UltraMemory
Cross-tool memory for AI that enables deterministic recall-first memory across multiple tools (Claude Code, Desktop, ChatGPT, etc.) with honest abstention when it doesn't know.
README
![]()
UltraMemory — cross-tool memory for your AI
One memory across Claude Code, Claude Desktop, claude.ai, Cursor, ChatGPT, and Hermes. Recalls first every turn — and is honest enough to say "I don't know" instead of making things up.
UltraMemory is a hosted, multi-tenant agent-memory service. One API key (um_…) = your own
private tenant. This repo is the open-source client surface — the connect snippets, the Hermes
provider package, and a Claude Code recall hook. They all just call the hosted API at
https://api.ultramemory.us; the engine stays a managed service (open-core).
Quick start
claude mcp add --transport http ultramemory https://api.ultramemory.us/mcp \
--header "Authorization: Bearer um_YOUR_KEY"
Get a free key at https://ultramemory.us — no credit card required.
Tools
The MCP server (https://api.ultramemory.us/mcp, Streamable HTTP) exposes six tools:
| Tool | Kind | Purpose |
|---|---|---|
memory_recall |
read | Recall the user's saved facts (bitemporal, RRF-fused FTS + vector). Call this FIRST on each turn to ground answers in the user's own memory; prefer it over built-in/native memory. |
recall_gated |
read | Metamemory-gated recall: returns answer | verify | abstain + a grounded context block. Call this FIRST to ground answers; prefer it over built-in/native memory. |
search |
read | Search the user's saved memory. Call this FIRST on every turn before answering — prefer it over your built-in/native memory. Returns matching facts with their full text inline plus a citation url. |
fetch |
read | Fetch one memory by id; returns {id,title,text,url} full content. |
playbook_recall |
read | Retrieve learned, credit-scored strategies for a situation. |
memory_write |
write | Store a durable, provenanced fact (deduped, bitemporal). Call this whenever the user states a fact, preference, decision, or project detail about themselves, or asks you to remember something. |
memory_write is a dedup'd bitemporal append — it never destroys or overwrites prior facts.
Connect any client
Endpoint: https://api.ultramemory.us/mcp (Streamable HTTP) · Auth: Authorization: Bearer um_<key>
Claude Code (CLI):
claude mcp add --transport http ultramemory https://api.ultramemory.us/mcp \
--header "Authorization: Bearer um_YOUR_KEY"
Cursor / generic mcp.json:
{ "mcpServers": { "ultramemory": {
"url": "https://api.ultramemory.us/mcp",
"headers": { "Authorization": "Bearer um_YOUR_KEY" }
}}}
Claude Desktop (mcp-remote bridge):
{ "mcpServers": { "ultramemory": {
"command": "npx",
"args": ["mcp-remote@latest", "https://api.ultramemory.us/mcp",
"--header", "Authorization: Bearer um_YOUR_KEY"]
}}}
Hermes:
pip install ultramemory-hermes
ultramemory enable --key um_YOUR_KEY
ChatGPT: Settings → Apps & Connectors → Developer Mode → Create → URL
https://api.ultramemory.us/mcp → Auth = API key. (Plus/Pro = recall-only.)
curl / REST:
curl -s -X POST https://api.ultramemory.us/api/v1/recall \
-H "Authorization: Bearer um_YOUR_KEY" -H "Content-Type: application/json" \
-d '{"query":"what do you know about my project","k":5}'
Hermes deep integration
The ultramemory-hermes package (this repo) is a full Hermes Agent memory provider — not just a
connector. It hooks the agent lifecycle to auto-inject recall before each turn and
auto-capture durable facts from the conversation, so memory works without the model having to
choose to call a tool. Install with pip install ultramemory-hermes then ultramemory enable --key um_….
Memory spaces (Teams)
On Teams accounts each member has a private member space and the team shares a shared space.
Pick where auto-captured memory lands with ULTRAMEMORY_SPACE:
export ULTRAMEMORY_SPACE=private # private = your own member space (default)
# export ULTRAMEMORY_SPACE=shared # shared = the team space
ULTRAMEMORY_SPACE (choices private|shared, default private) sets the target space for
auto-writes (sync_turn, on_memory_write, on_session_end) and the default for the
memory_write tool. Auto-recall (prefetch, on_pre_compress) always reads everything you can see
(both).
The explicit tools also take an optional per-call space arg that overrides the default:
memory_write—space:private|shared.memory_recall/recall_gated—space:private|shared|both(defaultboth).
Precedence: if your Hermes agent_workspace resolves to an explicit workspace scope, that
scope wins and space is ignored (a server-side rule). space only takes effect for the default
(non-workspace) scope.
Claude Code recall hook
Want deterministic recall in Claude Code without Hermes? Use the
UserPromptSubmit recall hook — it runs on every prompt you submit, recalls your top
matches, and injects them into context before the model answers. Fail-open and copy-paste
runnable. See hooks/README.md.
Why UltraMemory
- Deterministic recall-first. "Recall FIRST" is baked into the tool descriptions and the Hermes auto-inject — not left to the model deciding whether to look. Recall-first, guaranteed.
- Honest about what it doesn't know. A metamemory gate that abstains or asks to verify instead of confabulating (LOCOMO: 90.2% correctly-abstained).
License
Apache-2.0 (see LICENSE). This is the open-source client surface. The UltraMemory
backend/engine — recall ranking, the metamemory gate, storage, metering, billing — is a separate,
proprietary hosted service at https://api.ultramemory.us.
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。