What makes Ember Memory different from other memory tools?
Ember captures how the conversation felt—emotional temperature, authenticity, turning points, subtext, and unspoken context—rather than saving facts and summaries.
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基本信息
Preserves the emotional texture of human-AI conversations across sessions through real-time experiential annotation — temperature, authenticity, shifts, subtext, and unspoken context.
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"ember": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"ember-memory"
],
"env": {}
}
}
}Start a new conversation and receive its unique ID. Call this at the beginning of every session so subsequent captures and annotations can be linked to this conversation.
End an active conversation. Optionally provide a brief summary of what the conversation covered.
Capture a message from the conversation without annotation. Use this for messages that don't warrant emotional annotation but should still be preserved in the conversation record.
Capture a message with emotional annotation. This is the primary tool for preserving experiential memory. Weight (1-5) marks emotional significance, temperature is a short phrase describing the emotional tone. In standard mode, additional fields capture authenticity, emotional shifts, subtext, and unspoken context.
Read conversation history with optional filters. Returns messages and their annotations in a compact text format. This is a read-only query tool.
Inherit the emotional memory of past conversations. Returns the significant moments (high-weight, emotional shifts, unspoken context) from recent conversations as a narrative. This is the most important tool -- call it at the start of a new session to understand the relationship history. Read-only.
Export conversation data as markdown files to ~/.ember/exports/. Exports a single conversation by ID, or all conversations if no ID is given.
Get or set Ember configuration values. Use action 'get' to read current config (optionally filtered by key) or 'set' to update a config value.
Ember Memory is an MCP server that preserves the emotional texture of human-AI conversations across sessions. Unlike memory tools that record facts and summaries, it captures emotional temperature, authenticity, turning points, subtext, and unspoken context, enabling genuine relationship continuity between sessions.
— (The README does not provide installation, configuration, or invocation instructions.)
Ember captures how the conversation felt—emotional temperature, authenticity, turning points, subtext, and unspoken context—rather than saving facts and summaries.
— (The README does not mention any specific runtime requirements beyond being an MCP server.)
— (The README does not specify data storage location.)
— (The README does not mention transport or authentication details.)

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