servers, run sandboxed Python, and transfer large outputs via artifacts through one authenticated Streamable HTTP endpoint exposed by tunnel to a cloud chat client.

Provides a ready-to-run stdio server scaffold that agents can launch via npx without installing anything, bundled into a single file with an example tool, strict tool-schema checks, tests, and bilingual documentation. It gives developers a consistent foundation for building, validating, and shipping new MCP servers that agent-kit can execute directly.

MCP server for managing Git operations on local repositories, allowing users to list repositories, get and create tags, list commits, push tags, and refresh repositories through a standardized interface.

The Git MCP Server allows AI assistants to perform enhanced Git operations via the Model Context Protocol, supporting core Git functions, branch and tag management, GitHub integration, and more.

Enables on-demand generation of TypeScript tools using an LLM with human-in-the-loop approval and safe sandboxed execution. It allows users to create and persist custom functionality through natural language requests.

Gives Claude read-only access to a Zerodha Kite Connect account and Indian market data by running Claude-authored Python scripts against the zapkite library in an isolated subprocess, returning only printed output so large datasets never enter context. It also hosts scheduled market watchers that email alerts when conditions turn true, plus a web app for Zerodha login and watcher management.

An MCP server for integrating with Zerodha Kite API that provides Claude with tools to interact with your Kite trading account, enabling portfolio management, market data access, and order execution.

Turns any YAML manifest into a fully-functional MCP server without hosting infrastructure, enabling custom tools, resources, and prompts via declarative configuration.

Implements a Model Context Protocol server that connects with Zerodha Kite API, allowing users to buy/sell stocks and retrieve holdings and positions information.

Enables AI assistants to operate directly inside a running Unity Editor project, using built-in tools for scene creation, script generation, play mode automation, input simulation, and performance analysis.

A starter kit for quickly building Model Context Protocol (MCP) servers using the TypeScript SDK. It includes a structured project setup with pre-configured examples for implementing tools, resources, and Zod-based schema validation.

A FastMCP server that dynamically loads tools from Python/YAML file pairs, acting as a stand-in for the Tools Framework in agentic-assembly-framework.

An MCP server that enables Large Language Models or other MCP clients to interact with Ansys/AGI STK (Systems Tool Kit), allowing users to control STK Desktop simulations programmatically or via natural language.

Enables MCP clients to manage a workspace through file reading, writing, editing, searching, Bash/Python execution, and job control, with optional desktop GUI and Cloudflare Tunnel access.

Provides AI coding assistants with a persistent Macaulay2 1.26 session, letting them run computations such as Groebner bases, free resolutions, Betti tables, primary decompositions, and Hilbert polynomials while preserving state across calls.

A comprehensive Model Context Protocol server providing access to 70+ IT tools for developers and system administrators, including encoding/decoding, text manipulation, hashing, and network utilities.

Enables zero-install Macaulay2 computations from JupyterLab in a browser, including Groebner bases, resolutions, Betti tables, and package loading via the Model Context Protocol.

A FastMCP server exposing 22 tools for calendar, to-do, notes, web search, math, scratchpad, task queue, and sandboxed code execution, designed for safe RL training with structured outputs and FastMCP transforms.