"A simple memory MCP server with read/write tools and vector database search" matching MCP servers:

Gives multiple AI coding agents a shared, persistent memory by indexing your code and documentation into a vector database with AST-aware chunking and hybrid semantic/keyword search. Agents can search across projects and store, update, or forget decisions, conventions and lessons learned, all self-hosted with local embeddings.

In-memory vector store with TF-IDF vectorization and cosine similarity search, paid per call via x402 micropayments.

Enables AI agents to format SQL, explain queries in plain English, analyze schemas, build queries from natural language, and generate migrations, all without requiring a database connection.

A SQL Server CLI and MCP server for Claude Code that supports standard SQL Server authentication for database interaction and management. It enables users to perform schema exploration, execute queries, and manage data records with built-in SQL injection prevention.

Personal memory MCP server backed by SQLite FTS5 BM25 search with temporal reranking.

Provides local vector-based semantic memory storage for AI assistants to persist context and decisions across sessions using local embeddings and LanceDB. It enables private semantic search and session handoff capabilities to maintain long-term project context.

Provides AI assistants with persistent memory across sessions using local SQLite and keyword search, allowing storage and retrieval of user preferences, project context, and decisions.

Enables Google search with advanced options (date, language, country, safe search) and webpage content extraction via the Model Context Protocol.

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.

A very simple vector store that provides capability to watch a list of directories, and automatically index all the markdown, html and text files in the directory to a vector store to enhance context.

Enables LLMs to read and write local user data, generate fake users via sampling, and interact with structured prompts and resources.

Enables AI agents to create document timestamps on a VerusID, writing directly to the Verus blockchain via a local or remote daemon.

Enables writing to CellarTracker by moving bottles between bins or locations and logging consumption, with planning, execution, and verification of outcomes using an authenticated session.

Enables read-only research on Reddit via the Reddit API, including finding subreddits, searching, and reading comment trees, with support for multiple configured accounts.

Provides Claude with direct access to databases including SQLite, SQL Server, PostgreSQL, and MySQL, enabling execution of SQL queries and table management through natural language.

An MCP server that extends AI agents' context window by providing tools to store, retrieve, and search memories, allowing agents to maintain history and context across long interactions.

Enables read-write management of Microsoft Intune devices and group memberships via the Microsoft Graph API, including device property updates, remote actions, and group membership changes.

Enables AI agents to semantically search GitHub repository documentation by automatically fetching, vectorizing, and indexing content into an Upstash Vector database. It provides a standard MCP interface for agents to retrieve relevant documentation snippets through natural language queries.

Enables LLMs to store, search, and manage memories with hybrid semantic and keyword search using ChromaDB and Neo4j for persistent memory and knowledge graph capabilities.

MCP server for OpenAI Vector Store API, managing vector stores, files, file batches, and semantic search.