"Using Claude Desktop and Code MCP to manage Google Cloud Platform/Vertex AI projects" matching MCP servers:

Enables LLMs to generate and retrieve long-term memories using Vertex AI Memory Bank, with tools for memory initialization, generation, retrieval, creation, deletion, and listing.

Provides persistent memory capabilities for Claude Code using Neo4j graph database to track development tasks, code patterns, solutions, and their relationships across sessions and projects, enabling contextual assistance and pattern recognition.

Enables Claude Code to search, browse, and read its own past conversation history across all projects using BM25 keyword search.

MCP server for reading Claude Code session history from the local filesystem, exposing project and session data to MCP-compatible clients.

An MCP server that enables users to retrieve, filter, and search through Claude Code conversation history stored in local projects. It provides tools for listing projects and sessions, paginating through message history, and searching across conversations with keyword filtering.

Enables AI clients to access a shared, authenticated memory and project management system with durable storage, task tracking, roadmaps, and semantic search, deployed on Cloudflare.

Search and reference your Claude Code conversation history directly from Claude, with full-text search, conversation viewing, and project browsing.

Enables searching all Claude Code conversations across projects using natural language queries and instantly provides resume commands to continue discussions.

MCP server that connects Claude Code to Substrate organizational memory, providing tools for searching, reading, querying, and writing memory, with automatic capture of conversation turns.

Automatically captures technical and product decisions from Claude Mac app sessions and writes them into project files, enabling seamless context transfer between strategy and coding sessions.

提供文档智能问答的MCP服务器，支持查询知识库、获取会话历史和清理会话历史。

Enables AI assistants to retrieve, search, and compare procurement documents using hybrid retrieval and MCP integration.

Provides a local, agent-maintained product context layer over MCP, serving structured strategy, competitor, customer feedback, and feature inventory data to any AI tool such as Claude, Cursor, or ChatGPT, with local data storage, bring-your-own-LLM support, and weekly evidence-based roadmap reviews that can sync suggestions to Jira or Linear.

Bridges Hermes Agent to the Hermes Intelligence Platform API, enabling tools to read/write learning loop data (context, feedback, signals, memory, etc.) via stdio.

Integrates RAGFlow's knowledge base API with Claude Desktop for document retrieval, semantic search across multiple datasets, and intelligent query refinement using DSPy.

Provides persistent, searchable memory for Claude Code using local SQLite, semantic embeddings, and full-text search, enabling Claude to recall and retrieve context across sessions and projects without external services.

A local, cross-editor MCP server that provides persistent memory for coding agents, capturing and recalling decisions, conventions, and fixes across sessions without API keys.

Provides semantic code search and code insights via a knowledge graph, enabling AI to understand, navigate, and modify complex projects with deep dependency and architecture analysis.

A minimal, tag-free personal memory system that syncs across all Claude interfaces (mobile, web, desktop, Claude Code). Built on Cloudflare's edge stack for zero-maintenance serverless operation.

An MCP server that provides Claude Code with persistent memory across sessions, including session checkpoints, image persistence, and bidirectional sync with claude.ai projects.