"Information about SAP (Software or Other Meanings)" matching MCP servers:

Enables LLMs to list, open, and close installed software on Windows, macOS, and Linux through natural language.

Centralized MCP server that provides standardized development workflow commands to Cursor AI, auto-detecting project type (Laravel, Next.js, Flutter, Architecture) and offering relevant commands for implementation, testing, and commits.

Enables retrieval, setting, and detailed information lookup of EPICS process variables (PVs) for monitoring and controlling hardware or software parameters.

A persistent Python REPL MCP server for AI agents with stateful execution, real timeouts, crash isolation, and an MCP bridge to call other tools in the project.

Enables Claude to create and interact with real, persistent Windows terminal sessions (cmd.exe or PowerShell) through ConPTY, including sending commands, reading output, and scoped Ctrl+C interrupts without affecting other processes.

Enables AI assistants to understand lab topologies, follow operational principles, and interact with real network devices through observable terminals while keeping private access information hidden.

Enables a coding agent to get short, token-efficient answers about a project through grouped searches, focused symbol or section reads, and bounded read-only script output, with safety limits on paths, secrets, commands, and response size.

MCP server that gives Claude Desktop and other desktop MCP clients filesystem powers—read, write, edit, and manage files like AI coding assistants.

MCP server for TQS structural engineering CAD/analysis software, enabling Claude to read building models, extract drawing data, run structural processing, and script against the TQS API.

A minimal MCP server that exposes a single tool to query local hardware information (OS, CPU, memory, architecture).

An MCP server that intelligently filters and compresses tool outputs to reduce context window usage, saving up to 90% of tokens by removing noise such as passing tests and redundant information.

Enables AI agents to communicate and coordinate across tmux panes, allowing them to read, type, and send messages to each other without manual copy-pasting.

An MCP server that bridges AI assistants to other CLI tools, enabling capabilities like large-context reads, vision, file generation, and cross-vendor verification without API keys.

An MCP server that lets AI assistants inspect and control Asterisk and FreeSWITCH PBX systems, enabling natural language queries about live switch status, channels, registrations, and call control.

Provides AI coding agents with structured, evidence-based diagnostics about the local development environment, detecting tech stack, runtime mismatches, dependency state, services, ports, and Git status without exposing secrets or using network calls.

Lets AI coding agents read an outline of a large file or a digest of noisy command output instead of the full text, while every hidden line stays retrievable on disk through a run handle. Agents can request only the line ranges, slices, or grep matches they need and list recent runs, cutting token spend without losing information.

Provides Ubuntu system information (CPU, memory, disk, network, services, processes) to Bob via natural language queries.

Enables MCP-based communication with existing interactive terminal channels, such as shells or agent CLIs, by listing, reading, writing text, and sending control signals to tmux sessions without creating or managing them.

Lets ChatGPT, Claude Desktop, Claude Code, and other MCP clients run an allowlisted set of local commands and read files from a chosen directory, so an assistant can analyse a codebase or trigger local generators (images, sprites, assets) without metered API tokens. The server is read-only and deny-by-default by default, with no shell, path containment, opt-in writes, and required auth when exposed over HTTP.

A stateless MCP server that wraps the headless Gemini CLI, providing tools to send prompts to Google's Gemini models and receive text responses. It supports both simple prompts and prompts with contextual information.