"How to use Google Search" matching MCP servers:

Enables MCP clients to run offline-first web search, fetch and extract web content, build a local hybrid-retrieval knowledge base, and use persistent session memory without external API keys. It also supports intent-aware federated search, semantic reranking, entity graph exploration, and source-cited deep-search answers using local models.

Your coding agent remembers how it solved past tasks and reuses it next time: trigger, steps, outcome, lessons. Hooks recall the right skill before a task; skills strengthen with confirmed use and unused ones decay. Local SQLite, no API key, nothing leaves your machine. 9 MCP tools, works with Claude Code, Codex and Cursor. Agent-written memory stays untrusted until you approve it.

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.

Local MCP server that manages a job search using Markdown files, enabling skills tracking, gap analysis, and offer pipeline management via Claude.

Enables coding agents to use an Obsidian vault as long-term memory, with search, reading, and writing of notes, plus automatic capture of learnings that are propagated to MOCs, daily notes, and the knowledge index with git commits.

Model-agnostic, agent-ready Obsidian MCP server with RBAC, SLSA provenance, and native search. 163 tools across 31 domains, multi-vault, pluggable embeddings.

A local memory engine any AI tool can use.

SeaMeet MCP connects Claude, Cursor, Codex, and other AI agents to SeaMeet meeting recordings, transcripts, AI summaries, screenshots, action items, webhooks, and desktop recording controls. Use it to search meeting memory, read synced cloud recordings, and automate meeting notes through the Model Context Protocol.

MCP server that connects any AI to your Obsidian vault. Save articles from your phone, search across notes, build a compounding knowledge base. 15 tools, three transport modes (stdio, HTTP, cloud), zero-install Google Drive OAuth onboarding.

Enables multiple AI agents on one machine to write, search, fetch, link, and give feedback on a shared local store of Markdown-backed facts, preferences, and conventions that persists across sessions. Memories gain confidence as different hosts confirm their use and can be distilled into denser ones, so agents stop re-discovering the same context.

Cross-model AI memory persistence server that gives every AI tool you use access to the same persistent memory.

Enables searching Google Scholar with Scholar operators, year ranges, cited-by and all-versions lookups, and retrieving citations in five styles with BibTeX and EndNote export links as structured JSON.

Enables AI agents to query a local knowledge graph built from document collections using hybrid search (BM25 + vector fusion) and entity-relationship extraction. Supports privacy-first, offline operation with tools for semantic search, entity graph exploration, and corpus statistics.

An MCP server that allows AI assistants to search and retrieve human-curated content recommendations from Copus.

Enables keyword search, filtering, and retrieval of Claude Code memory files, reducing context overhead by fetching only relevant memories on demand.

Enables semantic search over markdown files to find related notes by meaning rather than keywords, and automatically detect duplicate content before creating new notes.

Self-hosted MCP memory server for personal use and teams

MCP memory server for AI agents that gets better with use

MCP server for intelligent, use-adaptive Obsidian vault search. It uses Hebbian learning and graph centrality to rank files by usage and relevance.

A codebase ontology and a cited wiki, both kept as Markdown in one folder on your disk. Typed graph answers — what a change affects, how two concepts connect, which wiki lines lack a citation — and every write lands as a Git diff a person reviews.

MCP server for Yandex Wiki with full-text search. Read and write pages, comments, attachments, and dynamic tables (grids); optional server-side read-only mode for agents. Docker-ready.

Gives Claude direct access to an Obsidian vault, enabling read, write, search, and automatic git sync for cross-device use.

Enables AI agents to use Obsidian vaults as persistent, bidirectional knowledge workspaces with wikilink/backlink resolution, structured frontmatter/tag indexing, task aggregation, and Obsidian Headless Sync.

Hebbian learning MCP server with neural memory graphs, eligibility traces, and three-factor reward signals. Associative memory that strengthens through use.

A Model Context Protocol server that enables AI models to perform real-time internet and knowledge searches through Higress, enhancing model responses with up-to-date information from Google, Bing, Arxiv, and internal knowledge bases.

Provides OpenCode with adaptive long-term memory by storing preferences, lessons, and usage history locally in SQLite, enabling AI to remember and adapt to users through context-based learning.

Provides persistent context management for AI agents by storing and querying semantic information using Upstash Vector DB and Google AI embeddings. It enables semantic search, batch operations, and metadata filtering to help agents retrieve relevant stored knowledge.

Enables Claude to save, retrieve, update, search, and organize personal ideas and reusable analytical frameworks in a private SQLite-backed knowledge base. Supports local desktop use or always-on access across a user's own devices over a private network.

Enables interaction with Notion workspaces through a comprehensive set of tools for managing pages, blocks, databases, users, comments, and search. Provides both a clean Python API and an MCP server for use with Claude Desktop.

Search your data exports from Google, Telegram, Spotify, and Instagram in one place. Everything runs on your own computer. Hybrid search and MCP, built in .NET 10

Enables agents to build and manage family trees, derive how people are related, and export diagrams or GEDCOM/HTML files through structured tools.

Enables Codex to use a local EverOS instance as long-term memory through MCP. Supports memory operations like search, get, save, and flush with automatic project ID inference.

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

Gives Claude persistent, local context about how you work, your weekly agenda, and shipped work, with automatic work logging and git integration—all stored privately on your machine.

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

MCP bridge for PDF Content Search — full-text PDF search with Apple Vision OCR across thousands of documents in under a second from Claude, Cursor, or any MCP client. Advanced filters (date, category, sender, amount), wildcards, boolean operators. Bridge open-source (MIT), PDF Content Search app is commercial with free iOS+Android companion scanner apps.

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.

Production-ready MCP server with session memory, Brave Search, Vertex AI Discovery Engine, Google Gemini analysis, and sandboxed code-mode transforms.