Use MCP to connect AI assistants with LinkedIn sales workflows

MCP in one paragraph

Model Context Protocol is an open standard that defines how an AI assistant calls structured tools provided by an external system. Where older approaches required pasting data into a chat or wiring up bespoke webhooks, MCP gives the AI a discoverable list of tools, the schema for each tool's arguments, and a way to call them with the same security model the underlying system already uses. For a SaaS product, exposing MCP tools means an AI assistant can read and write through the product's public surface using a single connection rather than a tangle of integrations.

The LinkedNav MCP tool groups

LinkedNav organizes its MCP surface into tool groups that map to the parts of a sales workflow. A workspace can enable each group independently, scoped by the API key tied to the connection. The grouping keeps the AI assistant focused on the relevant subset of tools for the task at hand rather than presenting every action at once.

• Dashboard stats: read aggregate workspace metrics for campaigns, replies, and enrichment
• Contacts: search, read, and update individual contact records sourced from LinkedIn
• Lists: create, populate, and read named lead lists used as the unit of work for campaigns
• Campaigns: read campaign state, performance, and step configuration
• Signal leads: read leads sourced from buying signals and social listening
• Social listening: configure and read the monitored topics, competitors, and influencers
• Email enrichment: trigger enrichment lookups and read results
• Agent actions: run packaged multi-step actions on a selected lead or list