Crosmos MCP Server

@crosmos-labs

リポジトリ

基本情報

カテゴリ

メモリとナレッジ

トランスポート

stdio

作者

crosmos-labs

投稿者

Aditya Chaudhary

Crosmos MCP Server について

Persistent memory for AI agents. Give your coding assistant organizational context that compounds — search memories with hybrid retrieval, store anything with auto entity extraction, and query a living knowledge graph that gets smarter over time.

#context #ai #memory

Crosmos 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": {
    "crosmos-memory": {
      "command": "npx",
      "args": [
        "-y",
        "@crosmos/crosmos-mcp"
      ],
      "env": {
        "CROSMOS_API_KEY": "<YOUR_API_KEY>"
      }
    }
  }
}

Crosmos MCP Server のツール

Search memories in Crosmos Memory Engine using hybrid retrieval. Combines semantic (vector), keyword (full-text), and graph-based retrieval. Requires a space_id — call list_spaces if you don't have one yet.

Add new memories to Crosmos Memory Engine. Content is processed through an extraction pipeline that identifies entities, relationships, and creates structured knowledge graph entries. Requires a space_id — call list_spaces if you don't have one yet.

Check the health status of the Crosmos Memory Engine API

List all memory spaces owned by the authenticated user. Call this to discover available space IDs needed by search_memories and add_memory.

概要

What is Crosmos?

Crosmos is a persistent memory layer for AI agents. It enables agents to store and retrieve organizational knowledge across sessions using a temporal knowledge graph with hybrid retrieval.

How to use Crosmos?

Install via npx @crosmos/crosmos-mcp setup which auto-detects MCP clients, or configure manually with a JSON block setting the CROSMOS_API_KEY (obtainable at console.crosmos.dev). Supported clients include Claude Desktop, Claude Code, Cursor, VS Code, Windsurf, opencode, Cline, Roo-Cline, and Zed.

Key features of Crosmos?

Graph-native memory with entity and relationship linking
Temporal – every fact is timestamped for time‑travel queries
Hybrid retrieval (semantic, keyword, graph, temporal)
Automatic entity and relationship extraction from raw text
Multi‑space isolation for projects, teams, or agents
Four retrieval signals fused into a single ranked result

Use cases of Crosmos?

Store and retrieve organizational knowledge across AI agent sessions
Query the knowledge graph as it existed at any past point in time
Isolate memory by project, team, or agent using named spaces
Allow agents to maintain persistent context without resets
Enable hybrid search combining semantic meaning with graph traversal

よくある質問

What is Crosmos and how does it differ from flat vector databases?

Crosmos uses a temporal knowledge graph that links memories as entities and relationships, not just flat vectors, enabling richer context and time

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