+++ title = “Vimeo MCP Server” linkbuilding = [ “vimeo mcp”, “mcp server available tool”, “mcp server provides tools”, “tools mcp server”, “mcp server tools” ] keywords = [ “vimeo mcp server”, “video hosting mcp”, “mcp server”, “vimeo”, “video management mcp”, “mcp”, “video hosting”, “model context protocol” ] description = “Streamline video content management with AI-powered workflows using the Vimeo MCP Server. Integrate Vimeo’s video hosting, analytics, and distribution capabilities with AI assistants and developer tools through the Model Context Protocol for automated video operations, performance tracking, and seamless content delivery.” image = “/images/hosted-mcp-servers/linkedin.webp” shortDescription = “Transform video content management by connecting Vimeo’s professional hosting platform with AI-powered workflows using the Vimeo MCP Server for automated uploads, analytics tracking, and intelligent content distribution.” tags = [ “Video Management”, “Content Hosting”, “MCP”, “AI Integration”, “Developer Tools”, “Video Analytics” ] categories = [ “Integrations”, “MCP Servers” ] showCTA = true ctaHeading = “Try Vimeo MCP Server with FlowHunt” ctaDescription = “Automate your video workflows, unlock powerful analytics, and streamline content distribution directly from your AI-powered tools.” ctaPrimaryText = “Try it Now” ctaPrimaryURL = “https://app.flowhunt.io/sign-in" ctaSecondaryText = “Book a demo” ctaSecondaryURL = “/demo/” fork = 0 star = 0 overallScore = "” date = “2026-01-14 13:44:27”

[[mcpServerConf]] client = “windsurf” config = “1. Ensure Python 3.10+ is installed. 2. Clone the repository or install via PyPI. 3. Add Vimeo MCP server to your mcpServers config: { "mcpServers": { "vimeo-mcp": { "command": "python3", "args": ["-m", "vimeo_mcp"], "env": { "VIMEO_ACCESS_TOKEN": "your_vimeo_access_token" } } } } 4. Save and restart Windsurf. 5. Verify access in Windsurf’s UI. "

[[mcpServerConf]] client = “claude” config = “1. Ensure Python 3.10+ is installed. 2. Use claude-config-template.json as a base. 3. Update mcpServers: { "mcpServers": { "vimeo-mcp": { "command": "python3", "args": ["-m", "vimeo_mcp"], "env": { "VIMEO_ACCESS_TOKEN": "your_vimeo_access_token" } } } } 4. Save and restart Claude. 5. Confirm connection in Claude’s integrations. "

[[mcpServerConf]] client = “cursor” config = “1. Install Python 3.10+ and the MCP server. 2. Edit Cursor’s configuration: { "mcpServers": { "vimeo-mcp": { "command": "python3", "args": ["-m", "vimeo_mcp"], "env": { "VIMEO_ACCESS_TOKEN": "your_vimeo_access_token" } } } } 3. Save and restart Cursor. 4. Check server status in MCP panel. "

[[mcpServerConf]] client = “cline” config = “1. Ensure Python 3.10+ is present. 2. Install the MCP server. 3. Update Cline’s configuration: { "mcpServers": { "vimeo-mcp": { "command": "python3", "args": ["-m", "vimeo_mcp"], "env": { "VIMEO_ACCESS_TOKEN": "your_vimeo_access_token" } } } } 4. Save, restart, and verify connectivity. "

[[faq]] question = “What is the Vimeo MCP Server?” answer = “It’s a bridge between Vimeo’s video hosting platform and AI/developer tools via the Model Context Protocol (MCP), enabling natural language access to video management, automated content distribution, analytics tracking, and seamless workflow integration for video creators and content teams.”

[[faq]] question = “What are the main use cases for video teams?” answer = “Automated video uploads and metadata management, bulk video operations across your library, natural language analytics queries, scheduled content publishing, thumbnail customization at scale, privacy and access control automation, and cross-platform video distribution workflows.”

[[faq]] question = “How do I secure my Vimeo API credentials?” answer = “Store your Vimeo access token in environment variables using the ‘VIMEO_ACCESS_TOKEN’ variable in your MCP server configuration. Never commit credentials to version control or hardcode them in configuration files.”

[[faq]] question = “Can I use this for video analytics and performance tracking?” answer = “Yes, the Vimeo MCP Server provides access to comprehensive video analytics including view counts, engagement metrics, audience demographics, watch time data, and performance trends, enabling AI-powered insights and automated reporting.”

[[faq]] question = “Does this work with Vimeo’s privacy controls?” answer = “Absolutely. The server supports full control over video privacy settings including public, private, password-protected, and domain-restricted access, allowing you to automate privacy management based on your content distribution strategy.”

[[faq]] question = “How do I use this MCP server inside FlowHunt?” answer = “Add the MCP component to your FlowHunt flow, open its configuration, and insert the Vimeo MCP server details in JSON format with your access token. Once configured, your AI agent will have access to Vimeo’s video management and analytics capabilities for intelligent video workflow automation.” +++

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