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ContextLattice

by sheawinklerversion 1.0.0i★ –iRuns in the cloud
Registry nameio.github.sheawinkler/contextlattice

Install

Overview

Description from the maker (original English)

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

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs in the cloud
  • Transport: Streamable HTTP
  • Category: Docs, sheets & office work

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on the maker’s server: what you ask it goes through their server.
  • The registry lists no key to fill in.

You need

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Works in Claude on the web, desktop and mobile:

  1. Open Settings → Connectors
  2. Press Add custom connector
  3. Paste the address below and press Add
  4. If it asks you to sign in, sign in with the maker
SettingsConnectors1+ Add2https://…3
https://contextlattice.io/mcp

Run this in your terminal

claude mcp add --transport http contextlattice https://contextlattice.io/mcp

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

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

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

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

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

ChatGPT connects only to servers on the internet:

  1. Open ChatGPT on the web → Settings → Connectors (Apps)
  2. Press Create or Add (some plans need Developer mode under Advanced first)
  3. Paste the address below, give it a name and save
  4. If it asks you to sign in, sign in with the maker
SettingsConnectors1+ Create2https://…3
https://contextlattice.io/mcp

Menu names can differ slightly by plan and over time.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

We have not read this server’s tool list yet; we check endpoints in rotation.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account sheawinkler, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • … Not checked yet

    Endpoint responds

    Not checked yet; we check endpoints in rotation

  • … Not checked yet

    Sign-in with OAuth

    Not checked yet; we check endpoints in rotation

  • … Not checked yet

    No hidden instructions in tool descriptions

    Not checked yet; we read the tool list when we check the endpoint

Compared with others in Docs, sheets & office worki

  • More stars than 0% of the other 3532 servers in this category
  • Published to the registry more recently than 3% of the other 3532 servers in this category
  • Basic checks equal to or better than 100% of the other 3532 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is ContextLattice safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs in the maker’s cloud. Connect over the internet with nothing to install, but what you send passes through the maker’s servers.

Is it still maintained?

The GitHub repo last changed –, and the latest version (1.0.0) reached the registry 9 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. It connects by URL, so apps that accept remote MCP servers work too, such as ChatGPT in developer mode.

What can I use instead?

In the same category: Agent-Native Calendar, Excel MCP Server, MCP Server for Excel

Alternatives

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Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

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Runs in the cloud★ 7,620MITUpdated 2 months ago
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Excel MCP Server

by haris-musa

Lets AI create and edit Excel files itself, including formulas, charts and PivotTables, without Excel installed.

Runs on your computer★ 4,276MITUpdated 7 days ago
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Excel automation for AI - Sheets, Power Query, DAX, VBA, Tables, Ranges and more. Windows only.

Runs on your computer★ 847MITUpdated 4 days ago
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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

ContextLattice

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

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
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.

2. Verify the runtime and retrieval path
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

Connect your agents

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.

The daily agent loop

# 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 --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

Prepare context for an external worker without exposing its one-shot claim.

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.

Architecture

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.

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.

| Path |

Only the beginning is shown; read the rest in the repo

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