"A GraphQL server for MCP (Model-Controller-Presentation) architecture" matching MCP servers:

Provides architecture design expertise to AI coding agents, analyzing requirements, selecting architecture patterns, generating concrete designs, and evaluating quality attributes.

MCP server that exposes GraphQL operations as typed tools for AI models, with schema exploration, validation, execution, hot reload, OAuth, prompts, MCP Apps widgets, and OpenTelemetry support.

A Model Context Protocol server that enables LLMs to interact with GraphQL APIs by providing schema introspection and query execution capabilities.

MCP server for Twenty CRM that enables AI assistants to interact with the CRM via GraphQL, including schema inspection and query execution.

An MCP server for controlling KR-series relay controllers via serial, TCP, or UDP, featuring auto-discovery, relay control, and advanced PLC capabilities.

Automatically discovers and exposes any GraphQL API as MCP tools with zero configuration.

Indexes GraphQL schemas using embeddings to enable semantic search of types and fields for fast lookup. It allows LLMs to discover relevant schema signatures and execute queries against live GraphQL endpoints.

Analyzes GitHub and local repositories to automatically generate visual architectural diagrams such as dependency graphs, class diagrams, and data flow diagrams.

A Model Context Protocol server that enables LLMs to interact with GraphQL APIs by providing schema introspection and query execution capabilities.

Converts a GraphQL schema into MCP tools, allowing AI to discover and call GraphQL queries and mutations via natural language.

An MCP server that seats multiple LLMs as a council, letting your assistant query them in parallel or in sequence, relay answers for cross-critique, and merge conclusions within one conversation.

Converts natural language queries into valid GraphQL queries and executes them against GraphQL APIs. Includes schema introspection, query validation, execution with authentication, and query history tracking.

Provides AI agents with a toolset to query model inventories, trace dependencies, and analyze the impact of changes across machine learning models and data pipelines.

MCP server for connecting to Microsoft Fabric and Power BI semantic models, enabling workspace browsing, dataset management, TMSL retrieval, DAX queries, model creation/editing, and includes a Best Practice Analyzer with 71 rules.

Enables inspecting ONNX models, probing the deployment environment, and benchmarking inference latency and FPS either locally or on remote SSH targets such as Linux workstations and Jetson devices. Benchmark results are validated against FPS, P95 latency and model-size constraints to produce PASS/FAIL deployment gates.

One MCP server that routes to 12+ AI providers for text, image, and video generation, with smart task delegation, web search, and model comparison—all from the terminal.

An MCP server that turns the Hugging Face Hub into a conversational model picker with a tool-use eval harness to prove the agent actually uses it correctly.

Routes questions to a council of AI models (local and cloud) and synthesizes their answers in five configurable modes: individual, categorized, deconflicted, pooled, and dialectic.

Enables agents to query governed metrics through MCP, including describing metrics, running deterministic SQL against a warehouse, explaining join path preferences, and searching semantically ambiguous terms.

An MCP server that enables AI agents to pause and request human approval or information via Slack, Telegram, or macOS dialogs before proceeding with actions.