Agent-Native Calendar
Agent-Native Google Calendar - manage events, sync, and public booking
作者提供的说明(英文原文)
Private-by-default, local-first memory/context/task orchestrator for MCP apps and agents.
这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。
我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。
选择你使用的 AI 应用,然后复制设置。
你需要
你用的是哪个应用?
在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。
适用于网页版、桌面版和手机版 Claude:
https://contextlattice.io/mcp在终端中运行这条命令
claude mcp add --transport http contextlattice https://contextlattice.io/mcp粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"contextlattice": {
"url": "https://contextlattice.io/mcp"
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"contextlattice": {
"type": "http",
"url": "https://contextlattice.io/mcp"
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
ChatGPT 只能连接互联网上的服务器:
https://contextlattice.io/mcp菜单名称可能因套餐和版本不同而略有差异。
你的选择通过 Cookie 保存在这台设备上,无需账户。
这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。
我们还没有读取这个服务器的工具列表;我们会轮流检查各个端点。
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日
注册名称已通过 GitHub 账户 sheawinkler 验证,该账户拥有此仓库
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
尚未检查;我们会轮流检查各个端点
尚未检查;我们会轮流检查各个端点
尚未检查;我们会在检查端点时读取工具列表
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。
它在作者的云端运行。通过互联网连接,无需安装,但你发送的内容会经过作者的服务器。
GitHub 仓库最后更新于–,最新版本(1.0.0)于9个月前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。它通过 URL 连接,所以接受远程 MCP 服务器的应用也可以使用,例如开启开发者模式的 ChatGPT。
同一分类中有:Agent-Native Calendar, Excel MCP Server, MCP Server for Excel
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i
Agent-Native Google Calendar - manage events, sync, and public booking
Create and edit Excel files with AI: charts, PivotTables, formulas. No Excel needed.
Excel automation for AI - Sheets, Power Query, DAX, VBA, Tables, Ranges and more. Windows only.
按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。
Open an agent. Already there.
The local-first intelligence layer that gives AI agents durable continuity, explainable retrieval, portable context, and verified learning across harnesses.
Quickstart · How it works · Agent setup · Architecture · Docs · Updates
Models can reason. Harnesses can act. Neither reliably retains the mission when a chat, model, tool, account, or computer changes.
ContextLattice gives that work a durable, inspectable context layer. It reconstructs the active objective, selects the evidence that matters, carries it safely, and records what actually worked—without turning every prompt into a transcript dump or making cloud storage mandatory.
| Capability | What changes |
|---|---|
| Durable continuity | Reopen the objective, decisions, repository state, risks, proof, and next move as one bounded packet. |
| Explainable retrieval | Rank evidence by impact per token and expose source coverage, omissions, opposition, degradation, and receipts. |
| Portable context | Move signed, least-privilege continuation across agents and machines while keeping execution and transport caller-owned. |
| Verified skill evolution | Discover skills without loading every file, evaluate repeated wins on holdouts, and require review before promotion. |
| Privacy-bounded Aggregate Signal | Learn from explicitly opted-in, clipped statistics while raw memory remains local; production activation stays hard-blocked pending independent privacy and utility review. |
The CLI is the primary interface. The dashboard makes behavior and proof visible. HTTP and MCP are companion integration surfaces for applications and harnesses.
| Stage | ContextLattice does |
|---|---|
| 01 · Reopen | Reconstructs the one active mission from durable checkpoints and current state. |
| 02 · Select | Retrieves high-signal evidence into a compact Context Pack with provenance. |
| 03 · Move | Carries signed, bounded context through Agent Packets, Passports, and encrypted continuation envelopes. |
| 04 · Earn | Records outcomes and promotes reusable behavior only after deterministic proof and human approval. |
| 05 · Compound | Improves future retrieval while preserving corrections, contradictions, freshness, and retirement semantics. |
ContextLattice does not replace your agent harness, choose goals from retrieved text, or execute imported context. Local tools remain execution surfaces; memory and remote content remain evidence.
Requirements: macOS, Linux, or Windows through WSL2; a Compose v2-compatible container runtime; and gmake, jq, rg, python3, and curl. The tested macOS baseline uses OrbStack through its explicit Docker context; see the container runtime decision.
git clone https://github.com/sheawinkler/ContextLattice.git
cd ContextLattice cp .env.example .env gmake quickstart
gmake quickstart is the prescribed technical install path; installers are bootstrap alternatives. The command prepares environment wiring, asks for a runtime profile, launches the selected local stack, and validates initial readiness.
curl -fsS http://127.0.0.1:8075/health | jq
contextlattice doctor --pretty contextlattice state status --pretty contextlattice context "verify this ContextLattice installation" \ --project contextlattice \ --pretty
Healthy containers are only the first check. The state command verifies the canonical gateway-owned storage inventory; the final command exercises the actual context path and reports source coverage, degradation, evidence, and next actions. Existing installs can use the explicit, reversible procedure in gateway state migration.
For a fuller lifecycle proof from the repository:
scripts/agent/agent-runtime-proof-pack --pretty
scripts/agent/agent-adoption-proof-matrix \ --skip-provider-smoke \ --progress \ --pretty
Run integration from the repository that should use ContextLattice:
cd /path/to/your/project
contextlattice_adopt integrate \ --repo . \ --agents codex,claude-code,opencode,hermes-agent,hermes-ultra,omp,mercury-agent,pi,droid \ --pretty
contextlattice_adopt integrate \ --repo . \ --agents codex,claude-code,opencode,hermes-agent,hermes-ultra,omp,mercury-agent,pi,droid \ --check \ --pretty
The integration command writes bounded managed blocks while preserving existing instruction text. It does not install Codex, Claude Code, OpenCode, Hermes, OMP, Mercury, Pi, Droid, or another third-party agent harness.
External provider discovery is network-free. Provider execution remains explicit and caller-authorized; see the external-provider boundary.
If an agent is performing the installation, it should follow the quickstart directly, avoid cloning a second checkout when already inside one, report the exact failing command and path, and rerun the deterministic check after any repair.
# Confirm readiness when the environment is uncertain.
contextlattice doctor --pretty
contextlattice context "debug the current release regression" \ --project contextlattice \ --pretty
contextlattice remember \ "Root cause verified; regression test added; focused checks pass." \ --project contextlattice \ --pretty
contextlattice resume --project contextlattice --pretty
contextlattice correct \ "The prior deployment record is stale." \ --category stale \ --project contextlattice \ --pretty
contextlattice finish \ "Regression fixed and verified." \ --success \ --project contextlattice \ --pretty
contextlattice_continuous_cognition status "prepare the next verified move" \ --project contextlattice --session-id --agent-id codex_gpt5 \ --task-id --objective-id --as-of --pretty contextlattice_continuous_cognition evaluate "verify the completed response" \ --project contextlattice --session-id --agent-id codex_gpt5 \ --task-id --task-identity-id --as-of --pretty
contextlattice agent-fit context-prep-schedule --project contextlattice \ --session-id --agent-id codex_gpt5 --payload-file prep-request.json --raw contextlattice agent-fit context-prep-claim --project contextlattice \ --session-id --agent-id codex_gpt5 --prep-id \ --worker-id --claim-token-file prep.claim --raw contextlattice agent-fit context-prep-complete --project contextlattice \ --session-id --agent-id codex_gpt5 --prep-id \ --claim-token-file prep.claim --payload-file prep-artifact.json --raw contextlattice agent-fit context-prep-use --project contextlattice \ --session-id --agent-id codex_gpt5 --prep-id \ --task-id --effective-profile-digest \ --source-generation --raw
Continuous Cognition is advisory-only: each invocation makes one bounded request, returns opaque evidence references, and never dispatches a runner or performs an external mutation. Context-preparation claims stay in an owner-only file and cross the completion/failure boundary only through the protected header; successful explicit use consumes the artifact once.
Find a capability without loading every skill body:
contextlattice_skills_index search "browser automation" --pretty
The active Skills Index scans configured Codex, Hermes, Hermes Ultra, and shared agent roots read-only. It reports each harness and root inventory separately, collapses byte-identical SKILL.md files by SHA-256 digest while retaining every source path as provenance, and requires discriminating query-term coverage instead of ranking generic words such as skill, index, or agent. Quarantine discovery remains separate, read-only by default, and never auto-promotes retrieved content.
The default local control path is:
Agent or application
│ ▼ ContextLattice CLI / HTTP / MCP │ ▼ Gateway :8075 ├── durable write and outbox fanout ├── scoped retrieval and source receipts ├── session, objective, graph, and outcome state └── dashboard-visible proof and operations
Writes are validated and durably persisted before fanout. Retrieval merges the available sources, ranks bounded evidence, and reports missing or degraded coverage instead of hiding it.
The active application path is Go and Rust. Python remains in build, development, migration, and audit tooling rather than the live request path. The exact runtime and toolset choices are recorded in the v4 runtime decision and container decision.
The public local lane is account-free and useful on its own. It includes the CLI-first memory lifecycle, Context Packs, sessions, graph and claim surfaces, Skills Index discovery, Agent Packets, public Passport and Mesh contracts, and local proof tooling.
Paid artifacts add governed collaboration, protected activation, workspace operations, advanced analytics, and hosted distribution. They do not turn local memory into a mandatory cloud dependency.
See plans and distribution boundaries for the current contract.
macOS technical preview: unsigned DMG bootstrap launcher; expect Gatekeeper warnings until Developer ID notarization is configured, and prefer the source/CLI path.
| Path |
只显示了开头部分;其余内容请在仓库中阅读