Eased
Eased is a library of motion-first React components for shadcn, installed with the shadcn CLI.
Find MCP servers that connect AI assistants to useful tools and data. Explore what each server does, its setup and its documentation.
2869 servers · Page 238 of 240
Eased is a library of motion-first React components for shadcn, installed with the shadcn CLI.
Zero trust LLM gateway. OpenAI-compatible proxy with semantic routing and load balancing across OpenAI, Anthropic, Ollama, vLLM, and any compatible…
MCP server and REST API for Japanese listed companies: EDINET XBRL line items, TDnet disclosures and JPX listings, with five years of financials,...
Mangrove gives trading agents guardrails. Every order an agent places goes through built-in risk management: circuit breakers, drawdown and daily…
Official MCP server of the Scrapling web scraping framework: HTTP requests, stealthy browser, screenshots and network inspection for AI agents. 17 tools, with
AzYun is a unified API gateway that works as the model-calling layer behind MCP workflows: one standard API reaches OpenAI, Claude, Gemini and other...
Hosted MCP connector for any IMAP/SMTP mailbox (Gmail, iCloud, GMX, WEB.DE, IONOS, Posteo …). Search and read email, extract PDF/Word attachments, sort...
Pika H3 is an AI video tool. Visit the official site for details and usage.
Cheapest AI virtual assistant for your business line: $1.99/mo per number, then pay only for usage ($0.20/min). Your AI receptionist answers calls, takes...
Public leads and enrichment — NPI, podcasts, local businesses, hiring, websites, teams, trends, trucking (8 MCP tools). Panda Federation focused server.
Site, email and agent safety — SPF/DKIM/DMARC, AI/SEO audit, page-change monitor, free hidden-AI scanner (4 MCP tools). Panda Federation focused server.
Termany MCP Server: Agent-Native Terminal.
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.