agentprofile
RemoteAbout agentprofile
agentprofile is an open-source remote MCP service that syncs skills and memory across agent tools through one profile, with a live dashboard. It can be self-hosted on Cloudflare; zero-knowledge credential handling is listed for a later phase.
Key features
- 01Sync skills and memory across agent tools
- 02Remember, recall, and forget facts
- 03Manage skills and retrieve context
- 04View and edit through a live dashboard
- 05Auto-detect and configure clients with the CLI
- 06Authenticate with OAuth or bearer tokens
Use cases
- 01Share preference memories across coding tools
- 02Save and retrieve agent memory across sessions
- 03Edit skills and memories in the dashboard
- 04Deploy the service on a personal Cloudflare account
MCP support
It provides a remote MCP service over Streamable HTTP, with tools to get context, list and retrieve skills, and remember, recall, or forget information. MCP clients can connect using OAuth or a bearer token.
Configuration
Remote servers need no local install. Pick your client, then copy the config or install in one click.
https://agentprofile.everyai-com.workers.dev/mcpclaude mcp add --transport http everyai-com-agentprofile https://agentprofile.everyai-com.workers.dev/mcp{"mcpServers":{"everyai-com-agentprofile":{"type":"http","url":"https://agentprofile.everyai-com.workers.dev/mcp"}}}Open in Cursor{"servers":{"everyai-com-agentprofile":{"type":"http","url":"https://agentprofile.everyai-com.workers.dev/mcp"}}}Open in VS Code{"mcpServers":{"everyai-com-agentprofile":{"type":"http","url":"https://agentprofile.everyai-com.workers.dev/mcp"}}}{"mcpServers":{"everyai-com-agentprofile":{"serverUrl":"https://agentprofile.everyai-com.workers.dev/mcp"}}}Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.
Tools
Details
From the project READMEagentprofile
Your agent's identity, everywhere. One profile — skills, credentials, and memory — synced to every agent tool through a single MCP URL. Open source, zero-knowledge, and self-hostable on your own Cloudflare account.
Every AI tool you use — Claude Code, Cursor, Codex — starts from zero: its own skills, its own pasted API keys, its own amnesia. agentprofile gives them one shared brain.
Live now: hosted at https://agentprofile.everyai-com.workers.dev · dashboard at
/app
Connect (any MCP client)
The server is a remote MCP server (Streamable HTTP) — no install needed, just one URL:
https://agentprofile.everyai-com.workers.dev/mcp
It supports two ways to authenticate:
- OAuth (recommended) — clients that support MCP OAuth discover it automatically from the URL and show a consent screen.
- Bearer token — run
npx @magicteams_ai/agentprofileto get a token, or hitPOST /profiles.
Claude Code
claude mcp add --transport http agentprofile https://agentprofile.everyai-com.workers.dev/mcp
Or with a bearer token:
claude mcp add --transport http agentprofile https://agentprofile.everyai-com.workers.dev/mcp \
--header "Authorization: Bearer ap_…"
Cursor / other mcp.json clients
{
"mcpServers": {
"agentprofile": {
"url": "https://agentprofile.everyai-com.workers.dev/mcp",
"headers": { "Authorization": "Bearer ap_…" }
}
}
}
Codex CLI
export AGENTPROFILE_TOKEN="ap_…"
codex mcp add agentprofile --url https://agentprofile.everyai-com.workers.dev/mcp --bearer-token-env-var AGENTPROFILE_TOKEN
Or, for a client that does OAuth discovery:
codex mcp add agentprofile --url https://agentprofile.everyai-com.workers.dev/mcp
VS Code / Copilot
{
"servers": {
"agentprofile": {
"type": "http",
"url": "https://agentprofile.everyai-com.workers.dev/mcp"
}
}
}
Or just run npx @magicteams_ai/agentprofile and it configures every client it finds.
60-second demo
npx @magicteams_ai/agentprofile
That creates an anonymous profile (no signup) on the hosted instance, auto-detects your installed MCP clients, and writes their config. Restart your tools, then:
- In Claude Code: "Remember that I prefer pnpm over npm."
- In Cursor: "What package manager do I prefer?"
It recalls it. That's your profile, everywhere.
What's in this repo (Phase 1)
This is the Phase 1 implementation from the master plan: a working end-to-end skeleton that syncs skills and memory across tools over MCP. Credentials (zero-knowledge), OAuth, semantic recall, and the skill registry land in later phases — see Roadmap.
| Path | What it is |
|---|---|
apps/worker | The Cloudflare Worker: a remote MCP server backed by one Durable Object per profile (SQLite for memory, R2 for skill bundles), plus a landing page (/) and a live dashboard (/app) with real-time WebSocket sync. |
packages/cli | The agentprofile CLI: instant-profile onboarding, client auto-config, doctor, skill add. |
Web UI
/— landing page with the one-command install and the pitch./app— live dashboard. Paste your token (or hit "Create new") and watch skills and memory update in real time: when any agent callsremember, the fact appears instantly over a WebSocket. Add or delete memories and skills right from the page./setup-prompt— the "set up with your agent" prompt: paste it into Claude Code or Cursor and your own agent installs and verifies agentprofile for you.
How it works
agent tool ──Streamable HTTP──▶ Worker ──idFromName(profileId)──▶ ProfileDO
(Claude Code / Cursor) /mcp per-user SQLite
• facts (memory)
• skills
- One Durable Object per user is the source of truth. It validates the profile's secret on every call and owns that profile's memory and skills.
- Bearer token =
ap_<profileId>.<secret>. TheprofileIdroutes to the DO; the DO verifies a SHA-256 hash of the secret. No central token table. - The MCP surface is 6 tools:
get_context,list_skills,get_skill,remember,recall,forget. Deliberately small — every description byte is paid on every client turn (pinned in tests).
Run it locally
npm install
npm run dev # starts the Worker on http://localhost:8787
In another terminal:
# point the CLI at your local server
AGENTPROFILE_SERVER=http://localhost:8787 npx @magicteams_ai/agentprofile
Run the tests and typecheck:
npm --workspace apps/worker run test
npm --workspace apps/worker run typecheck
Deploy your own (self-host)
agentprofile self-hosts on your own Cloudflare account — the free Workers tier covers personal use.
cd apps/worker
npx wrangler r2 bucket create agentprofile-bundles
npx wrangler deploy
# then set PUBLIC_BASE_URL to your deployed URL and connect with:
AGENTPROFILE_SERVER=https://agentprofile.<you>.workers.dev npx @magicteams_ai/agentprofile
Roadmap
- P1: MCP server + ProfileDO, 6 tools, memory + skills, instant-profile CLI, live dashboard. ✅
- P2: per-client grants + audit log with live enforcement + dashboard access panel ✅; MCP sessions (
Mcp-Session-Id) ✅; semantic recall via Workers AI embeddings (keyword fallback) ✅; pluggable memory providers (builtin default + Mem0 + Supermemory adapters,/memory-config) ✅; OAuth 2.0 + PKCE consent flow with discovery, dynamic registration, and consent screen ✅. - P3: zero-knowledge credentials (client-side E2E), JIT injection, approval flow.
- P4: one-click Deploy-to-Cloudflare, signed skill registry, format translators.
- P5: teams, SSO, hosted cloud.
See the full plan in docs/.
Contributing
Contributions are welcome under the DCO —
sign off commits with git commit -s. See SECURITY.md for
responsible disclosure.
License
Part of the everyai-com agent stack
Open-source infrastructure for local-first, governed AI agents:
- distillory — local-first memory engine that reasons at ingestion
- agent-ready — turn any app into an MCP server + API + CLI, safe by default
- primer — live business context injected into any agent
- plainsync — local-first Markdown workspace for humans + agents
- argus — cloud-native software verification with parallel browser testing
- mintly-alternative — self-hostable documentation layer for humans + AI agents
- talltrack — sales calls in, publishable content out
Built by Phanindra Reddy · magicteams.ai
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.