"Trending MCP server for memory usage with GitHub Copilot integration" matching MCP servers:

Enables AI tools like GitHub Copilot to manage and persist context using a local JSON-based memory store. Provides CLI, MCP server, and VS Code integration for storing, retrieving, and managing context entries.

Enables Claude Code sessions to read and edit OrcaSlicer presets, clone profiles, inspect saved plates, and search the OrcaSlicer wiki, all without OrcaSlicer running.

Enables Microsoft 365 Copilot and Copilot Studio chats to list, read, and write files in named code workspaces, preserving a separate workspace per conversation across restarts and optionally exposing headless browser and allowlisted command tools.

Integration project for Model Context Protocol (MCP) servers with Claude Desktop App, enabling filesystem operations, development support, and file management through natural language.

Enables ChatGPT web to read local files, search code, run shell commands, and drive a local Codex CLI via an official MCP connector, with human approval for risky commands and full audit logging.

Gives a Microsoft Copilot Studio agent Claude-Code-style tools to read, edit, search, and run shell commands against your local filesystem.

Exposes local memory vaults as 6 MCP tools over stdio, enabling clients like Windsurf, Zed, and Claude Desktop to read and write memory.

MCP server that exposes agent-memory-daemon to any MCP-compatible client — Kiro (CLI & IDE), Claude Desktop, Cursor, and others. The daemon does the thinking (consolidation + extraction); this server is a thin filesystem bridge so agents can read, append, and search memory through the Model Context Protocol.

50 tools and 400 functions for working with Excel/.xlsx spreadsheets — read/write, recalculate formulas, diff, repair broken references, and audit. Built for AI agents.

Provides persistent memory for Claude with hierarchical categorization, cross-corpus recall, session journals, and customizable persona, enabling memory continuity across sessions.

A local MCP server that provides agents with tools to list, read, search, inspect history and diffs, and capture unstructured text in a user-owned Git repository of durable memory.

Provides project memory management for Claude Desktop, storing memories as Markdown files with intelligent keyword-based retrieval and automatic creation/update decisions by LLM.

Memory bank with Server as SSH support for central knowledge base

MCP Server for the GitHub API, enabling file operations, repository management, search functionality, and more.

Provides a local markdown-based memory system for coding agents through MCP, enabling search, add, register, inventory, sync, and ingest operations across user and project memory. It gives any agent tool a durable, provider-agnostic shared memory stored in folders you own.

Enables reading, writing, and searching a local markdown-based memory store using MCP tools, with safety checks and index consistency.

Enables AI clients to preserve and share knowledge as plain Markdown files in a local folder the user owns, with tools to remember, recall, get, update, forget, and list scopes. Memories are stored by scope, versioned rather than overwritten, and readable or editable in Obsidian or any text editor.

A Model Context Protocol server that gives AI agents bounded, auditable access to propose changes to an Obsidian vault stored in GitHub, with per-agent expiring tokens, read/write/deny path policies, mutability rules, frontmatter checks, and human-reviewed proposal branches.

A collection of small MCP servers for macOS automation that expose Apple Mail, MoneyMoney, and Spotlight functionality as tools via AppleScript and command-line, enabling AI applications to search mail, manage contacts and transactions, and perform system-wide file searches through natural language.

Exposes local persistent memory as an MCP server with Markdown storage, PARA organization, Zettelkasten linking, and SQLite FTS5 search. Enables Claude and other MCP-compatible agents to store, organize, and retrieve knowledge with context-based recommendations through the Olima association engine.