"How to find people on LinkedIn using their username" matching MCP servers:

Enables agents to store documents and atomic facts with provenance in a local SQLite knowledge base, then search them through fused keyword, exact, semantic, entity, graph and fact retrieval arms that return one ranked list where every result carries its address, trust level and a reason for its rank. A read-only terminal and loopback web view let humans inspect the same searches, timelines, entity neighbourhoods and agent-written pages without being able to alter the knowledge base.

Enables coding agents to develop on one machine and verify results on another, using branch-bound runbooks, isolated checkpoints, and structured receipts to guide repair iterations.

Enables agents to reduce tool noise by exposing only two meta-tools for searching downstream MCP servers and calling their tools on demand. Connections are lazy and tool lists are cached, so configured servers can be used without loading every tool upfront.

Enables running local MCP servers on machines behind NAT and accessing their tools from anywhere through a single Streamable HTTP endpoint, without opening any inbound ports.

A Go CLI and MCP server for cross-posting to Twitter, LinkedIn, and Reddit from your terminal or AI agents, with secure local credential storage.

LLM Optimizer is an AI visibility intelligence platform. It analyzes how large language models and AI search engines perceive, cite, and recommend brands; then provides research-backed optimization strategies to improve that visibility.

Provides AI agents with nine read-only tools to search and explore Bible people, places, events, reigns, letters, journeys and passages, including relationships, timelines, geography, Bible references, and source-linked atlas records.

The Multi DB MCP Server is a high-performance implementation of the Database Model Context Protocol designed to revolutionize how AI agents interact with databases. Currently supporting MySQL and PostgreSQL databases.

Enables reading and managing Pipedrive CRM records—deals, people, organizations, activities, and notes—over MCP, including searching, writing, and moving deals through pipelines.

Enables AI agents to communicate with business agents across company boundaries using Google's A2A protocol, with tools for discovery, messaging, and connection management.

MCP server for processing Markdown resumes into multiple formats (PDF, LinkedIn templates) with AI analysis and Claude integration.

lunar-mcp is a Go-based MCP server that provides 28+ tools for Chinese traditional calendar, fortune telling, and divination. It enables AI agents to integrate Chinese cultural computations into their workflows.

Enables AI assistants to read, send, and manage Instagram direct messages, including viewing conversations, sending DMs to users, reacting to messages, and searching for users by username.

MCP server in Go to search and download books, papers, comics and more from Library Genesis — three focused tools, one static binary, no account required.

Records your terminal sessions per command (PTY + OSC 133) into local SQLite, so AI agents can search, retrieve, and diff what commands actually printed. Secret redaction is applied by default to everything served over MCP.

Model Context Protocol server for the NetLoc8 IP geolocation API. Gives AI assistants access to country/city lookup, timezone reconciliation, and IP utilities.

MCP server for GLEIF LEI (Legal Entity Identifier) database access. Look up, validate, and search legal entities and their relationships in the global LEI system.

PCI DSS v4.0.1 compliance scanner for Go payment services, delivered as an MCP server. Every finding maps to a specific PCI DSS requirement ID. Taint-aware cardholder data flow analysis with PCI SSC FAQ semantics, designed to complement broad SAST tools like Semgrep and CodeQL - not replace them.

Turn any OpenAPI/Swagger/Postman spec into an MCP server — give your LLM live access to any API.

Model Context Protocol (MCP) server for GitLab — exposes 1006 GitLab REST & GraphQL API operations as MCP tools (42 meta-tools / 57 enterprise), 24 resources, 38 prompts, and 17 completion types for AI assistants. Written in Go, single static binary, stdio and HTTP transport.