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Contextlattice MCP Server

@sheawinkler

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基本情報

カテゴリ

その他

ライセンス

Apache-2.0

トランスポート

stdio

作者

sheawinkler

投稿者

sheawinkler

Contextlattice MCP Server について

ContextLattice is the local-first control plane for long-horizon agent memory, coordination, and behavioral provenance.

Contextlattice MCP Server の設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "contextlattice": {
      "type": "streamable-http",
      "url": "http://127.0.0.1:8075/mcp",
      "headers": {
        "Accept": "application/json, text/event-stream",
        "Content-Type": "application/json",
        "x-api-key": "${CONTEXTLATTICE_ORCHESTRATOR_API_KEY}"
      }
    }
  }
}

Contextlattice MCP Server のツール

ツール一覧はまだありません

この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。

上のボタンでサーバーのエンドポイントに接続し、ツール一覧を取得できます。

概要

What is ContextLattice?

ContextLattice is a private-by-default memory and context orchestration system for AI agents. It provides a unified write/read contract for agentic memory, durable fanout across retrieval and storage lanes, and staged retrieval with agent sessions, all running in a local-first deployment with optional hosted surfaces. It is implemented as an MCP HTTP Gateway with a Go/Rust runtime.

How to use ContextLattice?

Clone the repository, copy .env.example to .env, then run gmake quickstart to launch the selected stack. Verify with curl -fsS http://127.0.0.1:8075/health | jq and the proof scripts. AI agents can install and integrate by following the Agent Quickstart block, which uses contextlattice_adopt integrate to write managed instruction blocks for supported agent profiles.

Key features of ContextLattice

  • Unified write/read memory contract for agentic systems.
  • Durable fanout across retrieval and storage lanes.
  • Staged retrieval with fast now and deep continuation.
  • Agent sessions with prior work, objective lineage, and handoffs.
  • Go/Rust runtime ownership for the active application path.
  • Local-first deployment with optional hosted surfaces.

Use cases of ContextLattice

  • Integrate memory and context orchestration into existing agent workflows (Codex, Claude Code, OMP, Mercury, etc.).
  • Manage long-running agent sessions with checkpoints, handoffs, and run-card exports.
  • Run a private-by-default memory layer for agentic systems without third-party cloud dependencies.
  • Deploy a single-container lite stack for local agent memory with topic_rollups and Qdrant.

よくある質問

1

What runtime dependencies does ContextLattice require?

The public lite stack uses Go and Rust services; the legacy Python runtime is archived and optional. Single-container lite builds run `gateway-go` without Python. Qdrant is the default vector lane; pgvector is supported but not started by default in lite mode.

2

How do I install and launch ContextLattice?

Clone the repository, copy `.env.example` to `.env`, then run `gmake quickstart`. The quickstart prompts for the runtime profile and launches the selected container stack. Verify with `curl -fsS http://127.0.0.1:8075/health | jq`.

3

What license is ContextLattice released under?

ContextLattice is licensed under BSL 1.1.

4

What is the default embedding path?

Embedding defaults to the Rust `fastembed-rs` sidecar. Ollama is available as an explicit compatibility fallback but is not the preferred embedding path.

5

How does the model inference runtime work?

The runtime detects the host profile and probes local backends. Default priorities vary by platform (Apple Silicon: mlx, vllm-metal; CUDA/ROCm: sglang, vllm; generic CPU: openai-compatible, llama.cpp). The provider is controlled by `ORCH_INFER_PROVIDER=auto` and can be overridden with environment variables.

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