@trendmoon/mcp-server
Advanced tools
TrendMoon MCP Server - Library and Standalone Server for Cryptocurrency and Social Data
A Model Context Protocol (MCP) server for accessing cryptocurrency and social trend data through the TrendMoon API.
npm install @trendmoon/mcp-server
npm install -g @trendmoon/mcp-server
trendmoon-mcp-server serve [options]
import { TrendmoonMcpServer } from '@trendmoon/mcp-server';
// Create server instance
const mcpServer = new TrendmoonMcpServer({
name: 'my-app-mcp',
version: '1.0.0'
});
// Get MCP server for integration in your app
const server = mcpServer.getMcpServer();
// Access TrendMoon services directly
const services = mcpServer.getServices();
const coinData = await services.coin.getCoinDetails({ symbol: 'BTC' });
trendmoon-mcp-server serve [options]
Options:
-t, --transport <type> Transport type (stdio|http) (default: "stdio")
-p, --port <number> HTTP port (default: "3000")
-h, --host <host> HTTP host (default: "0.0.0.0")
--no-cors Disable CORS
trendmoon-mcp-server serve --transport stdio
trendmoon-mcp-server serve --transport http --port 3000
For MCP Inspector, use: http://localhost:PORT/mcp
searchCoins : Search cryptocurrenciesgetCoinDetails : Get cryptocurrency detailsgetPlatforms : List available platformsgetHistoricalPrice : Historical prices with MACDcheckEMAPosition : Position relative to EMA 20/50getSocialTrend : Crypto social trendsgetProjectSummary : AI project summarygetKeywordTrend : Keyword trendssearchSocialPosts : Search social postsgetSocialTrends : Multiple social trendsgetTopicPosts : Posts related to specific topicsgetTopicNews : News related to specific topicsgetMessagesForChat : Chat messagessearchMessages : Search messagesgetChatByUsername : Chat detailssearchUsers : Search usersgetUserByIdentifier : User detailsThe server includes an analyzeCoinPerformance prompt that automatically combines:
// Library usage
const analysis = await mcpServer.getMcpServer().prompt("analyzeCoinPerformance", {
symbol: "BTC",
timeframe: "24h" // 1h, 24h, 7d, 30d
});
npm run inspect:direct
Opens MCP Inspector interface at http://127.0.0.1:6274
# Start in HTTP mode
npm run start:http:dev
# Test main MCP endpoint
curl -X POST http://localhost:3000/mcp \
-H "Content-Type: application/json" \
-d '{"jsonrpc":"2.0","id":1,"method":"tools/list","params":{}}'
# Test legacy endpoint (compatibility)
curl -X POST http://localhost:3000/ \
-H "Content-Type: application/json" \
-d '{"jsonrpc":"2.0","id":1,"method":"initialize","params":{"protocolVersion":"2024-11-05","capabilities":{},"clientInfo":{"name":"test-client","version":"1.0.0"}}}'
# Health check
curl http://localhost:3000/health
# Server info
curl http://localhost:3000/info
When running in HTTP mode, you can connect MCP Inspector to:
http://localhost:3000/mcp
src/
├── lib/ # Library code
│ ├── server/
│ │ ├── TrendmoonMcpServer.ts
│ │ └── types.ts
│ ├── tools/ # MCP tools
│ └── index.ts # Main library export
├── standalone/ # Standalone server code
│ ├── http/
│ │ └── HttpTransport.ts
│ ├── stdio/
│ │ └── StdioTransport.ts
│ └── server.ts
├── cli.ts # Command line interface
└── index.ts # Root entry point
The server supports various environment variables for configuration. Copy .env.example to .env and configure as needed:
# TrendMoon API Configuration
TRENDMOON_API_URL=https://api.qa.trendmoon.ai
TRENDMOON_API_KEY=xxxxxxxxx
# LLM Configuration (for AI features)
LLM_API_KEY="sk-xxxx"
LLM_BASE_URL="https://openrouter.ai/api/v1"
LLM_MODEL_NAME="openai/gpt-3.5-turbo"
# Debug and Development
DEBUG_MODE=false
| Variable | Description | Required | Default |
|---|---|---|---|
TRENDMOON_API_URL | TrendMoon API base URL | No | https://api.qa.trendmoon.ai |
TRENDMOON_API_KEY | Your TrendMoon API key for authentication | Yes | - |
LLM_API_KEY | API key for LLM provider (OpenRouter, OpenAI, etc.) | Yes | - |
LLM_BASE_URL | Base URL for LLM API calls | No | https://api.openai.com/v1 |
LLM_MODEL_NAME | Model name to use for AI features | No | gpt-3.5-turbo |
DEBUG_MODE | Enable debug logging and verbose output | No | false |
TrendMoon API Key:
TRENDMOON_API_KEY environment variableLLM API Key (for enhanced AI features):
LLM_API_KEY and configure LLM_BASE_URL accordinglyDevelopment (.env):
TRENDMOON_API_URL=https://api.qa.trendmoon.ai
TRENDMOON_API_KEY=your-dev-api-key
LLM_API_KEY="sk-your-openrouter-key"
LLM_BASE_URL="https://openrouter.ai/api/v1"
LLM_MODEL_NAME="openai/gpt-3.5-turbo"
DEBUG_MODE=true
Production:
TRENDMOON_API_URL=https://api.trendmoon.app
TRENDMOON_API_KEY=your-prod-api-key
LLM_API_KEY="sk-your-production-key"
LLM_BASE_URL="https://openrouter.ai/api/v1"
LLM_MODEL_NAME="openai/gpt-4"
DEBUG_MODE=false
FROM node:18-alpine
WORKDIR /app
COPY package*.json ./
RUN npm ci --only=production
COPY dist/ ./dist/
EXPOSE 3000
CMD ["npm", "run", "start:http"]
version: '3.8'
services:
trendmoon-mcp:
build: .
ports:
- "3000:3000"
environment:
- NODE_ENV=production
- TRENDMOON_API_URL=https://api.trendmoon.app
- TRENDMOON_API_KEY=xxxxxxx
- LLM_API_KEY=sk-your-api-key
- LLM_BASE_URL=https://openrouter.ai/api/v1
- LLM_MODEL_NAME=openai/gpt-4
- DEBUG_MODE=false
restart: unless-stopped
import { TrendmoonMcpServer, startStandaloneServer } from '@trendmoon/mcp-server';
// Library mode
const mcpServer = new TrendmoonMcpServer();
const tools = await mcpServer.getMcpServer().tools.list();
// Programmatic standalone server
await startStandaloneServer({
transport: 'http',
http: { port: 3000 },
server: { name: 'my-custom-server' }
});
# Via CLI
trendmoon-mcp-server serve --transport http &
# Via curl (preferred endpoint)
curl -X POST http://localhost:3000/mcp \
-H "Content-Type: application/json" \
-d '{
"jsonrpc": "2.0",
"id": 1,
"method": "tools/call",
"params": {
"name": "getCoinDetails",
"arguments": {"symbol": "BTC"}
}
}'
# Via legacy endpoint (for compatibility)
curl -X POST http://localhost:3000/ \
-H "Content-Type: application/json" \
-d '{
"jsonrpc": "2.0",
"id": 1,
"method": "initialize",
"params": {
"protocolVersion": "2024-11-05",
"capabilities": {},
"clientInfo": {"name": "test-client", "version": "1.0.0"}
}
}'
Start the server in HTTP mode:
trendmoon-mcp-server serve --transport http --port 3000
Open MCP Inspector and connect to:
http://localhost:3000/mcp
curl http://localhost:3000/info
Response includes server details, endpoints, active sessions, and usage instructions.
tools/list : List all available toolstools/call : Execute a tool with parametersprompts/list : List all available promptsprompts/get : Get a specific prompt{
"jsonrpc": "2.0",
"id": 1,
"result": {
"content": [
{
"type": "text",
"text": "..."
}
]
}
}
{
"status": "ready",
"timestamp": "2024-01-01T00:00:00.000Z",
"server": "TrendMoon MCP Server",
"transport": "Streamable HTTP",
"sessions": 0,
"mcpConnected": true
}
{
"name": "TrendMoon MCP Server",
"version": "1.0.0",
"transport": "Streamable HTTP",
"endpoints": {
"mcp": "/mcp (POST, GET, DELETE)",
"health": "/health",
"info": "/info"
},
"activeSessions": 0,
"protocol": "MCP Streamable HTTP Transport",
"mcpConnected": true,
"usage": {
"initialize": "POST /mcp with initialize request",
"requests": "POST /mcp with mcp-session-id header",
"notifications": "GET /mcp with mcp-session-id header (SSE)",
"terminate": "DELETE /mcp with mcp-session-id header"
}
}
The HTTP transport uses session-based communication:
initialize request to POST /mcpmcp-session-id headerGET /mcp with session IDDELETE /mcp with session IDgit clone https://github.com/trendmoon/mcp-server.git
cd mcp-server
npm install
cp .env.example .env
# Edit .env with your API keys and configuration
npm run build
npm run dev # STDIO mode
npm run dev:http # HTTP mode (port 3008)
npm run build # Build
npm run lint # Linting
npm test # Tests
npm run inspect:direct # MCP Inspector
curl http://localhost:3000/health
curl http://localhost:3000/info
git checkout -b feature/AmazingFeature)git commit -m 'Add some AmazingFeature')git push origin feature/AmazingFeature)MIT License - see the LICENSE file for details.
Made with ❤️ by the TrendMoon team
This package uses GitHub Actions for automated publishing. To release a new version:
package.json:npm version patch # For bug fixes
npm version minor # For new features
npm version major # For breaking changes
Create a new release in GitHub:
v1.0.1 (matching your package.json version)The GitHub Action will automatically:
For manual publishing:
# Ensure you're logged in
npm login
# Check what will be included in the package
npm pack --dry-run
# Publish the package
npm publish --access public
Note: You must have appropriate npm access to the @trendmoon organization to publish.
FAQs
TrendMoon MCP Server - Library and Standalone Server for Cryptocurrency and Social Data
The npm package @trendmoon/mcp-server receives a total of 0 weekly downloads. As such, @trendmoon/mcp-server popularity was classified as not popular.
We found that @trendmoon/mcp-server demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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