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

An MCP server that connects AI assistants to YNAB budgets, enabling natural language queries about finances backed by full API coverage and built-in YNAB methodology knowledge.

Enables AI agents to debug and repair historical Solaris/SPARC systems by providing an out-of-band control plane with guest DTrace, QEMU monitor access, SPARC-aware GDB, host eBPF/perf tracing, and an immutable evidence ledger for cross-layer hypothesis testing.

A minimal MCP server with get_weather and create_ticket tools, used for testing MCP servers across protocol, unit, eval, transport, and auth layers.

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

Connects AI assistants to Swiss environmental data from BAFU, including air quality, hydrology, natural hazards, and open datasets, with no API keys required.

Provides offline search and retrieval of Wikipedia articles using Kiwix .zim files, enabling LLMs to access full Wikipedia content without internet.

Enables generation of educational content like MCQs, lesson plans, and flashcards without relying on external LLMs, fully offline and compatible with Claude Desktop.

Exposes the shared health-check service as an MCP tool, letting clients query status, uptime, and version through the streamable HTTP endpoint.

Provides secure access to containerized build environments for software projects, enabling AI assistants to execute builds, run tests, manage git operations, and inspect build artifacts without requiring local installation of dependencies.

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

Provides tools to communicate with a service dependency API, enabling users to query and interact with service relationship data and dependency mappings.

It enables AI agents and CI to run profile-driven SOAP/REST service tests with automatic login/session handling, test-customer locking, masked transaction-log/HAR catalog import, and cross-environment scenario execution.

Enables users to describe their LLM fine-tuning job once and get the cheapest, fastest, and most balanced GPU options across a dozen cloud providers in seconds.

Enables agents to submit markdown for human review, track feedback, and apply revisions through an HTTP API with an optional MCP wrapper.

A production-ready generic FastMCP server template with SQLAlchemy async CRUD, enabling rapid bootstrapping of MCP data-management services. It provides registry-driven CRUD, FK resolution, conflict versioning, and multiple transports.

Real-time hydrological information retrieval service that provides water level, precipitation, dam discharge data, and observatory location information.

A reusable MCP HTTP server with OAuth 2.1 that turns any JSON-RPC handler into a production-ready endpoint with dynamic client registration, PKCE, refresh tokens, and OpenAPI docs.

Enables users to describe an LLM fine-tuning workload and receive ranked, cost- and runtime-optimized GPU recommendations across multiple cloud providers by estimating VRAM and FLOPs.

Enables users to describe an LLM fine-tuning job once and receive the cheapest, fastest, or most balanced GPU hardware options across a dozen cloud providers by calculating required VRAM/FLOPs and aggregating live pricing.

Enables users to describe an LLM fine-tuning job and receive ranked, task-aware GPU recommendations with estimated VRAM/FLOPs, cost, and runtime across more than ten cloud providers.