gtm-api

gtm-api is an advanced technical solution that functions as a LinkedIn API and an MCP (Model Context Protocol) server designed specifically for AI agents. This tool allows large language models such as Claude, ChatGPT, or Cursor to perform direct actions on the professional network, overcoming the functional limitations of the official LinkedIn API. Through a single technical contract, developers can equip their agents with the ability to search profiles, send messages, manage invitations, and automate contact data enrichment.

The gtm-api architecture is based on a highly secure connected-account approach. Each LinkedIn profile operates within an isolated anti-detect cloud browser using dedicated residential proxies. Its integration is versatile: it offers typed MCP tools for AI agents and a REST API for traditional backend infrastructures. The system automatically manages tokens, session recovery, and activity control, allowing for seamless execution without the need for constant manual intervention from a computer.

Key capabilities and functional benefits:

• Data Extraction and Scraping: Allows users to obtain lists of individuals who have interacted with specific posts, filtering by job titles (C-level, founders) and performing detailed profile enrichment.
• Intelligent Messaging Management: Read conversation threads, draft AI-powered responses, and automatically classify messages based on contact intent.
• Automated and Personalized Outreach: Send connection requests with personalized notes based on events, common interests, or mutual followers, while always maintaining natural sending rhythms.
• Advanced Interactions: The ability to send LinkedIn voice notes, a rare feature in automation tools that helps improve conversion rates.
• GTM Ecosystem Synchronization: Automatically classify and route leads to CRMs like HubSpot or automation platforms such as n8n, Make, and Zapier.

Security is the key differentiator for gtm-api. The tool implements Single Session Protection, ensuring that only one active session exists per account to prevent collisions and detection from concurrent access. With a restriction rate of less than 1% across an infrastructure supporting thousands of accounts, it applies warm-up curves and intelligent activity limits. This ensures that LinkedIn automation is sustainable in the long term, simulating human behavior through stable, geolocated browser fingerprints.

This resource is essential for GTM engineers, lead generation agencies managing multiple client accounts via OAuth, and platforms looking to integrate LinkedIn features into their software without building the infrastructure from scratch. While its current focus is LinkedIn, the technology is designed to eventually unify email, instant messaging, and calendar channels under a single programming interface.