Linked API MCP

Linked API MCP – Bridging AI Assistants and LinkedIn

Linked API MCP provides a secure, cloud‑based bridge that lets AI assistants such as Claude, Cursor, or VS Code interact directly with a user’s LinkedIn account. Instead of manually browsing the platform, developers can issue natural‑language commands that translate into LinkedIn actions—searching for prospects, sending connection requests, or pulling profile data—all executed through a sandboxed browser environment that protects credentials and preserves privacy.

This server addresses a common pain point for sales, recruiting, and market‑research teams: the repetitive, time‑consuming tasks of sifting through LinkedIn profiles and initiating outreach. By offloading these chores to an AI, users can focus on high‑value activities like crafting personalized messages or negotiating deals. The cloud browser ensures that the assistant can navigate LinkedIn’s dynamic interface without exposing sensitive tokens or requiring direct API access, which is often limited or rate‑restricted.

Key capabilities include:

• Lead and candidate discovery – filter by role, company size, location, or skill set; retrieve detailed background information.
• Automated outreach – compose and send connection or message requests, with templates that adapt to the recipient’s profile.
• Conversation management – read existing LinkedIn messages, propose context‑aware replies, and schedule follow‑ups.
• Competitive intelligence – aggregate data on competitors’ employees, recent hires, or company updates to surface industry trends.
• Safe execution – all actions run in a sandboxed browser, preventing accidental data leaks or credential exposure.

Typical use cases span multiple domains:

• Sales automation: a sales rep can ask the assistant to pull a list of software engineers at mid‑size firms in San Francisco, analyze their experience, and draft outreach messages that resonate.
• Recruiting: a recruiter can search for candidates with niche skills, review their LinkedIn experience, and initiate first‑touch outreach without leaving the AI interface.
• Customer support: a support agent can read past LinkedIn conversations and receive suggested responses that maintain brand tone.
• Market research: analysts can gather up‑to‑date employee data and company activity to inform competitive positioning.

Integrating Linked API MCP into an AI workflow is straightforward: developers expose the server’s tools to their assistant, then invoke them via natural‑language prompts. The assistant translates these prompts into tool calls, receives structured responses (e.g., a list of profiles or a message draft), and can further refine the output with iterative prompts. This tight coupling enables developers to build highly specialized agents that automate LinkedIn interactions while keeping all data processing in a controlled, privacy‑preserving environment.