temporal-mcp

temporal-mcp

Provides LLM agents with a sense of time between turns via two MCP tools that track elapsed time and day rollover per conversation thread.

Category
访问服务器

README

temporal-mcp

Your model knows calculus but not what day it is. Fix that.

temporal-mcp is a tiny Model Context Protocol server that gives LLM agents a sense of time between turns. Two tools, a few hundred lines, stdlib + mcp + platformdirs. That's the whole thing.

The problem

Open a fresh chat at 11 PM. The model says "good morning." Resume a conversation three weeks later. The model picks up mid-sentence like no time passed. Ask for "today's status." Get yesterday's status. Or last Tuesday's.

LLMs don't have wall clocks. They don't know when the last user message was, whether the calendar flipped, or whether this is a fresh thread or one resumed after a long gap. Most of the time this is harmless. Sometimes it makes your agent sound like it just woke up from cryosleep.

The fix

A persistent per-thread last-seen log, exposed as two MCP tools:

  • temporal_tick — call this once per user turn. Returns "it has been 14 minutes since the last message, no day rollover, timezone MDT" in a format the model can actually read.
  • temporal_peek — same thing, but doesn't advance state. For when you want the gap without claiming a turn.

That's it. Time exists. Your model should know that.

Try it in 10 seconds

curl -s -X POST https://temporal-mcp.dev/mcp \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $(uuidgen)" \
  -d '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{
        "name":"temporal_tick",
        "arguments":{"thread_key":"try-it","tz_offset_minutes":-360,"tz_name":"MDT"}}}' \
| python3 -c 'import sys,json; print(json.load(sys.stdin)["result"]["content"][0]["text"])'

You'll see something like:

[temporal] Wed May 13, 10:42 AM MDT | fresh thread (no prior history)
{...JSON payload...}

Run it twice and the second response shows the gap. Run it tomorrow and you'll get day rollover: yes. That's the whole point.

What you get

Every tick returns a human-readable header and a JSON payload:

[temporal] Wed May 13, 9:42 AM MDT | last prompt 14m ago (Wed 9:28 AM)

{"thread_key": "mcp:abc123", "now": 1747158120.0, "prev": 1747157280.0,
 "delta_sec": 840, "day_rollover": false, "fresh_thread": false,
 "tz_name": "MDT", "tz_offset_sec": -21600, "available": true, "error": ""}

The header is for the model. The JSON is for your code, in case you want to do something interesting with day_rollover (greet differently, reload context, recompute "today's items") or with delta_sec (decay relevance, detect a resumed session, flag idle threads).

Two ways to use it

1. Hosted endpoint — claude.ai, ChatGPT, mobile

If you use claude.ai web, ChatGPT, or anything else that wants a remote MCP server, point your connector at:

https://temporal-mcp.dev/mcp

There are two ways to authenticate, depending on what your client UI exposes:

A. OAuth 2.0 (claude.ai and ChatGPT custom connectors)

Both claude.ai and ChatGPT's custom connector UIs require OAuth 2.0 with a Client ID and Client Secret. The hosted endpoint is a full OAuth provider — visit https://temporal-mcp.dev/connect and click Generate OAuth Credentials. You'll get a fresh client_id + client_secret pair, shown once. Paste them into your client's connector config. That's the entire signup.

No email, no password, no account record — the credential pair is the identity. We store only a SHA-256 of the secret, so we never see the plaintext. Generate a new pair any time you want a fresh timeline.

Claude.ai setup: Settings → Connectors → Add custom connector. URL https://temporal-mcp.dev/mcp. Paste your Client ID and Client Secret. Connect. The auto-approve flow redirects you back, claude.ai exchanges the code for a token, and you're done.

ChatGPT setup: Same idea — Settings → Connectors → Custom MCP. Same URL, same credentials.

B. Raw bearer token (Cursor, Cline, Claude Desktop, Zed, Claude Code)

If your client supports custom HTTP headers (most do), skip OAuth and just send any opaque string as a bearer token:

Authorization: Bearer <any opaque string you choose>

Pick a UUID, a passphrase, anything. We SHA-256 it before storing anything; same identity-is-the-credential property as the OAuth flow, without the dance. This is the original lowest-ceremony path and works for any client that lets you set a custom header.

C. URL-embedded token (xAI, Grok, anything URL-only)

If your client's connector UI only exposes a URL field — no headers, no auth, no OAuth — embed your token directly in the path:

https://temporal-mcp.dev/mcp/<any opaque string you choose>

Or as a query parameter, if the path form gets stripped:

https://temporal-mcp.dev/mcp?token=<any opaque string you choose>

Same SHA-256 hashing, same identity model. URL-embedded tokens leak more easily than header tokens (proxy logs, referrers), so this path is a pragmatic fallback rather than the default — but the threat in our model is "someone advances your timeline," not data exposure. Rotate by picking a new random string any time you suspect the URL has been logged where it shouldn't be.

Either way

No signup. No email. No PII. The hosted endpoint is free, rate-limited to 60 requests/minute per credential. If you outgrow that, self-host (see below).

2. Local stdio — Claude Desktop, Cursor, Cline, Zed, Claude Code

For desktop/IDE MCP clients, pip install the Python package and run it locally. No network round-trip, state lives on your disk, no auth needed.

pip install temporal-mcp

Python 3.9+. Linux, macOS, Windows.

Run as stdio:

temporal-mcp        # or: python -m temporal_mcp

Claude Desktop

{
  "mcpServers": {
    "temporal": {
      "command": "temporal-mcp"
    }
  }
}

Cursor / Cline / anything else that speaks MCP stdio

Same idea — point the client at the temporal-mcp command.

Self-host the remote endpoint (Cloudflare Workers)

The hosted endpoint at temporal-mcp.dev runs on Cloudflare Workers backed by D1. If you want your own instance — for privacy, scale, or to ship it as part of a larger product — the entire deploy lives in workers/:

cd workers
npm install
npx wrangler login
npx wrangler d1 create temporal_mcp           # creates the database
# Paste the printed database_id into wrangler.toml
npx wrangler d1 migrations apply temporal_mcp --remote
npx wrangler deploy

Free tier covers ~100k requests/day forever. Set REQUIRE_AUTH=true in [vars] to refuse anonymous traffic. The Worker is ~400 lines of TypeScript and has its own unit tests (workers/test/).

Tools

temporal_tick

Advance the clock for a thread and return a snapshot. Call once per user turn.

Field Type Notes
thread_key string, optional Stable conversation/session ID. claude.ai web: conversation ID. Cursor: window/workspace ID. Anything else: any caller-stable string. Omit it and you get a default hostname+cwd hash — fine for local testing, not for serving multiple threads.
client_id string, optional Namespace tag (e.g. "caweb", "cursor"). Defaults to "mcp". Use distinct tags per client so threads don't collide in shared state.

temporal_peek

Read-only. Same shape, doesn't advance state. Use it when you want the gap delta but the call isn't the canonical "one tick per user turn" event.

State

Per-thread last-seen state lives at:

Platform Path
Linux ~/.local/share/temporal-mcp/state.json
macOS ~/Library/Application Support/temporal-mcp/state.json
Windows %LOCALAPPDATA%\temporal-mcp\state.json

Override with TEMPORAL_MCP_STATE_DIR=/some/path.

State writes are flock-safe on POSIX and atomically replaced via os.replace, so multiple agents pointing at the same state directory will not corrupt each other. (Windows falls back to an in-process lock — fine for a single MCP server, not designed for cross-process contention.)

Maintenance

python -m temporal_mcp gc        # prune threads > 30d idle
python -m temporal_mcp gc 7      # prune threads > 7d idle

Not exposed as an MCP tool on purpose — a model that can prune its own memory of "when did we last talk" will eventually do it at exactly the wrong moment. Run it from cron if you care.

Design notes (for the curious)

  • Thread keying is namespaced as {client_id}:{key}. Reserve a unique client_id per surface so threads from claude.ai web don't collide with a local Cursor session sharing the same state directory.

  • Failure is honest. If the state file is unreadable or the lock times out, the snapshot returns available: false with an error field and the header says gap: unknown. It does not silently lie and call it a fresh thread — a model that thinks every turn is fresh will keep saying good morning forever.

  • Watchdog. tick() runs in a daemon thread with a 100 ms timeout so a stalled state read can't block your hook budget. If it times out, you get the honest-failure snapshot above.

  • No HTTP transport in 0.1. Stdio only — that's what Claude Desktop, Cursor, and the other major MCP clients actually use. HTTP/SSE can land in 0.2 if there's demand.

Roadmap

  • 0.2 — optional HTTP/SSE transport, conversation-ID auto-resolve from Mcp-Session-Id and friends, configurable timezone override
  • 0.3 — opt-in "long gap" thresholds (return a resume: true flag past N hours) so agents can branch on resumed sessions without doing the math themselves

License

MIT. See LICENSE.

Author

Built by Garret Sutherland / MirrorEthic LLC, extracted from the temporal layer of a larger cognitive-mesh project where this primitive was load-bearing enough to deserve its own package.


<sub>mcp-name: io.github.MirrorEthic/temporal-mcp</sub>

推荐服务器

Baidu Map

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。

官方
精选
JavaScript
Playwright MCP Server

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。

官方
精选
TypeScript
Audiense Insights MCP Server

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。

官方
精选
本地
TypeScript
Magic Component Platform (MCP)

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。

官方
精选
本地
TypeScript
VeyraX

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。

官方
精选
本地
Kagi MCP Server

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。

官方
精选
Python
graphlit-mcp-server

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。

官方
精选
TypeScript
Exa MCP Server

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。

官方
精选
mcp-server-qdrant

mcp-server-qdrant

这个仓库展示了如何为向量搜索引擎 Qdrant 创建一个 MCP (Managed Control Plane) 服务器的示例。

官方
精选
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选