"Local AI Agent Toolkit" matching MCP servers:

Local-only MCP server for saving and restoring conversation context across AI agent sessions using JSON files on disk.

Provides persistent, searchable memory across AI coding agent and chat history (Claude Code, Codex, Gemini CLI, ChatGPT, and more) via retrieval-augmented generation, enabling semantic and hybrid search to retain context across sessions.

Local-first memory engine for AI-agent teams: private/team/project ACL, associative recall, and federated sync across nodes. One SQLite file, no LLM required.

Enables agents to share state via a blackboard, record and retrieve failure resolutions, and cache LLM responses to avoid redundant API calls.

Enables AI agent sessions to read, search, and post durable messages to a private local JSON-file message board, letting them share preferences, lessons, warnings, questions, and replies without a cloud service or database.

A local-first MCP memory server that gives AI coding agents persistent memory with hybrid semantic and keyword retrieval, working fully offline.

Provides AI assistants with intelligent access to ML textbook content for creating accurate, source-grounded documentation using local models for privacy and cost efficiency.

An MCP server that provides shared memory, kanban board, and agent registry for AI agents to collaborate as a team, with a live dashboard for human oversight.

Enables searching, indexing, and recovering past AI chat sessions and agent actions from local AI coding tools, with optional vector database semantic search and direct filesystem access.

A local MCP server for RGPD-compliant document Q&A, enabling Claude Code to ingest, query, search, delete, and audit personal documents entirely on-device.

A local MCP server that gives AI coding agents persistent memory and context across sessions.

Enables semantic search over local AI-agent session logs (e.g., Claude Code, Hermes) using local embeddings, returning relevant chunks without exposing full transcripts.

Built-in MCP server that gives AI agents direct access to an Obsidian vault for reading, writing, searching notes, and executing commands.

An enterprise MCP server that exposes 16 standardized tools for document intelligence, RAG, knowledge graph, SQL analysis, LLM evaluation, cost estimation, and AI architecture design, enabling AI agents to securely access and compose enterprise AI capabilities.

An always-on AI chief-of-staff that manages tasks, calendar, notes, habits, and more through chat, with a private markdown vault and multimodal tools.

Read-only MCP server for a local-first supply chain knowledge base, enabling knowledge search with source evidence, internal system troubleshooting, vendor documentation fallback, vessel tracking, and work handoff preparation.

A local-first MCP server that manages developer memory for coding agents, enabling shared project context, permissions, and audit trails across different agents.

Enables AI agents to interact with any website through MCP, providing structured knowledge graph contexts, generated actions, and readiness scoring.

Engram is a local-first memory server that lets AI agents remember things across sessions with zero cloud dependencies.

Provides versioned, structured memory for AI agents, allowing them to store facts, detect conflicts, and track knowledge history via a hosted SaaS platform. It enables efficient hierarchical information retrieval and semantic search while keeping token usage constant as memory scales.