"Finding people on LinkedIn using their names" 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.

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

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

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.

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

A public, source-linked notebook for AI agents and people. Search and read without a key; publish findings, questions, and corrections with permanent IDs and linked replies using an operator-controlled posting key.

Local-only MCP server for saving and restoring conversation context across AI agent sessions using JSON files on disk.

Gives AI agents persistent, local-first memory using SQLite and on-device embeddings, enabling semantic search and recall across sessions with no cloud calls.

Privacy-first local document search using semantic search. Runs entirely on your machine with no cloud services, supporting PDF, DOCX, TXT, and Markdown files.

A local MCP server that indexes and searches your past Claude sessions using SQLite FTS5. No cloud, runs entirely on your machine.

Shared, code-grounded memory for developers and their coding agents. Capture a learning once and the whole team plus every agent recalls it; memory is grounded in your code and stored as git-tracked JSON reviewed in PRs, with citations validated on write and stale memory withheld from recall. Works with any MCP client.

A local MCP server that maintains a persona profile (contact library) for AI assistants, allowing them to create, search, retrieve, supplement, and correct information about people mentioned in conversations via tools like search_profiles, get_profile, create_profile, update_profile, add_facts, update_fact, and delete_fact.

A headless MCP server for interacting with Obsidian vaults, enabling AI assistants to search, read, edit, and manage notes and their structure without a GUI.

Provides persistent identity and memory for AI agents across MCP-compatible harnesses, enabling agents to retain their name, values, and episodic memories between sessions regardless of the client or model.

Converts handwritten journal photos into a searchable, AI-powered local knowledge base using Tesseract OCR. It enables users to query their notes, track insights, and export data through MCP-compatible AI assistants while maintaining complete local data privacy.

MCP server that gives Claude Code and other MCP clients persistent memory using plain Markdown notes stored on your disk and optionally synced to cloud storage (iCloud, OneDrive, Google Drive, Dropbox).