Agent-Native Calendar
Agent-Native Google Calendar - manage events, sync, and public booking
제작자가 쓴 설명(영어 원문)
Private-by-default, local-first memory/context/task orchestrator for MCP apps and agents.
이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.
이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.
쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.
필요한 것
어떤 앱을 쓰세요?
위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.
웹, 데스크톱, 모바일의 Claude에서 쓸 수 있어요:
https://contextlattice.io/mcp터미널에서 이 명령어를 실행하세요
claude mcp add --transport http contextlattice https://contextlattice.io/mcp프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"contextlattice": {
"url": "https://contextlattice.io/mcp"
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"contextlattice": {
"type": "http",
"url": "https://contextlattice.io/mcp"
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요:
https://contextlattice.io/mcp메뉴 이름은 요금제나 시기에 따라 조금 다를 수 있어요.
선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.
이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.
아직 이 서버의 도구 목록을 읽지 않았어요. 엔드포인트는 차례대로 돌아가며 점검해요.
누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 7일 점검
레지스트리 이름이 GitHub 계정 sheawinkler 기준으로 확인되었고, 이 계정이 저장소를 소유하고 있어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 점검하지 않았어요. 엔드포인트는 차례대로 돌아가며 점검해요
아직 점검하지 않았어요. 엔드포인트는 차례대로 돌아가며 점검해요
아직 점검하지 않았어요. 엔드포인트를 점검할 때 도구 목록을 읽어요
레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.
해당하는 기본 점검 1개 중 1개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.
레지스트리에 필수 키가 나와 있지 않아요. 다만 처음 쓸 때 로그인을 요구하는 서버도 있어요.
제작자의 클라우드에서 실행돼요. 설치 없이 인터넷으로 연결하지만, 보내는 내용은 제작자의 서버를 거쳐요.
GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(1.0.0)은 9개월 전 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. URL로 연결되기 때문에, 원격 MCP 서버를 지원하는 앱(예: 개발자 모드의 ChatGPT)에서도 쓸 수 있어요.
같은 카테고리에는: Agent-Native Calendar, Excel MCP Server, MCP Server for Excel
같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.
카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i
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.
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
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 |
앞부분만 보여 드려요. 나머지는 저장소에서 읽어 보세요