"A method for finding people on LinkedIn and organizing them in a CSV" matching MCP servers:

Cite-able, content-addressed, signed memory of every place on Earth

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.

Local design engine for AI Agents. Create, edit and export real, editable designs — social posts, flyers, print-ready PDFs — with your brand applied. Every design opens in a built-in editor, so you can click the text and fix it yourself instead of re-prompting. Bring in what you already have: InDesign, PSD, PPX and PDF files come in as editable designs. Runs on your machine, no account needed.

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.

DevEyes is a Model Context Protocol (MCP) server that captures screenshots from your local development environment and automatically optimizes them for LLM consumption.

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 Model Context Protocol server for Discourse forums, extended with review queue tools to list and act on pending or flagged items, enabling AI agents to moderate content.

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.

Enables agents to quickly find and edit code in a codebase with surgical precision. Find symbols, edit them everywhere with tools for reading code blocks, searching/replacing text, and making precise line-based modifications.

A Model Context Protocol server for interacting with MongoDB Databases and MongoDB Atlas. It enables AI assistants to query, manage, and operate on MongoDB data and Atlas resources through natural language.

Enables users to search domains, find and verify email addresses, enrich people and companies, discover companies, and manage leads through the Hunter.io API.

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

A local-first, no-API-key MCP server that enables LLMs to search the web, fetch pages, and read documents using multiple engines and smart fallbacks.

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.