Labsco
evolsb logo

FastIntercom

from evolsb

A high-performance MCP server for analyzing Intercom conversations with fast, local access via caching and background sync.

🔥🔥🔥✓ VerifiedPaid serviceNeeds API keys
#email#analytics#payments#database#devops#git#monitoring#customer-support

FastIntercom MCP Server

High-performance Model Context Protocol (MCP) server for Intercom conversation analytics. Provides fast, local access to Intercom conversations through intelligent caching and background synchronization.

Features

  • 🚀 Fast Local Access: Sub-100ms response times for conversation searches
  • 🧠 Intelligent Sync: Request-triggered background updates ensure fresh data
  • 💾 Efficient Storage: SQLite-based local storage (~2KB per conversation)
  • 🔍 Powerful Search: Natural language timeframes and text search
  • ⚡ MCP Integration: Direct integration with Claude Desktop and MCP clients

Architecture

Intelligent Sync Strategy

FastIntercom uses a sophisticated caching strategy:

  1. Immediate Response: MCP requests return data instantly from local cache
  2. Background Sync: Stale timeframes trigger background updates
  3. Smart Triggers: System learns from request patterns to optimize sync timing
  4. Fresh Data: Next request gets updated data from background sync

Components

  • Database: SQLite with optimized schema for fast searches
  • Sync Service: Background service with intelligent refresh logic
  • MCP Server: Model Context Protocol implementation
  • CLI Interface: Command-line tools for management and monitoring

Development

Testing

Quick Tests

# Unit tests
pytest tests/

# Integration test (requires API key)
./scripts/run_integration_test.sh

# Docker test
./scripts/test_docker_install.sh

Comprehensive Testing

# Full unit test suite with coverage
pytest tests/ --cov=fast_intercom_mcp

# Integration test with performance report
./scripts/run_integration_test.sh --performance-report

# Docker clean install test
./scripts/test_docker_install.sh --with-api-test

# Performance benchmarking
./scripts/run_performance_test.sh

CI/CD Integration

  • Fast Check: Runs on every PR (unit tests, linting, imports)
  • Integration Test: Manual/weekly trigger with real API data
  • Docker Test: On releases and deployment validation

For detailed testing procedures, see:

Local Development

# Install in development mode
pip install -e .

# Run with verbose logging
fast-intercom-mcp --verbose status

# Monitor logs in real-time
tail -f ~/.fast-intercom-mcp/logs/fast-intercom-mcp.log

Performance

Typical Performance Metrics

  • Response Time: <100ms for cached queries
  • Storage Efficiency: ~2KB per conversation average
  • Sync Speed: 10-50 conversations/second
  • Memory Usage: <100MB for server process

Storage Requirements

  • Small workspace: 100-500 conversations, ~5-25 MB
  • Medium workspace: 1,000-5,000 conversations, ~50-250 MB
  • Large workspace: 10,000+ conversations, ~500+ MB

API Reference

MCP Tools

search_conversations

Search conversations with flexible filters.

Parameters:

  • query (string): Text to search in conversation messages
  • timeframe (string): Natural language timeframe ("last 7 days", "this month", etc.)
  • customer_email (string): Filter by specific customer email
  • limit (integer): Maximum conversations to return (default: 50)

get_conversation

Get full details of a specific conversation.

Parameters:

  • conversation_id (string, required): Intercom conversation ID

get_server_status

Get server status and statistics.

Parameters: None

sync_conversations

Trigger manual conversation sync.

Parameters:

  • force (boolean): Force full sync even if recent data exists

Support

  • Issues: GitHub Issues
  • Documentation: This README and inline code documentation
  • Logs: Check ~/.fast-intercom-mcp/logs/fast-intercom-mcp.log for detailed information