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Rust-native MCP server for Office document processing (Excel, Word, PowerPoint). Sub-millisecond, local-first, open source.
Find MCP servers that connect AI assistants to useful tools and data. Explore what each server does, its setup and its documentation.
2781 servers · Page 212 of 232
Rust-native MCP server for Office document processing (Excel, Word, PowerPoint). Sub-millisecond, local-first, open source.
Brandize MCP Server is the hosted MCP endpoint for Brandize, an AI logo generator.
Open-source MCP server that gives AI agents web search (SearXNG) and clean Markdown crawling of pages, whole sites and logged-in areas.
BitBrowser MCP simple to use, no complicated procedures required. Supports a variety of intelligent agent services.
QuantumProxies is a proxy network exposed as an MCP server. Instead of copying endpoints out of a dashboard, your agent asks for the proxies…
An MCP server for Google Tag Manager. Connect it to your LLM, authenticate once, and start managing GTM through natural language.
SaaS boilerplate/starter-kit in Go+React with Stripe integration, multi-tenant support, comprehensive features and AI-agent ready.
Yolfi Agent Kit SDK, CLI, and MCP server for AI coding agents.
Find quantum-vulnerable cryptography in your codebase — secp256k1, Ed25519, BLS, Schnorr, RSA. Local, offline MCP server for AI agents.
Every SERP, every extractor. One MCP: search, page fetch, cited research, transcripts, product prices and permit records for AI agents, with the…
OpenVibeCoding is the command tower for AI engineering: plan, delegate, track, resume, and prove long-running work across Codex and Claude Code.
Guardrailed video editing MCP server for AI agents. FFmpeg, Hyperframes, repurposing tools, Python client, and CLI. Local, fast, free.
An MCP server exposes tools or data through the Model Context Protocol so a compatible AI client can use them. Each project has its own installation, authentication and permission requirements.
Open a server’s page for its getting-started notes, compatibility and sources, then follow the original project’s documentation for your AI client.
Entries link to the original documentation. Check access requirements, costs and maintenance there before installing, and grant a server only the access it needs.