"IBM MCP Context Forge - Model Context Protocol Gateway Tool" matching MCP servers:

Unified MCP orchestration layer that consolidates multiple MCPs into a single interface with semantic tool discovery, code-mode execution, scheduling, and intelligent caching to reduce token usage by 97% and eliminate choice paralysis.

MCP server connecting Claude/Cursor to Codex CLI, enabling code analysis via @ file references, multi-turn conversations, sandboxed edits, and structured change mode.

Enables LLMs to interact with the AT Protocol ecosystem, including Bluesky, through natural language. Supports public data access without authentication and full write operations with authentication.

Relays error logs from other MCP servers when an LLM call fails and the returned error message is unclear, helping the model handle errors more intelligently.

A TypeScript-based server that enables programmatic management of pseudo-terminal sessions. It allows users to spawn, control, and interact with terminal processes in real-time through the Model Context Protocol.

Model Context Protocol (MCP) server for GitLab — exposes 1006 GitLab REST & GraphQL API operations as MCP tools (42 meta-tools / 57 enterprise), 24 resources, 38 prompts, and 17 completion types for AI assistants. Written in Go, single static binary, stdio and HTTP transport.

Enables AI agents to access and utilize GovBR Design System documentation, including component details, accessibility guidance, and search functionality via Model Context Protocol.

Provides enterprise architecture knowledge tools that ground agents in curated patterns, enabling translation of messy enterprise asks into realistic architecture recommendations, platform selection, risk checks, and brand context retrieval.

Provides a Model Context Protocol server with tools for knowledge base search, retrieval, and addition, plus system time, resources, and prompts. Supports stdio and Streamable HTTP transports for local and shared deployments.

A bridge between AI assistants and the Paradex perpetual futures trading platform for managing accounts, vaults, and orders. It enables users to retrieve real-time market data, monitor positions, and execute trading strategies through the Model Context Protocol.

Read-only MCP server for Pear Protocol that gives Claude access to markets, pair ratios, positions, orders, trade history, and portfolio.

A Model Context Protocol server for the EuroDNS User API — domains, DNS zones, contacts, subscriptions, SSL, invoices and orders.

A simple MCP server that provides a basic greeting tool and serves as a starter template for AWS Lambda deployment. Demonstrates how to build and deploy MCP servers with both local development and cloud deployment capabilities.

An MCP server that lets agents inspect, operate, and author Microsoft Power Automate cloud flows from a CLI/agent context.

Exposes Cursor-style skill packs (SKILL.md trees) via MCP resources, tools, and prompts, enabling any MCP client to list, get, search skills, and retrieve skill context.

A production-grade TypeScript starter for building Model Context Protocol servers, supporting stdio and Streamable HTTP transports with modular tools, resources, and prompts.

A smart AniList integration for the Model Context Protocol that provides AI assistants with tools for searching media, managing watchlists, and analyzing user anime or manga tastes. It goes beyond basic API calls by offering personalized recommendations, taste comparisons, and natural language profile summaries.

An MCP server that fetches web pages and extracts clean, AI-friendly Markdown content using Mozilla Readability. It provides secure web access for LLMs with built-in SSRF protection and automated content cleaning for improved context retrieval and summarization.

DevEyes is a Model Context Protocol (MCP) server that captures screenshots from your local development environment and automatically optimizes them for LLM consumption.

A communication framework that enables multiple AI agents to collaborate through asynchronous messaging, agent registration, and discovery. It facilitates complex task coordination and real-time discussion across distributed agent workflows using the Model Context Protocol.