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MCP.so is a third-party MCP Marketplace with 22589 MCP Servers collected.
ShipAny: NextJS boilerplate for building AI SaaS startups.
Latest MCP Servers
View AllProfitlee Mcp
ProfitLee MCP is an MCP server for analyzing ecommerce and marketplace profitability. It helps users calculate net profit, profit margin, ROI, breakeven price, and fee-adjusted outcomes from product cost, selling price, shipping, ads, platform fees, and tax inputs. It also supports reusable profit scenarios so users can compare pricing and cost assumptions more easily.
Finance Toolkit
The Finance Toolkit gives AI assistants access to 200+ financial metrics, all calculated transparently from raw financial statements, not pulled from third-party endpoints.
tinysend
tinysend gives agents email: create newsletters, manage subscribers and contacts, and write & send broadcasts - all over MCP. Remote streamable-HTTP server with OAuth sign-in (no API key to paste).
Motivegrid Vehicle Advisor
MotiveGrid Vehicle Advisor is a Model Context Protocol (MCP) server that provides structured, data-grounded vehicle intelligence for AI assistants. It enables ChatGPT, Claude, and other MCP-compatible tools to compare cars, evaluate long-term ownership cost, analyze safety and driver-assistance ratings, and generate personalized vehicle recommendations based on real constraints like budget, family size, and usage patterns. Unlike generic web search, MotiveGrid returns structured, decision-ready outputs built on real automotive datasets (including depreciation, fuel economy, and safety ratings), helping AI assistants give consistent, non-hallucinated car buying advice. What you can do with it: Compare vehicles side-by-side (e.g., Toyota RAV4 vs Honda CR-V) Get 5-year total cost of ownership breakdowns Retrieve structured vehicle scorecards (safety, reliability, comfort, efficiency) Generate ranked recommendations based on user needs and budget Explore electric vs hybrid vs gas tradeoffs with grounded data Designed for: AI assistants (Claude, ChatGPT, Cursor, etc.) Developers building automotive tools Users making real-world car buying decisions Key principle: All outputs are grounded in structured automotive data and designed to reduce hallucinations in AI-generated vehicle advice.
Mentionkit Mcp
Mentionkit is a AI first social listening tool with MCP support. After creating your account, you'll get a MCP url. Follow the instructions at https://app.mentionkit.com/mcp for Claude, ChatGPT or your favourite chat tool.
Latest MCP Clients
View AllADSUMO - #1 MCP for ad creatives
Adsumo turns any MCP-compatible AI tool into an ad studio. Connect once and your assistant can create professional, on-brand image and video ads without design tools or manual exports. Onboard a brand from a URL and Adsumo learns its logo, colors, voice, and products, so every ad comes out on-brand automatically. From there you can generate batches of image ads, produce video ads with Sora, Veo, Kling, or Seedance, edit and reframe creatives for any placement, translate copy into 100+ languages, and research what is winning in your niche through the built-in ad library. Run a single prompt or fire a full launch campaign across formats in one chat. *Some features require a subscription
OMNFLOW
Omnflow MCP gives AI agents three content automation tools: repurpose_content turns a blog post, transcript, or idea into 5 platform-ready posts (Twitter, LinkedIn, Instagram, etc.), analyze_voice extracts a writer's Voice DNA — tone, sentence style, and patterns — from any writing sample, and list_recent_demos lists recent public demo runs so you can see real inputs and outputs. Connect via https://omnflow.com/api/mcp.
OpenSEO
SEO research tools for AI agents: keyword research and metrics, SERP and local SERP results, domain and backlink analysis, rank tracking, and Google Search Console performance.
BUILDY
Buildy lets ChatGPT, Claude, or any coding agent build real web apps on demand. The app works across agents, so you can build it once and keep using the same app/data from ChatGPT, Claude, Codex, or wherever your agent runs.
FAQ
Frequently Asked Questions about MCP Server
What is MCP (Model Context Protocol)?
MCP is an open-source protocol developed by Anthropic that enables AI systems like Claude to securely connect with various data sources. It provides a universal standard for AI assistants to access external data, tools, and prompts through a client-server architecture.
What is MCP Server?
MCP Server is a system that provides context, tools, and prompts to AI clients. It can expose data sources like files, documents, databases, and API integrations, allowing AI assistants to access real-time information in a secure way.
How do MCP Server work?
MCP Server work through a simple client-server architecture. They expose data and tools through a standardized protocol, maintaining secure 1:1 connections with clients inside host applications like Claude Desktop.
What can MCP Server provide?
MCP Server can share resources (files, docs, data), expose tools (API integrations, actions), and provide prompts (templated interactions). They control their own resources and maintain clear system boundaries for security.
How does Claude use MCP?
Claude can connect to MCP server to access external data sources and tools, enhancing its capabilities with real-time information. Currently, this works with local MCP servers, with enterprise remote server support coming soon.
Is MCP Server secure?
Yes, security is built into the MCP protocol. Server controls its own resources, there's no need to share API keys with LLM providers, and the system maintains clear boundaries. Each server manages its own authentication and access control.
What is mcp.so?
mcp.so is a community-driven platform that collects and organizes third-party MCP Servers. It serves as a central directory where users can discover, share, and learn about various MCP Servers available for AI applications.
How can I submit my MCP Server to mcp.so?
You can submit your MCP Server by creating a new issue in our GitHub repository. Click the 'Submit' button in the navigation bar or visit our GitHub issues page directly. Please provide details about your server including its name, description, features, and connection information.