"Understanding Inference Models" matching MCP servers:

A minimal MCP server that exposes Gemini's web and multimodal understanding (video, audio, document, image) through five dedicated tools.

An MCP server providing vision understanding tools (image QA, OCR, video and document understanding) via OpenAI-compatible endpoints, defaulting to Zhipu GLM vision models.

Enables searching, comparing, and inspecting AI models by pricing, context window, and capabilities via the models.dev catalog.

Provides AI vision analysis via OpenRouter, enabling image understanding from local paths or URLs. Supports OCR, error diagnosis, and chart/UI analysis using Gemini models.

Enables image analysis and understanding using Vision Language Models through OpenAI-compatible APIs. Supports analyzing images from URLs or local files with custom prompts.

Provides image understanding capabilities by analyzing single or multiple images (local files, URLs, or base64) via MiniMax VL API, complementing text-only models.

Enables image understanding using Doubao vision models via MCP, supporting local file paths and URLs with customizable prompts.

An MCP server that uses Google's Gemini API to analyze videos and convert them to text descriptions that Claude Code can understand and act upon.

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.

A server that provides rich UI context and interaction capabilities to AI models, enabling deep understanding of user interfaces through visual analysis and precise interaction via Model Context Protocol.

Provides deterministic tools for understanding, transforming, and verifying structured data via MCP, enabling rule inference from examples and verification of transformed records.

Exposes locally hosted MLX models as MCP tools for Claude Desktop and Codex, with optional SearXNG search augmentation for private local inference.

Pre-attestation gate for AI inference that checks compliance conditions and issues Ed25519-signed clearances before execution, refusing any inference without a valid clearance.

Enables AI agents to route chat completion requests to task-appropriate models via LiteLLM/OpenRouter, track usage and budgets, and run side-by-side eval comparisons of models based on cost, latency, and response quality.

Provides image understanding capabilities for MCP clients (e.g., Claude Code) by analyzing images using vision models from providers like Alibaba Cloud Bailian, OpenAI, or OpenRouter, returning detailed descriptions in Markdown format.

Hands local video files to Gemini's native video understanding for detailed, timestamped descriptions, and also supports image/media viewing with frame extraction.

Enables text-only language models to understand images by forwarding image and prompt requests to vision model backends via MCP, returning descriptive text. Supports multiple OpenAI-compatible providers with task routing and safety checks.

Hardened MCP bridge to the full Ollama ecosystem — local and cloud models. 6 tools covering health, model management, chat, and generation with SSRF mitigation, singleton HTTP client, and structured error handling. Two deps, one file.

Provides read-only access to live Bay Area transit data, including routes, stops, real-time departures, vehicle positions, and service alerts, for use by large language models.

An MCP server that uses Xiaomi MiMo v2.5 multimodal model to provide image recognition capabilities (description, multi-image analysis, OCR, and image info validation) for text-only main models like deepseek-v4-flash, accepting local paths, URLs, file://, and base64 data inputs.