"Overview of HTTP (HyperText Transfer Protocol)" matching MCP servers:

Enables AI assistants to autonomously perform site reliability engineering including monitoring, root-cause analysis, impact assessment, and remediation with cryptographic zero-trust enforcement.

104 high quality skill packs across 20+ tech stacks. 1,284 curated chunks. 104 validated discoveries. Every piece reviewed, cross-validated, and myth-busted.

A Model Context Protocol server built with FastMCP that enables dynamic tool loading and configuration from individual Python files. It provides a flexible framework for automatically discovering, testing, and running tools via Stdio or HTTP transport modes.

Local-first MCP server for controlling Google Colab as a development, shell, file, and training runtime, with tools for notebook editing, GPU acceleration, and file transfer.

MCP server that parses web pages into clean markdown via Crawl4AI's HTTP API, exposing parse_page and health-check tools with configurable proxy and timeout.

Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.

Connects AI agents to ROS 2 robots via rosbridge, enabling observation, inspection, and control of robot topics, services, and actions through natural language.

Provides access to Atomic Red Team tests, enabling search, validation, and execution of atomic tests via natural language.

Code-mode MCP server (docs_search + execute_code two-tool surface) backed by a unified capability manifest across three sandbox kernels (in-process node:vm, WASM via QuickJS / Pyodide / Wasmtime, and remote microVM via E2B / Cloudflare Sandbox). At N=30 tools the bootstrap-context cost drops to 13.6% of direct tool-use. Apache-2.0.

A minimal MCP server that enables HTTP requests with any method, headers, and body types, supporting large responses through chunked transfers with disk-backed caching.

Enables AI assistants to interact with Intervals.icu fitness tracking and wellness data, allowing users to fetch, filter, and group activities or health metrics. It provides structured summaries of workouts and physical well-being through natural language queries.

Enables management of Kylas CRM lead operations, including creating leads, searching and filtering records, and resolving user, product, or pipeline IDs. It provides specialized tools for monitoring idle leads and accessing lead schema instructions through natural language.

Enables local forensic analysis of files by orchestrating system binaries (file, exiftool, strings, Volatility) via safe subprocess execution.

A Model Context Protocol server built with FastMCP that provides tools for retrieving the current local date and time. It allows LLMs to access precise temporal information directly from the host environment.

Bridges a local AI agent to a Colab session in the browser, enabling code execution and file operations through the Model Context Protocol.

Enables multi-LLM deliberation via a council of panel members, judges responses for consensus and contradictions, and returns analysis to the calling model.

COS-MCP is an MCP server that provides AI-powered organizational continuity planning. It maintains a knowledge graph of employees, systems, projects, and relationships, and exposes tools, resources, and prompts for knowledge graph visualization, risk analysis, employee transition planning, and organizational knowledge base queries.

A lightweight MCP server providing comprehensive date, time, and day-of-week information. It supports relative time calculations, timezone conversions, and detailed calendar metadata like week numbers and quarters.

An MCP server for Tendem that enables users to complete tasks using a hybrid of AI and human agents. It allows for seamless task delegation and management within MCP-compatible clients.

MCP server for AI-merge of team dev configurations, allowing the IDE's LLM to intelligently merge team configs with personal configs.