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Memory Arbiter MCP Server

@billy12151

代码仓库

基本信息

分类

记忆与知识

传输方式

stdio

作者

billy12151

提交者

张志维

关于 Memory Arbiter MCP Server

Share one memory store across all your AI coding tools. Memory Arbiter is a lightweight, fully local MCP Server with built-in dual-timeline conflict arbitration. No cloud, no LLM calls — just SQLite.

#memory#conflict-resolution#multi-agent#shared-memory#sqlite#local-first#mcp

Memory Arbiter MCP Server 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "memory-arbiter": {
      "command": "memory-arbiter-mcp",
      "env": {
        "MEMORY_ARBITER_CLIENT": "zcode",
        "MEMORY_ARBITER_AGENT_ID": "zcode-default",
        "MEMORY_ARBITER_DB_PATH": "~/.local/share/memory-arbiter/memory.sqlite3"
      }
    }
  }
}

Memory Arbiter MCP Server 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is Memory Arbiter MCP?

Memory Arbiter MCP is a Model Context Protocol server that provides a shared local memory store, backed by SQLite, for multiple AI coding tools such as ZCode, Codex, Cursor, and Claude Code. It is designed for developers who need a consistent memory layer across different assistants without relying on cloud services.

How to use Memory Arbiter MCP?

Install the package with pip install memory-arbiter-mcp, then add it as an MCP server to each AI coding tool you use. The shared memory database is stored locally in an SQLite file; no additional infrastructure is required.

Key features of Memory Arbiter MCP

  • Shared memory store across multiple AI coding tools
  • Conflict arbitration with multi-factor resolution
  • User-confirmed memories locked from agent overwrites
  • Zero cloud dependencies, all local SQLite
  • Graceful degradation through fallback search methods

Use cases of Memory Arbiter MCP

  • Maintain a consistent knowledge base across different coding assistants
  • Preserve user-confirmed context that agents cannot accidentally overwrite
  • Resolve conflicting memory entries automatically during multi-agent workflows
  • Keep all memory data locally for privacy and offline usage
  • Fall back to simpler search methods when vector search is unavailable

常见问题

1

How does conflict arbitration work?

Conflicts are resolved using a dual-timeline priority: user-confirmed entries take precedence, then event time, source trust level, and finally ingest time.

2

Can agents overwrite memories I’ve confirmed?

No. User-confirmed memories are locked and cannot be overwritten by agents, ensuring critical context remains stable.

3

Does this server require cloud services or LLM calls?

No. Everything runs locally on SQLite with no cloud dependencies and zero LLM calls for memory operations.

4

What happens if sqlite-vec is not installed?

The server degrades gracefully through fallbacks: first FTS5, then LIKE queries, and finally reading from a JSONL backup.

5

How is the memory store shared between tools?

Each tool connects to the same MCP server, which reads and writes a single local SQLite database file.

评论

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