ContextLattice

io.github.sheawinkler由 GitHub 账号 sheawinkler 发布v1.0.0更新于 Nov 2, 2026

Private-by-default, local-first memory/context/task orchestrator for MCP apps and agents.

已验证Streamable HTTP可网页运行效率与工作流知识与记忆

概览

AI 生成的概览

本地优先的记忆与上下文层,为 AI 代理提供跨会话、跨工具的持久连续性、可解释检索与可移植上下文。

可以做什么
  • 从持久检查点重开并恢复当前目标,无需重放整段对话
  • 按范围检索并排序证据,生成带来源与覆盖回执的紧凑上下文包
  • 按项目保存、纠正并结束持久记忆条目
  • 通过 Agent Packet 与 Passport 在代理和机器之间传递签名的最小权限上下文
  • 以只读方式搜索技能索引,无需加载每个技能文件即可找到能力
  • 执行仅作建议的持续认知状态与评估调用,返回证据引用
适用场景
适合代理需要在不同对话、模型、工具或电脑之间持续工作,并要求任务目标、决策与证据得以延续的场景。也适合希望使用本地、可检查且带检索回执的记忆,而不想依赖强制云存储的团队。
运行要求
需要本地运行环境:macOS、Linux 或经 WSL2 的 Windows,兼容 Compose v2 的容器运行时,以及 gmake、jq、rg、python3 和 curl。可通过源码配合 gmake quickstart 安装,或使用 Homebrew cask、DMG、MSI、Linux 安装包。公开本地通道无需账号;运维路由使用 API 密钥保护。资源档位从 2-4 vCPU、4-8 GB 内存起。
安装前请注意
安装会向仓库中的代理指令文件写入受管理的区块,但会保留原有文本。运维路由由 API 密钥保护,写入入口默认对疑似密钥内容进行过滤。付费制品涵盖受管协作、工作区操作与托管分发。macOS DMG 未签名,预计会出现 Gatekeeper 警告。

安装

在 SourceWeft 中

  1. 打开 控制台中的 ContextLattice,将其添加到工作区。
  2. 为需要使用其工具的对话启用该服务。

Web executable,通过 Streamable HTTP。 远程服务在工作区中配置后即可从网页运行时运行。

交给智能体安装

把这段提示词粘贴到 Claude Code、Codex、Cursor 等智能体,或 SourceWeft 对话中。智能体会读取该服务器的安装指南,先向你展示发布者、端点和登录方式,经你同意后再把它添加到你的客户端。密钥不会写进任何命令。

阅读 https://sourceweft.com/mcp/io.github.sheawinkler%2Fcontextlattice/install.md,并按其中说明把这个 MCP 服务器接入我的客户端。修改任何配置之前,先告诉我它的发布者、端点和登录方式,等我确认。不要把 API 密钥写进命令或我会提交的文件;问我密钥应从哪里获取。

查看智能体所依据的安装指南

其他 MCP 客户端

把它添加到你客户端的 mcpServers 配置中。

{
  "mcpServers": {
    "contextlattice": {
      "type": "http",
      "url": "https://contextlattice.io/mcp"
    }
  }
}

README

ContextLattice

[ContextLattice editorial website hero showing a live local context field]

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.

[CLI first] [ContextLattice v5.0.2] [Local-first runtime] [Apache License 2.0]

Quickstart · How it works · Agent setup · Architecture · Docs · Updates

Stop replaying the brief

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.

CapabilityWhat changes
Durable continuityReopen the objective, decisions, repository state, risks, proof, and next move as one bounded packet.
Explainable retrievalRank evidence by impact per token and expose source coverage, omissions, opposition, degradation, and receipts.
Portable contextMove signed, least-privilege continuation across agents and machines while keeping execution and transport caller-owned.
Verified skill evolutionDiscover skills without loading every file, evaluate repeated wins on holdouts, and require review before promotion.
Privacy-bounded Aggregate SignalLearn 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.

How it works

StageContextLattice does
01 · ReopenReconstructs the one active mission from durable checkpoints and current state.
02 · SelectRetrieves high-signal evidence into a compact Context Pack with provenance.
03 · MoveCarries signed, bounded context through Agent Packets, Passports, and encrypted continuation envelopes.
04 · EarnRecords outcomes and promotes reusable behavior only after deterministic proof and human approval.
05 · CompoundImproves 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.

Quickstart

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.

1. Install

zsh
git clone https://github.com/sheawinkler/ContextLattice.gitcd ContextLatticecp .env.example .envgmake 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.

2. Verify the runtime and retrieval path

zsh
curl -fsS http://127.0.0.1:8075/health | jqcontextlattice doctor --prettycontextlattice state status --prettycontextlattice 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:

zsh
scripts/agent/agent-runtime-proof-pack --prettyscripts/agent/agent-adoption-proof-matrix \  --skip-provider-smoke \  --progress \  --pretty

Connect your agents

Run integration from the repository that should use ContextLattice:

zsh
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.

The daily agent loop

zsh
# Confirm readiness when the environment is uncertain.contextlattice doctor --pretty
# Retrieve scoped context before substantial work.contextlattice context "debug the current release regression" \  --project contextlattice \  --pretty
# Save concise, durable progress.contextlattice remember \  "Root cause verified; regression test added; focused checks pass." \  --project contextlattice \  --pretty
# Resume without replaying the transcript.contextlattice resume --project contextlattice --pretty
# Repair stale or wrong recall without silently rewriting history.contextlattice correct \  "The prior deployment record is stale." \  --category stale \  --project contextlattice \  --pretty
# Close the loop with the verified outcome.contextlattice finish \  "Regression fixed and verified." \  --success \  --project contextlattice \  --pretty
# Project the next bounded move or bind a completed response to durable proof.contextlattice_continuous_cognition status "prepare the next verified move" \  --project contextlattice --session-id <session-id> --agent-id codex_gpt5 \  --task-id <task-id> --objective-id <objective-id> --as-of <rfc3339> --prettycontextlattice_continuous_cognition evaluate "verify the completed response" \  --project contextlattice --session-id <session-id> --agent-id codex_gpt5 \  --task-id <task-id> --task-identity-id <task-identity-id> --as-of <rfc3339> --pretty
# Prepare context for an external worker without exposing its one-shot claim.contextlattice agent-fit context-prep-schedule --project contextlattice \  --session-id <session-id> --agent-id codex_gpt5 --payload-file prep-request.json --rawcontextlattice agent-fit context-prep-claim --project contextlattice \  --session-id <session-id> --agent-id codex_gpt5 --prep-id <prep-id> \  --worker-id <worker-id> --claim-token-file prep.claim --rawcontextlattice agent-fit context-prep-complete --project contextlattice \  --session-id <session-id> --agent-id codex_gpt5 --prep-id <prep-id> \  --claim-token-file prep.claim --payload-file prep-artifact.json --rawcontextlattice agent-fit context-prep-use --project contextlattice \  --session-id <session-id> --agent-id codex_gpt5 --prep-id <prep-id> \  --task-id <task-id> --effective-profile-digest <sha256-digest> \  --source-generation <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:

zsh
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.

Architecture

The default local control path is:

text
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.

Public and paid boundaries

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.

Install options

macOS technical preview: unsigned DMG bootstrap launcher; expect Gatekeeper warnings until Developer ID notarization is configured, and prefer the source/CLI path.

PathBest forStatus
Source + gmake quickstartTechnical users and terminal-capable agentsRecommended
brew tap sheawinkler/contextlattice && brew install --cask contextlatticemacOS convenience bootstrapAvailable
macOS universal DMGGuided macOS bootstrapUnsigned technical preview; expect Gatekeeper warnings
Windows x64 MSIGuided Windows bootstrapAvailable
Linux bootstrap bundleGuided Linux bootstrapAvailable

Resource profiles

ProfileCPURAMStorage
Hugging Face / Glama lite2–4 vCPU4–8 GB20–50 GB SSD
Local Lite core2–4 vCPU8–12 GB25–80 GB SSD
Local Lite advanced4–6 vCPU12–16 GB80–140 GB SSD
Local Full6–8 vCPU12–20 GB100–180 GB SSD

For heavier ingest, model storage, or the spike-lab adapters, read the installation and storage guidance before selecting a profile.

Security and privacy

  • Local-first and account-free in the public local lane.
  • API-key protection for operational routes.
  • Deterministic secret-like content filtering at write ingress: redact by default, block when configured, and allow only by explicit operator choice.
  • Provenance and trust isolation on retrieved memory.
  • Signed portable context and encrypted continuation envelopes.
  • Dry-run-first graph repair, source backfill, and quarantine workflows.
  • No automatic execution of retrieved instructions or imported continuation content.

Security reports follow SECURITY.md.

Documentation

NeedStart here
Product overviewcontextlattice.io
InstallationInstallation guide
CLI and agent lifecycleCLI reference
Harness and app integrationIntegration guide
Architecture and scalingArchitecture · Scaling memory
TroubleshootingTroubleshooting guide
Current behavior and release evidenceUpdates · v5.0.2 release notes
RoadmapPublic roadmap
Agent hooksAgent hook contract
Retrieval trustRetrieval receipts
Skills and verified learningSkill efficacy review · Skill Foundry
Portable contextContext Passport and Mesh
Local inferenceLocal model options
Full repository-backed manualPublic field manual

The current release baseline is v5.0.2.

License

ContextLattice's public lane is licensed under the Apache License 2.0.

来源:README.md,提交 e0daa91

工具

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版本历史

1
  1. v1.0.0最新Sep 16, 2026

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