"A local AI setup with LM Studio and a secure browser for real-time AI searches" matching MCP servers:

A Model Context Protocol (MCP) server that exposes the EasyDeploy public REST API as tools for Claude, Cursor, Claude Code, and other MCP clients.

Enables discovery of public API operations, scoped read-only diagnostics for domains, DNS, and mail, and a controlled write lifecycle that requires independent human approval before any mutation.

Enables AI assistants to deploy and manage hosted apps from git repos, read logs, add Postgres databases and domains, manage API keys and budgets, and send requests to 200+ AI models. Connects over remote Streamable HTTP with OAuth sign-in, so users need no API keys, installs, or local server.

MCP server that lets an AI agent manage Proxmox VE in natural language, with policy-driven security, read-only mode, two-step confirmations, and audit logging.

Intelligent AI routing and integration platform for seamless provider switching

An MCP server that gives an agent a remote browser:

An MCP server that enables running commands against a ServiceNow instance via its REST APIs, including Table, Aggregate, Attachment, Import Set, Batch, CMDB, Service Catalog, Change Management, and Knowledge APIs.

Provides Vertex AI Search for Commerce product search as a tool, enabling AI agents to search product catalogs using natural language queries.

Enables AI agents to access Cloudflare Workers AI for serverless LLM chat completions, text embeddings, and image generation via MCP tools.

Implementation of Model Context Protocol (MCP) server that provides tools for accessing Google Cloud's Vertex AI Gemini models, supporting features like web search grounding and direct knowledge answering for coding assistance and general queries.

A community MCP server for Cisco Secure Access that exposes the Secure Access REST API to AI clients as a curated catalog of tools for Admin, Deployments, Investigate, Policies, and Reports.

Deterministic AI data-center design tools for sizing, validation, and conceptual rack/site layouts. Supports NVIDIA Hopper, Blackwell, and Rubin profiles. Calculations require a registered AIDC API key; results preserve warnings, RFIs, and pending validations.

Provisions Google Analytics 4 for local AI/web projects by creating properties and web data streams, injecting gtag snippets, and saving configuration.

A Model Context Protocol server for Microsoft SQL Server and Azure SQL Database with permission-based access modes (read-only, DML, full) and security features like SQL classification and connection locking.

Enables MCP-compatible clients to search approved local Markdown runbooks, retrieve selected local host health details, and get bounded Kubernetes pod-status summaries for allowlisted clusters and namespaces.

Enables AI assistants to manage Amazon SageMaker AI resources including endpoints, jobs, pipelines, MLflow tracking servers, domains, models, model cards, and apps.

Local MCP server (stdio) exposing the entire Hetzner Cloud API as 201 typed tools, read and write

Enables AI-powered image and video analysis using Google Gemini and Vertex AI models. Supports analyzing single or multiple images, detecting objects with bounding boxes, and video content analysis through natural language prompts.

Enables comprehensive integration with Azure AI services including OpenAI, Cognitive Services, Computer Vision, and Face API through a mission-critical MCP server. Provides enterprise-grade reliability with high availability, observability, chaos engineering, and secure multi-region deployment capabilities.

Enables AI agents to discover and invoke backend tools over MCP JSON-RPC while enforcing 3-legged OAuth 2.0 identity propagation, role-based access control, and protocol transcoding to REST APIs.

Enables integration with Google Cloud Vertex AI Search for enterprise search capabilities through a stdio-based MCP server.

Enables managing Vercel projects, deployments, build logs, domains, and environment variables through natural language in Microsoft Copilot Studio, using streamable HTTP with API key authentication.

Exposes SAP AI Core APIs as MCP tools, enabling AI assistants to manage AI Core lifecycle and administration through natural language.

Enables MCP clients to browse hosted devices, upload models and datasets, compile and quantize models, run inference, read performance profiles, and download compiled outputs and logs through the Core API.

Enables AI assistants to interact with Databricks workspaces, running SQL queries, managing jobs, and exploring schemas via the Model Context Protocol.

Enables interaction with Azure AI Agent Service by automatically discovering agents and creating MCP tools for querying and managing agent workflows.

Enables AI assistants to query BigQuery read-only via MCP with enforced dataset boundaries, result limits, and audit labels.

Enables interaction with Azure AI Foundry services for model exploration, deployment, and performance evaluation. It provides tools for managing knowledge bases via AI Search Service, executing fine-tuning jobs, and orchestrating AI agents through natural language.

Enables AI assistants to generate images using Cloudflare Workers AI models directly through the Model Context Protocol. It supports various models like Flux and Stable Diffusion, providing seamless image generation and storage via Cloudflare R2.

Exposes a single HTTP endpoint that aggregates tool definitions from GitHub, Kubernetes, and database namespaces, letting clients list available tools and invoke them by name. It provides health-check, tool-discovery, and tool-call routes for local, read-only experimentation without calling hosted models or applying production changes.