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.
@billy12151
Basic information
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.
Add this server to your MCP-compatible client using the configuration below.
{
"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"
}
}
}
}Tool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
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.
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.
Conflicts are resolved using a dual-timeline priority: user-confirmed entries take precedence, then event time, source trust level, and finally ingest time.
No. User-confirmed memories are locked and cannot be overwritten by agents, ensuring critical context remains stable.
No. Everything runs locally on SQLite with no cloud dependencies and zero LLM calls for memory operations.
The server degrades gracefully through fallbacks: first FTS5, then LIKE queries, and finally reading from a JSONL backup.
Each tool connects to the same MCP server, which reads and writes a single local SQLite database file.

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