"Automated cryptocurrency trading bot using on-chain data and Hummingbot" matching MCP servers:

A composable middleware framework for building MCP server chains that enables the creation of transparent proxies to transform requests and responses. It allows users to add cross-cutting concerns like authentication, logging, and AI-driven orchestration to existing MCP servers.

Enables execution and monitoring of Cucumber.js + Playwright automated tests, including real test runs, status checks, feature discovery, and coverage analysis.

Enables Codex to trigger an animated hand on your desktop that delivers playful cartoon slaps when mistakes are detected, with severity-based slap counts, while the agent continues working.

Provides AI assistants with intelligent access to project documentation and API references through smart search, contextual rules, and Docset integration. Enables AI to understand project-specific conventions, patterns, and official framework documentation without token limits.

Unifies 21 supply chain security data sources into a single MCP server, enabling AI agents to perform comprehensive package audits, vulnerability checks, provenance verification, and risk assessment across multiple ecosystems.

A template for deploying an MCP server on Vercel, with example tools like roll_dice and get_weather.

Enables MCP-compatible agents like ChatGPT and Claude to securely access a Grok Bot workstation's folder-scoped files, shell, and Git tools over HTTPS+OAuth or local stdio, and to orchestrate specialized Grok Bot agents via a message bridge.

MCP server deployed on EdgeOne Pages, providing a Streamable HTTP MCP server for intelligent chat applications with tool capabilities like generating webpages.

A comprehensive Model Context Protocol (MCP) server implementing the latest MCP specification with tools, resources, prompts, and enhanced sampling capabilities that features HackerNews and GitHub API integrations for AI-powered analysis.

Relays a result screenshot to Slack so you can review a coding agent's output without opening the app.

Chain of Draft Server is a powerful AI-driven tool that helps developers make better decisions through systematic, iterative refinement of thoughts and designs. It integrates seamlessly with popular AI agents and provides a structured approach to reasoning, API design, architecture decisions, code r

MCP server for Discord bot API that exposes five tools to search, inspect, and call stable Discord HTTP endpoints using bot-token authentication, with automatic schema refresh and strict safety filtering.

Scrapes the official Telegram Bot API documentation and provides tools for querying methods, types, fields, and relationships.

Implements the Chain of Draft reasoning approach to generate minimalistic intermediate reasoning outputs while solving tasks, significantly reducing token usage while maintaining accuracy.

MCP server generated from an OpenAPI Specification, exposing tools via HTTP. It allows clients to invoke API operations using JSON-RPC 2.0 requests.

A deployment template for running Model Context Protocol servers as Vercel Functions. It provides a foundation for developers to build and host custom tools, prompts, and resources with optimized execution for MCP client integration.

Enables auditing package.json files for real npm supply-chain attack mechanisms — typosquatted dependency names, malicious preinstall/install/postinstall scripts that pipe downloads into a shell or decode base64 payloads, and unpinned versions — plus live npm registry lookups that flag nonexistent, brand-new, deprecated, or typosquatted packages. It exposes dedicated tools for full manifest audits and single-name typosquat checks.

Enables AI assistants to interact with the Telegram Bot API, supporting messaging, user management, and bot configuration with intelligent message splitting and error handling.

A humorous MCP server that always advises against shipping on Friday, returning a catastrophic risk level and a rotating reason.

Transforms prompts into Chain of Draft (CoD) or Chain of Thought (CoT) format to enhance LLM reasoning quality while reducing token usage by up to 92.4%, supporting multiple LLM providers including Claude, GPT, Ollama, and local models.