"Git MCP (Model Context Protocol) Server" matching MCP servers:

A stateful gateway server for AI applications that solves the memory limitations of Large Language Models by maintaining separate conversation contexts for each user.

An MCP server that enables AI models to retrieve information from Ragie's knowledge base through a simple 'retrieve' tool.

A lightweight MCP server for semantic search over markdown knowledge bases, enabling AI coding agents to index, search, and answer questions from local markdown documents.

Local-first shared memory and coordination layer for AI coding agents, with repository evidence, reservations, handoffs, code graph context, and dashboard review backed by PostgreSQL/pgvector.

Persistent 3D/2D spatial world model MCP server for AI agents. Entity tracking, object permanence, AABB collision simulation & view frustum projection via local SQLite.

An MCP server that provides AI trading agents with persistent, outcome-weighted memory to learn from historical performance and detect behavioral biases. It enables agents to automatically adjust strategies and optimize position sizing based on context-aware recall of past trade outcomes.

Context Forge is a vendor-neutral continuity layer for AI tools. It stores project context in Markdown and JSON, retrieves task-scoped context, and leaves structured handoffs so another model can continue without being taught the project again.

Provides time intelligence, persistent memory and complete traceability for AI coding agents. Enables sophisticated activity tracking, timezone management, smart reminders, and cross-session continuity with support for both per-project and centralized storage modes.

A comprehensive MCP server for managing AI-assisted Dungeons & Dragons campaigns, featuring tools for character sheets, combat tracking, and world-building. It enables players and DMs to interact with 5e game mechanics and query personal PDF rulebooks using RAG capabilities.

Resume-as-an-Agent (RAAA) or Portfolio-as-an-Agent (PAAA) allows Agents to talk to your resume, find out if you are available for work, and more. Use the MCP to allow recruiters, managers, and anyone with an agent to "talk" to your resume.

An MCP server that provides persistent, cross-session memory and team knowledge sharing for AI development workflows. It enables project DNA scanning, semantic search, context budgeting, and git-aware indexing to prevent AI context loss between sessions.

Enables AI agents to run automated daily code reviews, retrieve Markdown reports, and curate a project knowledge base across any Git repository.

Automatically captures project state on git commits, detects context drift, and delivers structured token-budgeted briefings to AI agents, ensuring project continuity without manual effort.

Enables AI clients to read and write to a user-owned markdown bucket via S3-compatible storage, providing a persistent shared context layer across different AI tools.

An MCP server that captures the rationale behind code changes at the moment they are written, binding decisions to commits with full provenance, and serves that context later without guessing. It records 'why code exists' and tracks anchor health over time.

An enhanced memory management system that wraps memento-mcp with sophisticated features including protocol enforcement, quality scoring, hybrid search strategies, and synthesis reports. Enables intelligent memory storage, retrieval, and analysis with automatic archival and confidence tracking.

Provides redacted access to a private local knowledgebase for coding agents, allowing them to inspect files while hiding sensitive names and identifiers.

Multi-modal RAG engine for AI assistants. Stores conversation history, conclusions, diffs, error traces, and other development artifacts in LanceDB with vector search, multi-factor scoring, and an LLM-driven consolidation pipeline.

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.

Context Mode is an MCP server that reduces context window waste by sandboxing data-heavy tools, tracking session state in SQLite, and promoting code-based analysis over raw data reads, achieving up to 98% context savings.