Enables building zero-dependency Model Context Protocol servers over the Streamable HTTP transport, exposing typed tools, resources and URI templates, prompts, background tasks, and OAuth-protected endpoints. It can be mounted into FastAPI, Starlette, Flask, Django or any ASGI/WSGI app, or run standalone on the Python standard library alone.

Enables a model to write short Python programs that call a wrapped MCP server's tools as async functions, rather than invoking them one at a time. The program runs in a locked-down Docker sandbox, and every tool call passes through a host-side bridge that enforces an allowlist, schema-validated arguments, call budgets, timeouts and output caps.

Enables AI agents to list and compare LLM API prices per million tokens, rank the cheapest models by context and keyword, look up GPU rental rates per hour by provider, and estimate self-hosting cost per million tokens against API pricing. Pricing data comes from OpenRouter's public models endpoint plus a dated GPU price CSV, with source URLs and explicit notes when data is missing.

Enables AI assistants to query and safely update an Odoo database through well-documented MCP tools, with read-only mode by default, model allowlists, and Odoo access rights enforced.

Enables triaging incoming messages by classifying them into a small bounded set of action categories with a fast model, then routing each one to dismiss noise, send notifications for action items, or optionally auto-register calendar events. Users bring their own source, notifier, and calendar through small adapter interfaces, with verdicts and state kept in local SQLite storage.

Enables agents to observe a desktop and perform mouse and keyboard actions through ESP32-based BLE or USB HID hardware, with local action translation and no second model in the MCP path.

Enables MCP clients to discover NVIDIA, AMD, and Intel GPUs, monitor utilization, memory, temperature, power, clocks, and processes, retain bounded local history, and estimate whether AI models fit available VRAM before loading them.

Enables AI assistants to run local Radiance lighting and daylighting simulations on user-owned models, including annual daylight, compliance metrics, renders, glare analysis and electric lighting studies, with reproducible exported scripts.

Enables MCP clients to generate images, videos, and Seedance clips through the PowerTokens official REST API, including model and pricing discovery, cost estimation, asset uploads for first/last-frame references, and automatic polling and downloading of results.

Enables organizing personal contacts into concentric social layers, estimating warmth decay via an exponential half-life model, and scheduling mindful reconnection touchpoints within a weekly cognitive bandwidth.

Enables computing composite glycemic load for multi-ingredient meals, modeling protein and fat attenuation of glucose spikes, and forecasting post-prandial fatigue and stable focus hours to guide meal and task scheduling.

Enables users to aggregate meal glycemic index/load, model protein and fat buffering, forecast post-prandial cognitive crash risk and focus hours, and receive macronutrient stabilization recommendations.

Enables forecasting of 90-minute ultradian rhythm phases, alertness peaks and dips, and restorative nap windows through two-process sleep-wakefulness modeling.

Enables forecasting of ultradian alertness peaks and troughs, modeling homeostatic sleep pressure against circadian drive to prescribe restorative nap durations that avoid sleep inertia.

Enables computing physiologically adaptive focus durations and personalized micro-break prescriptions by modeling exponential mental fatigue and Yerkes-Dodson arousal for sustainable work-rest cycles.

Enables deterministic execution, cryptographic security, and game-theoretic optimization through the Model Context Protocol, returning deterministic JSON tool results for agent telemetry and task inputs.

Enables agents to use ACT-R spreading activation memory, semantic association graphs, and automated memory consolidation via the Model Context Protocol.

Enables local synchronization of Garmin activity and health data using a personal API key, then lets MCP-connected AI clients analyze training readiness and recovery with cited models and research. Supports viewing records, sleep/HRV, stress, Body Battery, and generating pre-run recommendations without hosting accounts or personal data.

Enables natural-language control of Siemens NX 12 for 3D modeling, 2D drafting, tolerance annotation, process planning, read-back verification, and PDF export through a persistent NXOpen bridge.

Overture is an open-source, locally running web interface delivered as an MCP (Model Context Protocol) server that visually maps out the execution plan of any AI coding agent as an interactive flowchart/graph before the agent begins writing code.

Enables coding agents to perform semantic Python AST diffing across git boundaries, detect breaking changes, and generate concise PR triage summaries for reviewers via the Model Context Protocol.

A model context protocol server to work with JetBrains IDEs: IntelliJ, PyCharm, WebStorm, etc. Also, works with Android Studio

This is a 12306 ticket search server based on the Model Context Protocol (MCP).

Unreal Engine plugin for LLM/GenAI models & MCP UE5 server. OpenAI GPT-5, Deepseek R1, Claude Opus/Sonnet, Gemini 3, Grok 4, Alibaba Qwen, Kimi, ElevenLabs TTS, Inworld, OpenRouter, Groq, GLM, Ollama, Local, Meshy, Tripo, Hunyuan3D, Rodin, fal, Dashscope, Seedream. NPC AI, agentic, chat, 3D gen, TTS, multimodal, image gen. UnrealMCP/UnrealClaude