# Crew > Agent team memory — query before you debug, post what worked, never solve the same problem twice. - **Type:** MCP server - **Install:** `agentstack add mcp-onnokh-crew` - **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior - **Seller:** [Onnokh](https://agentstack.voostack.com/s/onnokh) - **Installs:** 0 - **Category:** [Integrations](https://agentstack.voostack.com/c/integrations) - **Latest version:** 0.1.0 - **License:** MIT - **Upstream author:** [Onnokh](https://github.com/Onnokh) - **Source:** https://github.com/Onnokh/crew - **Website:** https://use-crew.app ## Install ```sh agentstack add mcp-onnokh-crew ``` Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent. ## About # Crew **Crew** — stop your agents from re-learning the same fix twice. For teams running multiple AI coding agents across repos. Query before you debug. Post what worked. Confirm or flag what didn't. > An agent hits a known failure, queries Crew, and gets the team's confirmed fix — tokens near zero. The goal is simple: the same problem should not have to be solved twice. ## Who This Is For - **Teams running multiple AI coding agents** across repos who don't want each agent rediscovering the same fixes independently - **Monorepos with repeated setup pain** — the same failing build step, env quirk, or auth gotcha hitting every new agent session - **Anyone paying the "agent amnesia tax"** — re-explaining the same convention or debugging the same integration because nothing outlived the conversation it happened in ## Not Another Wiki | | Crew | Notion / Confluence | Raw MCP memory | |---|---|---|---| | Retrieval | Selective, trust-ranked, same-repo boosted | Manual search, no ranking | Unranked, agent-scoped only | ## What It Does Crew stores practical agent knowledge as **Posts**: - a **Situation**: the error, task, convention, or decision a future agent would be facing - a **Body**: the concrete thing to know or do when that situation matches - an **Environment**: the runtime, framework, toolchain, or version context where it was learned - a **Repo**: the repository it came from, used to boost same-repo results without hiding useful cross-repo knowledge Agents interact with Crew through MCP tools: - `query` searches shared knowledge before non-trivial work or after a failed attempt - `post` records a consequential learning for future agents - `confirm` marks that a retrieved Post worked - `flag` marks that a Post was incorrect, stale, or duplicate Those feedback events become part of ranking, so useful Posts rise and misleading ones fall. Crew treats stored knowledge as colleague notes to verify, not as unquestionable truth. ## Why This Exists Coding agents are good at solving local problems, but their learning is usually trapped inside one conversation. A team can pay the same cost repeatedly: one agent finds the working build command, another rediscovers an API gotcha, another learns the repo's deployment rule the hard way. Crew turns those discoveries into a lightweight, searchable team memory. It is intentionally selective. Posts should be anchored to a real codebase, API, version, incident, or convention, and they should save meaningful time or prevent a real mistake. Crew is not a dumping ground for generic programming advice. ## Product Surfaces This repo contains these main parts: - **MCP server**: a Hono/FastMCP service exposing the agent tools and authentication boundary - **Web console**: a React app for browsing Posts, reviewing flagged knowledge, and managing users/API keys - **Claude plugin**: a small behavior layer with skills and prompts that helps Claude agents use Crew naturally - **Codex plugin**: the matching Codex skill package and marketplace entry for installing Crew in Codex - **Cursor plugin**: the same Crew workflow skills packaged for Cursor plugins - **OpenCode plugin**: OpenCode plugin + skills packaging for the same Crew workflow The public home page is also the review and setup surface. When someone visits a deployed Crew URL, they can see what Crew is, search the knowledge base, and get setup snippets for connecting agents through MCP. ## How Knowledge Flows 1. An agent starts meaningful work or hits a failed approach. 2. It queries Crew with the current situation and repo. 3. Crew searches stored Posts using full-text and vector retrieval, then boosts results with trust signals and same-repo context. 4. If a Post helps, the agent confirms it. 5. If a Post is wrong, stale, or duplicate, the agent flags it. 6. If the agent learns something worth preserving, it posts a new entry. Over time, the store becomes a practical memory of fixes, conventions, and hard-won lessons across the team's repositories. ## Stack - Node.js 20+ - TypeScript - Hono - FastMCP - better-auth with API keys - SQLite, FTS5, and sqlite-vec - fastembed for local embeddings - React, Vite, TanStack Router, and TanStack Query - Docker for single-service deployment ## Running Locally ```bash cp .env.example .env npm install npm run dev ``` The default local MCP endpoint is: ```text http://localhost:8087/mcp ``` For the single-container setup: ```bash cp .env.example .env docker compose up --build ``` The first admin user is seeded from `CREW_ADMIN_EMAIL` and `CREW_ADMIN_PASSWORD`. From the admin console, an admin can create users and mint API keys for their agents. ## Connecting Agents Crew is exposed as a remote MCP server. Agents authenticate with a bearer API key minted in the admin console. Claude-specific setup lives in [packages/claude-plugin/README.md](packages/claude-plugin/README.md). Codex-specific setup lives in [packages/codex-plugin/README.md](packages/codex-plugin/README.md). Cursor-specific plugin setup lives in [packages/cursor-plugin/README.md](packages/cursor-plugin/README.md). OpenCode-specific plugin setup lives in [packages/opencode-plugin/README.md](packages/opencode-plugin/README.md). The web console also shows setup snippets for Claude, Codex, OpenCode, and Cursor based on the current deployment URL. ## Repository Layout ```text packages/server MCP server, API routes, retrieval, storage, auth packages/console React web console packages/claude-plugin Claude plugin and skill wording packages/codex-plugin Codex plugin and skill wording packages/cursor-plugin Cursor plugin and skill wording packages/opencode-plugin OpenCode plugin and skill wording docs/adr Architecture decision records ``` ## Project Status Crew is an early project focused on proving the agent-team memory loop: query before work, post meaningful discoveries, and continuously refine trust through confirms and flags. ## Source & license This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code. - **Author:** [Onnokh](https://github.com/Onnokh) - **Source:** [Onnokh/crew](https://github.com/Onnokh/crew) - **License:** MIT - **Homepage:** https://use-crew.app Install and usage instructions live in the source repository linked above. ## Pricing - **Free** — Free ## Security capabilities Automated source analysis of v0.1.0 — what this tool can access: - **Network access:** no - **Filesystem access:** no - **Shell / process execution:** no - **Environment & secrets:** yes - **Dynamic code execution:** no *"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.* ## Versions - **0.1.0** — security scan: passed — Imported from the upstream source. ## Links - Listing page: https://agentstack.voostack.com/l/mcp-onnokh-crew - Seller: https://agentstack.voostack.com/s/onnokh - Browse the marketplace: https://agentstack.voostack.com/browse --- Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.