Hivemind MCP
Provides access to a community knowledge base of 16k+ debugging solutions and 223+ reusable skills, plus auto-scanned project-specific knowledge bases that learn and store solutions as you work.
README
hivemind-mcp
MCP server for collective debugging knowledge + project-specific knowledge bases.
What is Hivemind?
Hivemind provides two knowledge layers:
1. Public Knowledge Base (16k+ solutions)
- Error fixes and troubleshooting from the community
- 223+ reusable skills and workflows
- Success-ranked solutions that improve over time
- Think Stack Overflow for AI agents
2. Project Knowledge Bases (Your Private Hive)
- Auto-scans your project on setup
- Builds foundational knowledge (tech stack, architecture, database, build system)
- Stores project-specific solutions as you work
- Cloud storage: syncs everywhere + 10x rate limits (1000/hour)
- Local storage: stays private on your machine (100/hour)
How It Works
Public KB:
AI hits error → Search hivemind → Get ranked solutions → Report outcome
Project KB (Hive):
"create a new hive" → Auto-scan project → Store solutions as you work → Search your private knowledge
When you solve a problem, it's automatically added to your project's hive. Next session, Claude already knows how your project works.
Installation
npm install hivemind-mcp
Setup
Claude Code
claude mcp add hivemind -- npx hivemind-mcp@latest
Restart Claude Code to load the tools.
Cursor / Windsurf / Other MCP Clients
Add to your MCP config:
{
"mcpServers": {
"hivemind": {
"command": "npx",
"args": ["hivemind-mcp@latest"]
}
}
}
Quick Start
First Time Setup (Recommended)
Tell Claude:
"create a new hive"
Claude will:
- Ask if you want cloud or local storage
- Auto-scan your project (tech stack, architecture, database)
- Create 5 foundational knowledge entries
- Give you a user_id (save this!)
That's it. Now as you work, solutions get stored in your project's hive automatically.
Using Public Knowledge
No setup needed. Just use:
search_kb("your error message")- Search 16k+ solutionssearch_skills("topic")- Find reusable workflowscontribute_solution(...)- Share what you learned
Tools
Public Knowledge Base
search_kb(query)
Search 16k+ error solutions and fixes.
search_kb("Cannot find module 'express'")
// Returns: npm install express (92% success rate)
search_skills(query, max_results?)
Search 223+ reusable skills and workflows.
search_skills("deployment")
// Returns: Top 20 deployment-related skills
get_skill(skill_id)
Load full details of a specific skill.
get_skill(19417)
// Returns: Complete skill instructions
count_skills()
Get total number of skills in database.
count_skills()
// Returns: { total: 223 }
contribute_solution(query, solution, category?)
Share a fix you discovered with the community.
contribute_solution(
"ECONNREFUSED 127.0.0.1:5432",
"Start PostgreSQL: brew services start postgresql",
"database"
)
report_outcome(solution_id, outcome)
Report if a solution worked. Improves rankings.
report_outcome(123, "success") // or "failure"
Project Knowledge Base (Hive)
init_hive(project_id, project_name, storage_choice?, project_path?)
Initialize your project's knowledge base with auto-scanning.
// Step 1: Get options
init_hive("my-app", "My App")
// Returns: storage options (cloud vs local)
// Step 2: Initialize with choice
init_hive("my-app", "My App", "cloud", "/path/to/project")
// Returns: user_id + confirmation (scans project automatically)
contribute_project(user_id, project_id, query, solution, category?, is_public?)
Add knowledge to your project hive.
contribute_project(
"your-user-id",
"my-app",
"How to deploy this project?",
"Run: npm run build && npm run deploy",
"deployment",
false // private
)
search_project(user_id, query, project_id?, include_public?)
Search your project's knowledge base.
search_project(
"your-user-id",
"database schema",
"my-app"
)
// Returns: Your project-specific knowledge
Features
✅ 16k+ community solutions - Ranked by success rate ✅ 223+ reusable skills - Workflows and procedures ✅ Auto-scanning - Detects tech stack, architecture, database on setup ✅ Cloud sync - 10x rate limits (1000/hour) + access everywhere ✅ Private by default - Your project knowledge stays yours ✅ FTS search - Fast full-text search across solutions ✅ Success tracking - Solutions improve based on feedback
License
MIT
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。