"An in-memory data store for caching and message brokering" matching MCP servers:

An MCP server that lets AI agents register a name and bio, discover one another, exchange messages, and be woken when mail arrives rather than polling, backed by a shared SQLite database over stdio for one machine or HTTP for a team.

Enables coding agents to coordinate in spaces through direct messages, topics, blackboards, and durable inboxes, exposing bus tools over MCP and RPC while pushing inbox updates over SSE.

Enables independently operated AI clients to exchange private 1:1 messages and files using authenticated participant identities, with retry deduplication, status tracking, notifications, and owner conversation inspection. Provides REST and MCP tools for messaging, attachments, subscriptions, and replay.

Enables MCP clients and webhook-driven agents to exchange durable messages with atomic claim, completion, and acknowledgement workflows, plus verified webhook event subscriptions and native wake-ups.

MCP server for managing and controlling multiple isolated Chrome/Edge browser instances, exposing tools for navigation, screenshots, clicking, form filling, and JavaScript execution to AI clients.

Enables Codex to rank available tools and skills, rerank code and documentation search results, and triage saved output artifacts using Jev-based relevance scoring while leaving final decisions to Codex.

An MCP relay that adds a use_jev tool to every connected server, letting the Jev model autonomously select and execute tool calls while the calling model supplies any required text values. It enables agents to delegate multi-step tool use across all configured MCP servers through a single unified interface.

Enables Codex to manage a local Claude Code companion through MCP, implementing a dual-agent workflow where Codex handles reasoning and review while Claude Code performs engineering tasks.

Enables Claude Code to control Firefox through tools for tabs, navigation, clicks, typing, scrolling, screenshots, page reading, forms, JavaScript, and console/network logs.

Enables AI agents to browse a yoga apparel catalog and complete purchases through authenticated JSON/MCP checkout, with identity, mandate, budget, and payment gates.

Enables users to describe an LLM fine-tuning workload once and receive ranked, task-aware GPU recommendations across a dozen cloud providers based on required VRAM/FLOPs, cost, and runtime. It surfaces the cheapest, fastest, and balanced options through MCP so coding assistants can plan training hardware without manual price comparison.

Enables building and evaluating LangGraph agents over a protocol-level MCP server to measure failure rates across four agent topologies.

An advanced contextual memory server for agent orchestration providing chronological history, semantic vector search via Redis Stack, and temporary scratchpad storage. It also enables context compression through history rollups and facilitates inter-agent communication using a Redis-based Pub/Sub system.

Enables ZCode to control a real Chrome browser, including tabs, navigation, page content, clicks, form filling, keyboard input, scrolling, screenshots, and JavaScript evaluation through a local MCP bridge.

Wraps a dependency-free memory lifecycle engine as six read-only MCP tools, letting any agent extract facts with pure regex, score signals, compute Ebbinghaus decay and archival judgments, and simulate a full five-stage dream cycle for long-term memory growth. Runs over stdio or streamable HTTP with no API key, storing no caller data.

Enables OpenAI-compatible clients to access external tools, APIs, repositories, and data sources through MCP with allowlisting, approval, and argument validation, deployable as a FastAPI service or Python library.

A shared memory and coordination server for multiple AI coding agents, built on the Model Context Protocol (MCP).

Provides MCP tools for persistent, cross-session memory via Cloudflare Agent Memory, enabling agents to store, recall, ingest, summarize, and manage memory namespaces.

Provides a shared memory bridge for AI agents (QClaw, Claude Code, Codex) allowing them to store, search, and retrieve notes, decisions, and conclusions via MCP tools, using local SQLite with optional TencentDB integration.

Proxies every Playwright MCP tool so agents drive a real browser, while automatically attaching per-site lessons, self-firing fixes, saved procedures and the site's observed internal API to each navigation. Later sessions on the same domain start where the previous one stopped, without anyone having to write or request the notes.

An enhanced MCP server that provides intelligent memory and task management for AI assistants, featuring semantic search, automatic task extraction, and knowledge graphs to help manage development workflows.

Enables AI tools and agents to share a persistent memory space, so a decision, task, or encrypted secret saved in one client can be searched, recalled, and handed off from another. It also tracks goals day by day, moves unfinished work between sessions, and keeps exports, trash recovery, and per-account isolation under the user's control.

A lightweight MCP server that records and reuses prompt gaps — essential context missing from initial instructions — so your AI assistant learns from every session using a plain JSONL file tracked by Git.

Provides a centralized MCP-based system for managing and accessing multi-project memory banks remotely, with features like project isolation, file structure validation, and type-safe operations.

A persistent memory implementation using a local knowledge graph that lets Claude remember information about users across conversations.

Provides a shared context layer for AI agent teams to improve token efficiency through context deduplication and incremental state sharing. It enables multiple agents to coordinate tasks, share real-time discoveries, and manage dependencies while significantly reducing redundant data transmission.

Enables AI agents to drive real Google Chrome with stealth and captcha handling, using Patchright to avoid bot detection.

Enables MCP-compatible agents to recall approved durable memory and propose new or replacement memories for review, without granting direct write or administrative access.

Enables AI agents to persist and share durable memory — appending session logs with checkpoints and handoffs, claiming and completing tasks, and recording decision records — all stored as plain Markdown and JSONL files in a git repository. Everything written is full-text searchable, and the server speaks MCP so MCP-aware clients can plug in directly with zero vendor lock-in.

Enables Claude Code sessions to persist and share context by saving, searching, organizing, checkpointing, and restoring work history, decisions, and progress across sessions and parallel assistants.