"Information and resources about memory" matching MCP servers:

Persistent memory and automatic git snapshots for Claude Code, capturing decisions, patterns, and architecture across sessions.

Provides Claude with a persistent, auditable memory stored as markdown and YAML files in a private GitHub repo. Enables reading, appending, organizing, and messaging between agent conversations through MCP tools.

Serves a git-backed folder of Markdown notes over MCP so AI agents can search, read, write, move and delete them, with every write recorded as a git commit attributed to the calling client. Supports full-text section search with snippets, wikilinks and typed relations, LFS-backed searchable attachments, optimistic concurrency for multiple agents, and per-client token or OAuth 2.1 access.

A git-backed per-repo memory layer for Claude Code, enabling persistent, version-controlled storage and retrieval of memories to build a self-evolving skill.

Manages knowledge graph data synchronized with GitHub repositories, enabling remote storage and collaboration of memory entities, relationships, and observations.

Enables AI coding assistants to persist context across sessions by saving, searching, checkpointing, restoring, and organizing decisions, progress, files, and Git-related state.

Enables Git repository operations and real-time monitoring via MCP tools, with support for WebSocket events, authentication, and observability.

Enables deterministic behavioral regression review of pull-request diffs by checking changed code against approved incident-derived contracts. It exposes read-only tools to assess diffs and pull requests, list and fetch contracts, and report outcomes over stdio without mutating repositories.

Bridges disconnected AI sessions with persistent project memory and automatic session handoff, integrating GitHub workflows for context-aware development.

A FastMCP-based server designed for the banking and fintech domains, providing tools for database queries, Git operations, and deployment management. It features a modular architecture with reusable prompt templates and integrated security practices for sensitive data handling.

Enables searching GitHub users and repositories, fetching details, and performing stock market technical analysis via AlphaVantage.

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A persistent, PostgreSQL-backed repository management system and semantic memory MCP server that stores the entire Git DAG natively in PostgreSQL with temporally-decayed semantic vector embeddings for AI IDEs.

Enables querying any GitHub, GitLab, or Bitbucket repository and getting AI-generated answers about the codebase, powered by Gemini.

Enables asking natural-language questions about any GitHub repository and receiving answers grounded in the actual code, with read-only enforcement and automatic repository fetching.

Local-first memory layer for AI coding agents — Markdown as source of truth, MCP server + CLI, human-reviewed capture, team knowledge via git PRs

Enables AI coding agents to persist structured long-term memory (gotchas, architecture, API notes) in a .context folder and sync across devices and agents via Git.

Semantic git queries via MCP. Beyond git log — answer who/what/why about any line, file, or branch with blame, co-change, PR linkage.

Enables natural-language queries about public GitHub repositories, including issues, pull requests, repo metadata, and READMEs, via the GitHub API.

Fetches glasz-style spec files (product.md, tech.md, test-plan.md, and INDEX.md) from GitHub repositories, enabling LLMs to answer questions about features, stories, and acceptance criteria without cloning or pasting files.