Elasticsearch MCP (VSee Fork)
Provides specialized analytics tools for querying VSee's Elasticsearch stats-\* indices, including account/group metrics, visit trends, platform breakdowns, rating distributions, and subscription tier analysis.
README
Elasticsearch MCP (VSee Fork)
Modified MCP server with hardcoded schemas matching VSee's Elasticsearch indexes. Specialized analytics tools optimized for stats- indices.*
elasticsearch-mcp-vsee is a modified Model Context Protocol (MCP) server that provides specialized analytics tools for Elasticsearch clusters, optimized for VSee's stats-* indices. This fork features hardcoded schemas and field names that match VSee's specific Elasticsearch index structure, enabling specialized tools for account/group analytics, visit trends, platform breakdowns, and rating distributions. Built with TypeScript and optimized for Elastic Cloud environments, it offers comprehensive analytics capabilities with enterprise-grade security features.
🚀 Features
- 🔐 Secure by Design: Input validation, script sanitization, injection prevention
- ☁️ Elastic Cloud Ready: Native support for cloud ID and API key authentication
- ⚡ High Performance: Connection pooling, optimized query execution, efficient aggregations
- 🛠️ Comprehensive Tools: 11 specialized tools for analytics, summaries, and data exploration
- 📊 Advanced Querying: Full Elasticsearch DSL support with aggregations and highlighting
- 🔍 Smart Validation: Zod-based schemas with security-first validation
- 📝 Full TypeScript: Complete type safety with strict null checks
🎯 Purpose
This MCP server is designed for VSee's Open WebUI deployment to provide specialized analytics tools for querying VSee's Elasticsearch stats-* indices. It integrates with VSee's Open WebUI infrastructure via MCPO (MCP OpenAPI bridge) to expose Elasticsearch analytics capabilities to LLMs.
📦 Usage with VSee's Open WebUI Deployment
This MCP server is automatically loaded by VSee's Open WebUI deployment through the MCP configuration. It connects to VSee's Elasticsearch deployment to provide analytics on visit statistics, account/group metrics, platform breakdowns, and more.
Configuration
The MCP server is configured in vsee/mcp/config.json:
{
"mcpServers": {
"elasticsearch": {
"command": "npx",
"args": ["-y", "elasticsearch-mcp-vsee"],
"env": {
"ELASTIC_NODE": "https://omtm.es.us-east-1.aws.found.io",
"ELASTIC_USERNAME": "your-username",
"ELASTIC_PASSWORD": "your-password",
"NODE_TLS_REJECT_UNAUTHORIZED": "0"
}
}
}
}
The Open WebUI deployment automatically loads this configuration and starts the MCP server via MCPO, making all 11 tools available to the LLM for querying Elasticsearch data.
🔄 Updating and Publishing
Making Changes
- Develop locally: Make changes to the code in
elasticsearch-mcp/ - Test your changes: Use
npm run test:toolsto test against your Elasticsearch instance - Build: Run
npm run buildto compile TypeScript - Publish: Publish to npm with
npm publish --access public- Make sure to increment the version in
package.jsonfirst
- Make sure to increment the version in
Updating VSee's Deployment
After publishing a new version to npm:
-
Update
vsee/mcp/config.json: Change the package version in theargsarray:{ "mcpServers": { "elasticsearch": { "command": "npx", "args": ["-y", "elasticsearch-mcp-vsee@0.5.0"], // Update version here "env": { ... } } } } -
Restart the MCPO service: The MCPO container will automatically download and use the new version on restart:
docker compose -f docker-compose.vsee.yaml restart mcpo -
Verify: Check that the new version is loaded by examining the MCPO logs or testing the tools in Open WebUI.
Note: You can also use @latest to always pull the latest version, but specifying a version number is recommended for production stability.
🛠️ Available Tools
| Tool | Description | Use Cases |
|---|---|---|
get_index_fields |
Discover index fields and types | Schema exploration, field discovery |
top_change |
Find top accounts or groups with highest visit increase/decrease | Trend analysis, account/group monitoring |
get_subscription_breakdown |
Compare subscription tiers with metrics per tier | Subscription-tier analysis and comparisons |
get_platform_breakdown |
Platform or platform version breakdown (provider/patient, platform/version) | Platform adoption, device preferences, version analysis |
get_rating_distribution |
Rating histograms with statistics | Satisfaction analysis |
get_visit_trends |
Time series visit trends (daily/weekly/monthly) | Trend visualization |
get_usage_summary |
Comprehensive metrics summary with flexible filtering and grouping | Multi-dimensional analysis and comparisons |
📋 Tool Examples
Get Account Summary
{
"tool": "get_account_summary",
"arguments": {
"account": "example-customer",
"startDate": "now-1y",
"endDate": "now"
}
}
Get Top Accounts by Growth
{
"tool": "top_change",
"arguments": {
"groupBy": "account",
"direction": "increase",
"topN": 10,
"currentPeriodDays": 30,
"previousPeriodDays": 30
}
}
Get Platform Breakdown
{
"tool": "get_platform_breakdown",
"arguments": {
"role": "provider",
"breakdownType": "version",
"topN": 10,
"startDate": "now-30d",
"endDate": "now"
}
}
Get Visit Trends
{
"tool": "get_visit_trends",
"arguments": {
"interval": "daily",
"startDate": "now-30d",
"endDate": "now",
"groupBy": "subscription"
}
}
⚙️ Configuration
Environment Variables
The MCP server reads configuration from environment variables. These are set in vsee/mcp/config.json under the env section:
| Variable | Description | Required | Example |
|---|---|---|---|
ELASTIC_NODE |
Elasticsearch URL | Yes | https://omtm.es.us-east-1.aws.found.io |
ELASTIC_USERNAME |
Basic auth username | Yes | your-username |
ELASTIC_PASSWORD |
Basic auth password | Yes | your-password |
NODE_TLS_REJECT_UNAUTHORIZED |
Disable TLS verification (for self-signed certs) | No | "0" |
Alternative: Elastic Cloud Authentication
If using Elastic Cloud with cloud ID and API key:
| Variable | Description | Required |
|---|---|---|
ELASTIC_CLOUD_ID |
Elastic Cloud deployment ID | Yes* |
ELASTIC_API_KEY |
Elasticsearch API key | Yes* |
*Either ELASTIC_CLOUD_ID + ELASTIC_API_KEY OR ELASTIC_NODE + ELASTIC_USERNAME + ELASTIC_PASSWORD is required
🔒 Security Features
Input Validation
- Zod Schemas: Strict type validation for all inputs
- Field Name Validation: Prevents reserved field usage
- Size Limits: Document size, array length, string length limits
- Depth Validation: Prevents deeply nested objects/queries
Script Security
- Script Sanitization: Blocks dangerous script patterns
- Parameter Validation: Validates script parameters
- Execution Limits: Prevents resource exhaustion
Query Security
- Injection Prevention: Sanitizes and validates all queries
- Script Query Blocking: Prevents script-based queries in sensitive operations
- Rate Limiting: Protects against abuse
Data Protection
- Credential Masking: Never logs sensitive information
- Secure Connections: TLS/SSL support
- Access Control: Validates permissions before operations
🏗️ Architecture
┌─────────────────┐ ┌─────────────────┐ ┌─────────────────┐
│ MCP Client │◄──►│Elasticsearch MCP│◄──►│ Elasticsearch │
│ (Claude, etc.) │ │ Server │ │ Cluster │
└─────────────────┘ └─────────────────┘ └─────────────────┘
│
┌─────────────┐
│ Tools │
│ │
│ • search │
│ • fields │
│ • summaries │
│ • trends │
│ • analytics │
└─────────────┘
📊 Performance
Benchmarks
- Search: <500ms average response time
- Aggregations: Optimized for large-scale analytics
- Memory Usage: <100MB for typical operations
- Concurrent Requests: Up to 10 simultaneous operations
Optimization Features
- Connection Pooling: Reuses Elasticsearch connections
- Optimized Queries: Efficient aggregation pipelines
- Smart Caching: Reduced redundant queries
- Health Monitoring: Automatic reconnection on failures
🔧 Development
Setup Development Environment
# Install dependencies
npm install
# Set up environment variables
export ELASTIC_NODE="https://your-elasticsearch-url"
export ELASTIC_USERNAME="your-username"
export ELASTIC_PASSWORD="your-password"
export NODE_TLS_REJECT_UNAUTHORIZED="0" # If needed for self-signed certs
# Run in development mode
npm run dev
# Test tools against live Elasticsearch
npm run test:tools
# Build for production
npm run build
# Publish new version (after incrementing version in package.json)
npm publish --access public
Project Structure
elasticsearch-mcp/
├── src/
│ ├── tools/ # MCP tool implementations
│ ├── elasticsearch/ # ES client and connection management
│ ├── validation/ # Input validation schemas
│ ├── errors/ # Error handling utilities
│ ├── config.ts # Configuration management
│ ├── logger.ts # Structured logging
│ └── server.ts # Main MCP server
├── tests/ # Test suite
└── build/ # Compiled output
📄 License
This project is licensed under the MIT License - see the LICENSE file for details.
🏷️ Version History
- v0.5.0 - Added
find_entities_by_metrictool with multi-metric filtering support, updated default limits - v0.4.0 - Tool consolidation: merged 14 tools into 11 specialized analytics tools
- v0.3.0 - Specialized analytics tools for stats-* indices
- Full changelog: CHANGELOG.md
🔗 Links
Built for VSee by VSee
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。