MIND MCP Server
Enables AI agents to persist and retrieve memories via a personal knowledge graph, with tools for emotional intelligence, CRM, life management, social features, self-training, and autonomous insights.
README
@astramindapp/mcp-server
MIND MCP Server — The most complete AI memory layer available. 15 tools, 89 actions.
Your AI agents forget everything between sessions. MIND fixes that. Connect any MCP-compatible agent to your personal knowledge graph — with emotional intelligence, CRM, life management, social features, self-training, autonomous insights, and more.
15 Tools
| Tool | Actions | What It Does |
|---|---|---|
mind_query |
1 | Semantic search across your knowledge graph (5 search modes) |
mind_remember |
5 | Store, search, get, list, delete — documents, entries, thoughts |
mind_context |
1 | Load persistent identity, preferences, rules, priorities, recent activity |
mind_life |
12 | Goals, projects, tasks + full calendar management + productivity stats |
mind_crm |
7 | Contacts, pipeline, activity logging, interaction history |
mind_graph |
3 | Graph stats, diagnostics, entity labels |
mind_admin |
7 | User provisioning, featured minds, tier/credit management |
mind_sense |
7 | MINDsense emotional intelligence — state, signals, timeline, KG weights, spikes |
mind_research |
3 | Launch autonomous deep research jobs |
mind_train |
7 | Self-training sessions + save chats to knowledge graph |
mind_social |
14 | Thoughts (posts), social feed, communities, likes, comments |
mind_profile |
9 | Profile, custom system prompts, LLM model selection |
mind_insights |
7 | Autonomous Learning Engine insights, weekly summaries, feedback |
mind_automate |
6 | Scheduled automations, event triggers, execution history |
mind_notify |
4 | Notifications, mark read, stats |
Quick Start
1. Get a MIND API Key
Sign up at m-i-n-d.ai → Settings → Developer → Create API Key
2. Install
npm install -g @astramindapp/mcp-server
3. Configure Your AI Tool
Claude Code
claude mcp add mind -- env MIND_API_KEY=mind_xxx mind-mcp
Claude Desktop
Add to your claude_desktop_config.json:
{
"mcpServers": {
"mind": {
"command": "mind-mcp",
"env": {
"MIND_API_KEY": "mind_your_key_here"
}
}
}
}
Cursor
Add to .cursor/mcp.json:
{
"mcpServers": {
"mind": {
"command": "mind-mcp",
"env": {
"MIND_API_KEY": "mind_your_key_here"
}
}
}
}
Any MCP-Compatible Agent
The server works with any tool that supports Model Context Protocol — Claude, GPT, Gemini, Llama, or any future model.
How It Works
Your AI Agent <--> MCP Protocol <--> MIND MCP Server <--> Personal Knowledge Graph
|
Emotional Intelligence
Autonomous Learning
CRM + Life + Social
- Agent calls
mind_contextat session start → loads identity, rules, priorities - Agent calls
mind_querybefore decisions → retrieves relevant memories - Agent calls
mind_rememberafter tasks → stores outcomes and learnings - Agent calls
mind_sense→ reads user's emotional state to adapt responses - Agent calls
mind_insights→ surfaces autonomous pattern detection - Next session, any agent has full context. Knowledge compounds.
What Makes MIND Different
vs. Flat File Memory (MEMORY.md)
| Flat Files | MIND | |
|---|---|---|
| Size | ~20K chars, truncated | Unlimited knowledge graph |
| Retrieval | Loads everything every turn | Only relevant memories via semantic search |
| Structure | Unstructured text | Graph with entities, relationships, and emotional weights |
| Cross-agent | One tool only | Shared across all AI agents |
| Intelligence | None | Autonomous pattern detection + emotional encoding |
vs. Other MCP Memory Servers
| Anthropic Official | Mem0 | Graphiti/Zep | MIND | |
|---|---|---|---|---|
| Tools | 8 | 4 | 9 | 15 |
| Knowledge graph | Basic (JSON) | No (vectors) | Yes (Neo4j) | Yes (LightRAG) |
| Emotional intelligence | No | No | No | Yes (patented) |
| CRM | No | No | No | Yes |
| Life management | No | No | No | Yes |
| Social features | No | No | No | Yes |
| Self-training | No | No | No | Yes |
| Research agent | No | No | No | Yes |
| Automations | No | No | No | Yes |
| Mobile app | No | No | No | Yes |
Tool Reference
mind_query — Search Your Knowledge Graph
query: "What did I decide about the authentication approach?"
mode: "hybrid" // hybrid (default), mix, global, local, naive
Returns an AI-synthesized answer from your stored documents, entries, and thoughts with source attribution.
mind_remember — Store & Manage Content
| Action | Description |
|---|---|
create |
Store content (auto-categorized as document, entry, or thought) |
delete |
Remove by ID |
search |
Find entries/thoughts by query |
get |
Retrieve specific item by ID |
list |
Paginated listing of all content |
mind_context — Load Persistent Context
Loads five structured sections at session start:
- Soul — Core identity, mission, personality
- User — Who the user is, their role, preferences
- Rules — Operating constraints, behavioral guidelines
- Priorities — Current goals, active projects, deadlines
- Recent — Latest activity, outcomes, decisions
mind_life — Life Management + Calendar
| Action | Description |
|---|---|
list, create, update, complete, delete, move, get |
Full task/goal CRUD |
calendar_list, calendar_create, calendar_update, calendar_delete |
Calendar events |
stats |
Productivity metrics and completion rates |
mind_crm — Contact Relationship Management
| Action | Description |
|---|---|
list, create, update, delete, get |
Contact CRUD with pipeline stages |
log_activity |
Record calls, emails, meetings, notes |
list_activities |
View interaction history |
mind_sense — MINDsense Emotional Intelligence
| Action | Description |
|---|---|
state |
Current emotional state (valence, arousal, trend, sensitivity) |
signals |
Recent emotional signals with strength and source |
timeline |
Historical emotional data |
kg_weights |
Entities weighted by emotional significance |
spikes |
Detected emotional spikes |
acknowledge |
Mark a spike as acknowledged |
summary |
AI-generated emotional summary |
mind_research — Autonomous Research
| Action | Description |
|---|---|
start |
Launch a deep research job on any topic |
status |
Check job progress |
list |
View all research jobs |
mind_train — Self-Training
| Action | Description |
|---|---|
start |
Begin guided training (basics, network, expertise, history, goals, freeform) |
chat |
Send training message |
status, list_sessions, pause, resume |
Session management |
save_chat |
Save any chat conversation into the knowledge graph |
mind_social — Social Layer
| Action | Description |
|---|---|
create_thought, get_thought, delete_thought, like_thought |
Thought (post) management |
feed, user_feed, search_feed |
Social feed browsing |
create_community, list_communities, get_community |
Community management |
join_community, leave_community |
Membership |
create_post, list_posts |
Community posts |
mind_profile — Profile & Preferences
| Action | Description |
|---|---|
get, update |
Profile management |
get_chat_prompt, set_chat_prompt |
Custom chat system prompt |
get_thought_prompt, set_thought_prompt |
Custom thought generation prompt |
get_model, set_model, list_models |
LLM model selection (50+ models) |
mind_insights — Autonomous Learning Engine
| Action | Description |
|---|---|
list |
Recent pattern-detected insights |
unread_count |
Count of unseen insights |
view, feedback |
Mark seen, rate helpfulness |
analyze |
Trigger on-demand analysis |
weekly_summary |
Weekly intelligence summary |
context |
ALE context data |
mind_automate — Automations
| Action | Description |
|---|---|
list, create, update, delete |
Automation CRUD |
run_now |
Trigger immediately |
history |
Execution log |
mind_notify — Notifications
| Action | Description |
|---|---|
list |
View all notifications |
mark_read, mark_all_read |
Read management |
stats |
Notification overview |
mind_admin — Administration
| Action | Description |
|---|---|
create_user |
Provision new MIND account |
list_users |
List users with analytics |
update_user_tier |
Change subscription tier |
adjust_user_credits |
Add/deduct credits |
create_featured_mind |
Create public featured mind |
list_featured_minds, update_featured_mind |
Featured minds catalog |
Partner Integration
Partner apps can programmatically create MIND accounts using partner keys:
curl -X POST https://m-i-n-d.ai/admin/users/create \
-H "X-API-Key: mind_partner_YOUR_KEY" \
-H "Content-Type: application/json" \
-d '{
"username": "newuser",
"email": "user@app.com",
"password": "securepassword",
"generate_api_key": true
}'
Returns a JWT + permanent API key. Your app stores the API key and uses it for all subsequent MCP/API calls on behalf of that user.
Environment Variables
| Variable | Required | Default | Description |
|---|---|---|---|
MIND_API_KEY |
Yes | — | Your MIND Developer API key |
MIND_BASE_URL |
No | https://m-i-n-d.ai |
MIND API base URL |
Programmatic Usage
import { createMindMcpServer, MindClient } from "@astramindapp/mcp-server";
const client = new MindClient({
baseUrl: "https://m-i-n-d.ai",
apiKey: "mind_xxx",
});
const server = createMindMcpServer(client);
// Connect to any MCP transport
Patents
MIND's technology is protected by multiple provisional patents including:
- Emotion-Weighted Knowledge Graph Encoding (U.S. App. 64/030,662)
- Cross-Agent Persistent Memory via Model Context Protocol
Links
- Website: m-i-n-d.ai
- GitHub: theastraway/mind-mcp-server
- npm: @astramindapp/mcp-server
- MCP Docs: m-i-n-d.ai/mcp.html
License
MIT — Astra AI, Inc.
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。