"A system for parsing and investigating contact information provided in a sentence" matching MCP servers:

A lightweight MCP server that enables AI assistants to execute local development tools and retrieve system status with low latency over stdio or HTTP.

An offline MCP server for SAP ABAP that provides static analysis, ABAP Cloud readiness checks, and RAP scaffolding using abaplint, enabling AI agents to analyze and generate ABAP code without a live SAP system.

An MCP server that turns AI assistants into competent Festo/CODESYS PLC engineers by grounding them in curated, manufacturer-accurate knowledge and forcing every artifact through a machine-checked validation pipeline for CODESYS import.

Provides a Model Context Protocol server with tools for knowledge base search, retrieval, and addition, plus system time, resources, and prompts. Supports stdio and Streamable HTTP transports for local and shared deployments.

Enables listing top-level frames in a Figma file and fetching a selected frame's rendered PNG, node JSON, and image-fill map into a local output directory.

A Firecrawl MCP server with built-in support for multiple API key rotation, enabling web search, scraping, crawling, extraction, and more via MCP clients.

A production-grade, extensible Python template for building Model Context Protocol servers with support for Streamable HTTP and stdio transports. It provides a structured framework for implementing tools, resources, and prompts with built-in authentication, observability, and background task management.

A TypeScript-based MCP server that enables users to interact with Prometheus metrics using PromQL queries and discovery tools. It allows LLMs to retrieve time-series data, metadata, alerts, and system status directly from a Prometheus instance.

Integrates Cursor AI with Vite Dev server, allowing AI agents to modify code and observe live updates through the Hot Module Replacement system in real-time.

Exposes GOV.UK Frontend components and Design System patterns and styles as MCP resources for use with AI assistants.

An MCP server that provides AI clients with access to developer documentation via llms.txt files. Exposes tools, resources, and prompts.

Enables AI assistants to perform Google searches with real, resolvable sources and transparent search terms.

MCP server for overseer.nvim — gives any MCP-capable coding agent running inside Neovim (Claude Code, Codex, Gemini CLI, opencode) the same visibility and control over tasks the user has: list, run, tail, restart, stop. Agent-started dev servers land in the user's own task list instead of becoming invisible orphaned processes.

Enables AI models to access and search offline Wikipedia and other knowledge bases stored in ZIM format files. Provides intelligent content retrieval, structured browsing, advanced search capabilities, and metadata extraction for comprehensive offline knowledge access.

Enables multi-level reasoning with configurable depth levels, session-based state management, structured thought input, and real-time trace resources.

Relays error logs from other MCP servers when an LLM call fails and the returned error message is unclear, helping the model handle errors more intelligently.

Provides unofficial access to Philippine Stock Exchange data including quotes, price history, disclosures, financial reports, and market data via MCP.

Provides AI assistants with direct access to Jamf official documentation, enabling them to answer Jamf-related questions by searching, retrieving articles, and browsing product documentation.

Local MCP server for generating image assets with Google Gemini (Nano Banana 2 / Pro). Supports transparent PNG/WebP output, exact resizing/cropping, up to 14 reference images, and Google Search grounding.

Enables LLMs to interact with the AT Protocol ecosystem, including Bluesky, through natural language. Supports public data access without authentication and full write operations with authentication.