rafter-mcp
Rafter — shared memory, skills and agents for your team
Rafter is a hosted MCP server that gives your whole team one shared brain across the AI tools you already use. Capture how your team actually solves tasks — as memories, skills and agents — and every teammate's Claude, Cursor or ChatGPT session starts with that context instead of a blank slate.
https://app.heyrafter.xyz/api/mcpRemote server, Streamable HTTP transport, OAuth 2.1 sign-in (browser flow, dynamic client registration — no API keys to paste).
Connect
Claude Code
claude mcp add --transport http rafter https://app.heyrafter.xyz/api/mcpClaude Desktop / claude.ai — Settings → Connectors → Add custom connector → paste https://app.heyrafter.xyz/api/mcp.
Cursor — add to ~/.cursor/mcp.json:
{
"mcpServers": {
"rafter": { "url": "https://app.heyrafter.xyz/api/mcp" }
}
}ChatGPT — Settings → Connectors → enable Developer mode → Create a connector with the same URL.
Anything else that speaks MCP — point it at the URL above; the server handles the OAuth dance.
First connection opens a browser sign-in (Google, GitHub or email) and a consent screen scoped to one of your workspaces.
Related MCP server: BaseMouse
Tools
Tool | What it does |
| Full-text + entity search across your workspace's memories, skills and agents |
| Fetch one artifact with its graph edges ( |
| Write a durable team learning back from any session |
| Create or update a skill / agent / memory (versioned) |
| Read, browse and remove artifacts |
| Set up shared spaces |
| Bring the team in, manage roles |
| Current user + workspace context |
Artifacts are versioned, and [[wiki links]] between them resolve into a real graph — so fetch returns not just the document but what it cites and what cites it.
What teams use it for
Stop repeating yourself: decisions, conventions and gotchas written once, recalled in every teammate's session.
Turn one person's workflow into everyone's skill: capture the steps that worked, run them from any MCP client.
Onboarding: new teammate connects, asks "how do we do X here", gets the team's actual answer.
Install the Rafter skill
Two ready-to-use files make your AI actually use the shared brain instead of guessing:
skill/SKILL.md— a Claude Code skill: drop it into.claude/skills/rafter/SKILL.mdin your project (or~/.claude/skills/rafter/) and your agent searches Rafter before answering "how do we do this" questions, and writes learnings back.examples/startup-prompt.md— a startup prompt to paste into any tool's project/system instructions for the same behavior without skill support.
Links
Site: heyrafter.xyz
Pricing: heyrafter.xyz/pricing
Privacy: heyrafter.xyz/privacy
The hosted server itself is closed-source; this repository is its public home — docs, connect snippets, and the place to open an issue.
This server cannot be deployed
Maintenance
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Related MCP Servers
- AlicenseAqualityCmaintenanceLocal-first, source-traceable memory for AI agents — no LLM at ingest, $0 per message, zero data egress. Gives Claude Code, Cursor, and any MCP client one shared persistent memory with semantic recall, belief revision, selective forgetting, and a provenance guard that blocks acting on stale or unconfirmed memories.2315MIT
- AlicenseAqualityBmaintenanceShared, versioned memory for your agents across Claude Code, Cursor, Kiro and Grok. One MCP server, sourced answers, full history.3MIT

Ambientofficial
AlicenseNot gradedqualityBmaintenanceEnables AI apps like Claude, ChatGPT, Copilot, Claude Code and Codex to read and write a shared company wiki over MCP, where meetings, work sessions and notes become living pages about people, projects and decisions. It also serves search, briefs, transcripts, decisions and action items, and lets teams connect their own git-hosted team wiki.1MIT- AlicenseAqualityAmaintenanceGives any MCP client (Claude, ChatGPT, Cursor, and others) one shared knowledge-graph memory where agents record decisions, problems, and approaches together with their reasoning, then retrieve them by meaning rather than keyword. Spreading activation pulls in linked context and decay lets unused knowledge fade without deleting it.918Apache 2.0