dejaview-mcp
Provides persistent knowledge graph memory for AI agents, enabling them to store, recall, and query facts about people, projects, and relationships across sessions.
README
dejaview-mcp
Persistent knowledge graph memory for AI agents — an MCP server backed by DejaView.
Connect Claude Desktop, Cursor, Windsurf, or any MCP-compatible host to a live knowledge graph. Your AI remembers people, projects, decisions, and relationships across every session.
Get your free API key at dejaview.io.
Option 1: Cloud (no install required) ⚡
The fastest way to get started — no pip install, no local process.
{
"mcpServers": {
"dejaview": {
"type": "streamable-http",
"url": "https://api.dejaview.io/mcp",
"headers": {
"Authorization": "Bearer dv_your_key_here"
}
}
}
}
Paste this into your Claude Desktop, Cursor, or Windsurf MCP config. Done.
Option 2: Local (pip install)
If you prefer to run the server locally:
pip install dejaview-mcp
Add to your config:
{
"mcpServers": {
"dejaview": {
"command": "dejaview-mcp",
"env": {
"DEJAVIEW_API_KEY": "dv_your_key_here"
}
}
}
}
Config file locations:
- macOS:
~/Library/Application Support/Claude/claude_desktop_config.json - Linux:
~/.config/claude/claude_desktop_config.json - Windows:
%APPDATA%\Claude\claude_desktop_config.json
What it does
DejaView gives your AI a persistent knowledge graph it can read from and write to across sessions. Unlike flat context windows that reset every chat, the graph grows over time.
| Tool | What it does |
|---|---|
agent_context |
Load a full memory summary at session start |
remember |
Store a fact (subject, predicate, object) |
remember_many |
Store multiple facts at once |
recall |
Get everything known about an entity |
search |
Find entities by name |
ask |
Natural language Q&A over the graph with citations |
timeline |
See recently stored facts |
graph_stats |
Entity and relationship counts |
share |
Generate a public shareable link for any entity |
forget |
Remove a specific fact |
forget_entity |
Remove an entity and all its connections |
Example
Once connected, just chat naturally:
"Remember that Alice is the lead on Project Atlas and prefers async communication."
The agent calls remember() automatically. Next session:
"What do I know about Alice?"
The agent calls recall("Alice") and tells you everything — including things you told it months ago.
Self-hosting
Want to run your own DejaView instance? The API is open source: github.com/JakeC77/DejaView
Set DEJAVIEW_ENDPOINT to point at your instance:
DEJAVIEW_API_KEY=dv_... DEJAVIEW_ENDPOINT=https://your-instance.com dejaview-mcp
Links
- Website: dejaview.io
- API: api.dejaview.io/docs
- GitHub: github.com/JakeC77/DejaView-MCP
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。