"Deploying an MCP service in an offline environment" matching MCP servers:

Enables local AI inference using Ollama and open-weight models, designed for offline operation in low-connectivity environments.

Call OpenAI Codex from Claude Code for independent second opinions, structured code review, and delegated coding tasks through a FastMCP plugin that drives the codex CLI safely.

Enables AI agents to read and create customers, jobs, estimates, invoices, calendar tasks, equipment, technicians, and reference data through the documented Service Fusion REST API, handling OAuth 2.0 and pagination automatically.

Provides access to Hong Kong government environment data, including the current Air Quality Health Index (AQHI) from monitoring stations across Hong Kong.

Enables AI agents to manage a Canonical Landscape estate, including inventory, alerts, patching, and script execution, with built-in safety layers to prevent accidental destructive actions.

Provides GDB and clangd-based tools for debugging C++ programs, enabling step execution, variable inspection, diagnostics, and combined runtime-static analysis.

An MCP server that provides Large Language Models with access to YNAB (You Need A Budget) budgets, allowing them to fetch budget data including accounts, categories, and category groups.

Exposes data query and auto-insights (anomaly detection) as MCP tools. Enables AI agents to query metrics, list columns, and get data insights directly from pandas.

Enables downloading content from various social media platforms through a unified API. Provides a single tool to download media from multiple social networks using the Social Download All In One service.

Exposes five tools for querying and analyzing a customer-support dataset, including listing categories/intents, filtering, counting, and summarizing records.

Enables AI assistants to interact with humans through GUI dialogs for text input, choices, confirmations, and information display.

Enables AI assistants like Claude to interact with humans through intuitive GUI dialogs, supporting text input, choices, confirmations, and information displays.

A single-process MCP server that crawls web pages, handles anti-bot challenges, converts HTML to Markdown, and caches results in PostgreSQL, providing tools to fetch and read web content.

Generate professional AI-powered presentations from a topic, raw text, or document file. Export to PPTX, PDF, image, or shareable link.

Enables AI agents to interact with Freeplay, an ops platform for AI engineering teams, to analyze production logs, identify quality issues, iterate on prompts and agents using real data, and run experiments before deploying.

Provides a generic HTTP client tool allowing AI agents to make arbitrary HTTP requests from their environment, with support for environment-variable placeholders for secrets.

A FastMCP server that turns JSON data into Plotly figures, deployable as an isolated service on Modal. Data goes in as JSON; a validated Plotly figure (JSON) or a rendered PNG comes back over the Model Context Protocol.

An MCP server that enables AI assistants to diagnose network and service problems by walking a structured funnel of cURL timing metrics, identifying which hop is at fault, and providing targeted recommendations.

Enables AI agents to store and retrieve self-hosted memories over MCP (stdio or Streamable HTTP) using local embeddings that work fully offline. Writes are redacted before they hit storage and every read is recorded in an exportable, append-only audit log.

An MCP server that enables autonomous code development by pulling GitHub issues, fixing them in a sandboxed environment, running tests, opening PRs, and promoting to production upon human approval.