"LLVM" matching MCP servers:

Gives text-only LLM coding agents vision by routing images to a multimodal model and returning detailed textual descriptions. Supports local files, URLs, clipboard, base64, raw bytes, and multiple providers like OpenAI, Anthropic, and Gemini.

MCP server that completes prompts with automatic provider fallback across OpenAI, Anthropic Claude, and Google Gemini. It is rate-limit aware, retries on transient failures, and provides a transparent attempt log.

Manages brand monitoring projects, runs scans across 350+ LLMs, and analyzes results through natural language.

Atlas Cloud MCP Server enables developers to access state-of-the-art AI models for image generation, video generation, and LLMs through a unified MCP interface. Fast, scalable, and cost-efficient alternative to traditional AI providers.

An MCP server that provides local, private, synchronous access to Ollama models for prompt answering, text classification, and model listing, without any file access or command execution.

Give your AI assistant real-time LLM/VLM knowledge. Pricing, benchmarks, and recommendations — updated every hour, not every training cycle.

An MCP server that enables multiple AI models (ChatGPT, Gemini, Claude, Grok) to discuss, debate, and reach consensus via browser automation.

Enables an LLM to autonomously maintain a Markdown-based wiki with YAML frontmatter, using hybrid BM25 and local CPU vector search for fully offline retrieval without external APIs or databases.

A powerful MCP server for querying and processing large Swagger/OpenAPI JSON documents, enabling LLMs to efficiently access API documentation without loading entire files.

MCP chess runtime that lets LLMs play, analyze, and adapt strength by exposing Stockfish, human move likelihood (Maia3), and Lichess statistics, with the LLM handling strategy and the server handling computation.

An MCP server that bridges multiple LLMs (OpenAI-compatible APIs and CLI coding agents) for collaborative debugging and diverse AI perspectives.

Centralized encrypted gateway that routes requests to 11+ LLM providers (API keys and CLI subscriptions) through a single OpenAI-compatible endpoint, with MCP tools for vault operations, code search, and shared state.

Enables local chess move validation and game state management for standard and variant rules via MCP, without engine recommendations.

Enables AI coding agents to run multi-model council deliberations by concurrently querying OpenAI and DeepSeek for architectural planning and adversarial critique, then synthesizing the results into actionable implementation decisions.

Unified MCP server for querying multiple LLM providers (Gemini, OpenAI, Anthropic, etc.) with advanced routing, cost optimization, and fallback resilience.

A Model Context Protocol server that provides unified access to multiple LLM APIs including ChatGPT, Claude, and DeepSeek, allowing users to call different LLMs from MCP-compatible clients and combine their responses.

A Model Context Protocol (MCP) gateway for running Claude Code, Codex, Gemini, Grok, and Mistral (Vibe) CLIs from one MCP endpoint, with durable async jobs, session continuity, cache-aware prompting, observability, and personal-appliance setup tooling. Why developers try it: one local MCP endpoint for cross-LLM validation, multi-agent coding workflows.

Exposes the MiniMax M3 LLM API to MCP-compatible clients, enabling chat completions, text completions, tool calls, and token counting via stdio or SSE transport.

MCP server that provides a live coordination layer for AI agents, including attributable handoffs, a shared event ledger, atomic work-claiming, and advisory file leases to prevent collisions.

Provides a universal bridge to interact with any OpenAI-compatible LLM API (local or cloud), enabling model testing, benchmarking, quality evaluation, and chat operations with performance metrics.