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

Local-first memory for AI agents about the people in your life. MCP server + CLI on SQLite. Never phones home.

An MCP server that gives AI agents a private, durable memory of people, providing a personal people graph in PostgreSQL with tools to search, remember, and connect people, plus imports from LinkedIn, Google Contacts, and WhatsApp, and a browser UI.

Pull Deep Memory from across your Claude Code Sessions — when you need it.

Analyzes LinkedIn saved jobs with EROI scoring and writes analysis back to a knowledge base for automated reporting.

Turns GitHub repository history into a cited maintainer skill for coding agents, providing tools to collect evidence, query the knowledge graph, and inspect bundles.

Turn Obsidian notes into agent-ready context, preview-only plans, and safe repo handoffs.

On Board is a local MCP server that gives multiple AI agents and IDEs a shared project memory, ticket queue, and handoff history, so agents can seamlessly continue each other's work. It supports agent-to-agent wake events, enabling autonomous workflows like reject-fix-resubmit cycles without human relay.

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 AI tools to query context from a local JSON data source via stdio, demonstrating the Model Context Protocol.

MCP server that connects AI agents to Google NotebookLM, enabling natural language interaction with notebooks, including Q&A, source ingestion, and audio overview generation.

Enables local-first knowledge management for Codex, providing tools for guided discussions, contextual recall, review, and daily topics.

Builds a searchable memory bank from persona-specific PDF content and exposes it as an MCP tool for querying.

Self-improving, verifiable memory for AI coding agents. Learns how you work, stops repeating mistakes, models each project, recalls the right lesson at the right moment. Every memory is signed and tamper-evident. Local-first.

Semantic memory for AI builders: capture the tacit engineering know-how that never reaches your docs, recall it the moment it applies. Built in Rust on Postgres and pgvector.

A self-hostable, open-source, semantically-searchable Agent Skills registry delivered over MCP, with a three-tier progressive disclosure architecture.

Enables indexing local documents (PDF, Markdown, text, code) into a knowledge base and querying them via semantic search using local embeddings, all running privately on your machine.

An MCP server that provides on-demand skill discovery for AI coding agents by querying GitHub repositories, using BM25 search to return relevant SKILL.md content.

Enables AI clients to search, read, and analyze a local SQLite knowledge base built from the full public archives of people you follow, bookmark, or subscribe to, with tools for onboarding, querying, and topic tracking.

Enables any AI coding agent to instantly find and resume sessions created in another agent. It indexes sessions from multiple harnesses locally and injects a compact, ready-to-resume payload without using LLM tokens.

Bible knowledge graph: 31,102 verses, 341,289 cross references, people, places, themes.