"GNOME Terminal" matching MCP servers:

Records your terminal sessions per command (PTY + OSC 133) into local SQLite, so AI agents can search, retrieve, and diff what commands actually printed. Secret redaction is applied by default to everything served over MCP.

Enables Claude Code with persistent semantic memory, cross-session context, and memory hygiene via a local AD4M executor, offering 13 tools for managing semantic graphs and cross-terminal relay.

Enables AI agents and WSL/Linux terminal users to connect to a Windows Obsidian vault via the Local REST API, supporting note reading, creation, updates, search, file listing, tags, and command execution.

A fully-local AI memory system that saves notes, code, and terminal output to a vector database via Ollama and LanceDB, enabling context retrieval from terminal, API calls, or inside Claude Code.

Enables AI agents to share a persistent, self-learning memory by ingesting and classifying knowledge from Obsidian, code, transcripts, bookmarks, and terminal sessions, then retrieving token-optimized context through MCP and REST APIs.

An agent-capable MCP server with terminal access, filesystem control, and persistent memory. It includes sandboxing, access control, activity logging, and a file-backed memory store for context across conversations.

Enables AI agents to share persistent, searchable memory across sessions by ingesting and organizing knowledge from sources like Obsidian, code, transcripts, and terminal sessions. It provides token-optimized retrieval, semantic and keyword search, and MCP/REST access so agents can capture, classify, synthesize, and reuse context.

Enables AI agents to capture, classify, synthesize, and retrieve persistent knowledge from sources like Obsidian, code, web clippings, transcripts, bookmarks, terminal sessions, and fixes, using FTS5 and semantic search through MCP and REST interfaces.

Enables AI coding agents to declare and maintain a live, layered dependency map during bottom-up development, exposing eight mmap_* tools that ghost the intended design first and then light nodes up as they are built and verified in a terminal pane beside the conversation.

Enables AI agents to share persistent memory by ingesting knowledge from sources like Obsidian, code, documents, web clips, and terminal sessions, then providing token-optimized search, context, classification, synthesis, and capture tools through MCP and REST APIs.

Enables AI agents with persistent memory using SQLite and local LLM models through Ollama integration. Provides chat with context retention and multi-client support across VS Code, Gemini-CLI, and terminal interfaces.

Enables AI agents to capture, classify, synthesize, and retrieve persistent knowledge through MCP and REST APIs, so multiple agents can share memory and improve across sessions. It provides full-text, semantic, and hybrid search with token-optimized context retrieval from sources like Obsidian, code, transcripts, and terminal sessions.

Enables AI agents to capture, classify, promote, synthesize, and retrieve persistent knowledge from sources such as Obsidian vaults, code repos, YouTube transcripts, bookmarks, terminal sessions, and bug fixes. Exposes tiered cold/warm/hot memory with token-optimized search, context briefings, and cross-source synthesis so multiple agents share one compounding brain across sessions.

Enables AI coding assistants like Claude Code, Cursor, and Codex to share chat logs, terminal history, and session context with each other. Eliminates the need to re-explain context when switching between different AI coding tools.

Enables AI agents to share persistent, self-improving memory by ingesting, classifying, synthesizing, and retrieving knowledge from sources such as Obsidian vaults, code, transcripts, bookmarks, and terminal sessions through MCP and REST APIs.

A local, offline memory server for AI agents that stores and retrieves memories without LLM calls, enabling persistent cross-session memory with bi-temporal querying and auditable records.

Gives a remote MCP client one read-only tool for asking a locally running Hermes Agent short questions, answered with that machine's own memory and session context, over bearer-authenticated Streamable HTTP. It exposes no terminal, file writes, messaging, or other action capability, and every other request is refused upstream of the model.

A task-aware transparent proxy that wraps stdio MCP servers (such as git, filesystem, and terminal) and compresses large tool outputs field-by-field using declarative YAML profiles, passing narrow intent queries through untouched. Discarded data is stored in SQLite and can be losslessly retrieved via an injected tool, either in full, by line range, or by grep, while errors are always preserved and failures fall back to the raw result.

Lets an AI coding agent declare a system's layered dependency graph up front as ghost nodes, then light each node up as code is built and verified, with a live terminal pane showing spinners on active work and red on cracked foundations. It exposes eight mmap_* tools so structural rules — downward-only edges and unique ranks — are enforced as the design ledger.

An MCP server that lets Claude Code, Codex, pi, omp and other MCP clients declare and maintain a live layered dependency map of a system, exposing eight mmap_* tools to add ghost nodes, draw downward-only edges, and light nodes up as built and verified. It turns bottom-up progress into a shared ledger in a terminal pane beside the conversation, marking nodes red when later work cracks a foundation.