Overview
Labra AI Agent enables organizations to streamline revenue, manage transactions, and gain insights into their AWS Go-To-Market (GTM) strategy. Effortlessly integrate with your CRM environments and third-party tooling.
Labra's AI capabilities are purpose-built for Cloud GTM. Gain access to AI-driven buyer insights, marketplace optimization strategies, automated actions, custom workflows, and so much more!
Highlights
- Marketplace operations like offers, contracts, metering, and invoicing can be automated with Labra AI
- Get Co-sell data and all the analysis with it in your preferred CRM environment
- Operationalize your GTM faster with AI-powered buyer insights, automated workflows, and more
Details
Unlock automation with AI agent solutions

Features and programs
Trust Center
Financing for AWS Marketplace purchases
Pricing
Dimension | Description | Cost/12 months | Overage cost |
---|---|---|---|
product price | Pricing as defined in the contract | $12,000.00 |
Vendor refund policy
Contact our support team for refund information.
Custom pricing options
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Legal
Vendor terms and conditions
Content disclaimer
Delivery details
API-Based Agents & Tools
API-Based Agents and Tools integrate through standard web protocols. Your applications can make API calls to access agent capabilities and receive responses.
Additional details
Usage instructions
🚀 Labra MCP Server Quick Reference
Seamless integration with Labra's marketplace management platform for metering data and product information.
MCP Server URL: https://api.labra.io/mcp_service/v1/mcp/
🖥️ Claude Desktop Setup
Prerequisites
- Node.js and npm installed on your system
Installation & Configuration
- Configure Claude Desktop: { "mcpServers":{ "labra":{ "command":"npx", "args":[ "mcp-remote", "https://qa.api.labra.io/mcp_service/v1/mcp/", "--header", "Authorization: Bearer <your-jwt-token>" ] } } }
- Restart Claude Desktop
🔧 Claude Code Setup
Installation & Configuration
🔌 Other MCP Clients
For other MCP clients, check their respective documentation for HTTP transport configuration.
Usage Examples
- Show me metering data for product X from last month
- Get details for all AI/ML products
- @labra health-check
Available Functions
📊 Metering Data
Retrieve usage and billing data for marketplace products. Returns: Metered quantities, buyer details, product info, pricing dimensions, processing status
📦 Product Catalog
Access product information and marketplace catalog data. Returns: Product ID/name/type, marketplace URLs, contract metrics, pricing models, lifecycle status
💡 Common Use Cases
- Business Intelligence: Real-time dashboards, automated reporting, trend analysis
- Operations: Usage monitoring, error tracking, compliance reporting
- Customer Success: Usage insights, subscription health monitoring
⚡ Best Practices
- Use specific date ranges for better performance
- Implement error handling for processing status
- Cross-validate metering with product data
- Cache frequently accessed data
🎯 Quick Start
- Get authentication token using client-credential OAuth flow
- Configure your client to use the token for authenticated calls
- Test: What products do I have in my catalog?
- Build queries: Compare usage between Q1 and Q2 2024
- Advanced: Create monthly recurring revenue trends
🔧 Troubleshooting
- Connection Failed: Check API key and endpoint
- No Data: Verify date ranges and filters
- Slow Performance: Use specific queries and date ranges
📈 Advanced Features
- Automated monthly reports
- Usage alerts and notifications
- Custom analytics pipelines
- Integration with other MCP servers
📘 Learn More
Help Center: https://helpcenter.labra.io/hc/en-us
To manage (CRUD actions) your API keys, please visit to https://app.labra.io/settings/keys
Enables real-time access, automated workflows, and scalable analytics for marketplace data directly within your client.
Resources
Vendor resources
Support
Vendor support
Reach out to our support team on support@labra.io
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.