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🔧 MCP (Model Context Protocol) Integration Guide

NeuroLink Universal AI Platform with External Server Connectivity

📖 Overview​

NeuroLink now supports the Model Context Protocol (MCP) for seamless integration with external servers and tools. This enables unlimited extensibility through the growing MCP ecosystem while maintaining NeuroLink's simple interface.

Enhanced MCP Integration with Factory Patterns​

import { NeuroLink } from "@juspay/neurolink";

const neurolink = new NeuroLink();

// NEW: Enhanced MCP integration with generate()
const result = await neurolink.generate({
  input: { text: "List files in current directory using MCP" },
  provider: "google-ai",
  disableTools: false, // Enable MCP tool usage
});

// Alternative approach using legacy method (backward compatibility)
const legacyResult = await neurolink.generate({
  prompt: "List files in current directory using MCP",
  provider: "google-ai",
  disableTools: false,
});

What is MCP?​

The Model Context Protocol is a standardized way for AI applications to connect to external tools and data sources. It enables:

  • ✅ External Tool Integration - Connect to filesystem, databases, APIs, and more
  • ✅ Standardized Communication - JSON-RPC 2.0 protocol over multiple transports
  • ✅ Tool Discovery - Automatic discovery of available tools and capabilities
  • ✅ Secure Execution - Controlled access to external resources
  • ✅ Ecosystem Compatibility - Works with 65+ community servers

🚀 Quick Start​

# Install filesystem server for file operations
npx neurolink mcp install filesystem

# Install GitHub server for repository management
npx neurolink mcp install github

# Install database server for SQL operations
npx neurolink mcp install postgres

2. Test Connectivity​

# Test server connectivity and discover tools
npx neurolink mcp test filesystem

# List all configured servers with status
npx neurolink mcp list --status

3. 🆕 Programmatic Server Management​

NEW! Add MCP servers dynamically at runtime:

import { NeuroLink } from "@juspay/neurolink";
const neurolink = new NeuroLink();

// Add external servers dynamically
await neurolink.addExternalMCPServer("bitbucket", {
  command: "npx",
  args: ["-y", "@nexus2520/bitbucket-mcp-server"],
  env: {
    BITBUCKET_USERNAME: "your-username",
    BITBUCKET_APP_PASSWORD: "your-token",
  },
});

// Add database integration
await neurolink.addExternalMCPServer("database", {
  command: "node",
  args: ["./custom-db-server.js"],
  env: { DB_CONNECTION: "postgresql://..." },
});

// Verify registration
const status = await neurolink.getMCPStatus();
console.log("Active servers:", status.totalServers);

4. Execute Tools (Planned)​

This feature is planned for a future release.

# Execute tools from connected servers (planned — not yet implemented)
npx neurolink mcp exec filesystem read_file --params '{"path": "README.md"}'
npx neurolink mcp exec github create_issue --params '{"title": "New feature", "body": "Description"}'

📋 MCP CLI Commands Reference​

Server Management​

neurolink mcp install <server>

Available servers:

  • filesystem - File and directory operations
  • github - GitHub repository management
  • postgres - PostgreSQL database operations
  • brave-search - Web search capabilities
  • puppeteer - Browser automation

Example:

neurolink mcp install filesystem
# ✅ Installed MCP server: filesystem
# 💡 Test it with: neurolink mcp test filesystem

Add Custom Servers​

neurolink mcp add <name> <command> [options]

Options:

  • --args - Command arguments (array)
  • --transport - Transport type (stdio|sse|websocket|http)
  • --url - URL for SSE/WebSocket/HTTP transport
  • --headers - HTTP headers for authentication (JSON)
  • --env - Environment variables (JSON)
  • --cwd - Working directory

Examples:

# Add custom server with arguments
neurolink mcp add myserver "python /path/to/server.py" --args "arg1,arg2"

# Add SSE server
neurolink mcp add webserver "http://localhost:8080" --transport sse --url "http://localhost:8080/mcp"

# Add HTTP remote server with authentication
neurolink mcp add remote-api "https://api.example.com/mcp" --transport http --url "https://api.example.com/mcp" --headers '{"Authorization": "Bearer YOUR_TOKEN"}'

# Add server with environment variables
neurolink mcp add dbserver "npx db-mcp-server" --env '{"DB_URL": "postgresql://..."}'

List Configured Servers​

neurolink mcp list [--status]

Example output:

📋 Configured MCP servers (2):

🔧 filesystem
   Command: npx -y @modelcontextprotocol/server-filesystem /
   Transport: stdio
✔ filesystem: ✅ Available

🔧 github
   Command: npx @modelcontextprotocol/server-github
   Transport: stdio
✖ github: ❌ Not available

Test Server Connectivity​

neurolink mcp test <server>

Example output:

🔍 Testing MCP server: filesystem

✔ ✅ Connection successful!

📋 Server Capabilities:
   Protocol Version: 2024-11-05
   Tools: ✅ Supported

🛠️  Available Tools:
   • read_file: Read file contents from filesystem
   • write_file: Create/overwrite files
   • edit_file: Make line-based edits
   • create_directory: Create directories
   • list_directory: List directory contents
   + 6 more tools...

Remove Servers​

neurolink mcp remove <server>

⚙️ Configuration​

External Server Configuration​

External MCP servers are configured in .mcp-config.json:

{
  "mcpServers": {
    "filesystem": {
      "name": "filesystem",
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-filesystem", "/"],
      "transport": "stdio"
    },
    "github": {
      "name": "github",
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-github"],
      "transport": "stdio"
    },
    "custom": {
      "name": "custom",
      "command": "python",
      "args": ["/path/to/server.py"],
      "transport": "stdio",
      "cwd": "/project/directory"
    }
  }
}

Environment Variables​

Set these in your .env file for server authentication:

# Custom Server Configuration
CUSTOM_API_KEY=your-api-key
CUSTOM_ENDPOINT=https://api.example.com

🛠️ Available MCP Servers​

Filesystem Server​

Purpose: File and directory operations Installation: neurolink mcp install filesystem

Available Tools:

  • read_file - Read file contents
  • write_file - Create or overwrite files
  • edit_file - Make line-based edits
  • create_directory - Create directories
  • list_directory - List directory contents
  • directory_tree - Get recursive tree view
  • move_file - Move/rename files
  • search_files - Search for files by pattern
  • get_file_info - Get file metadata

GitHub Server​

Purpose: GitHub repository management Installation: neurolink mcp install github

Available Tools:

  • create_repository - Create new repositories
  • search_repositories - Search public repositories
  • get_file_contents - Read repository files
  • create_or_update_file - Modify repository files
  • create_issue - Create GitHub issues
  • create_pull_request - Create pull requests
  • fork_repository - Fork repositories

PostgreSQL Server​

Purpose: Database operations Installation: neurolink mcp install postgres

Available Tools:

  • read-query - Execute SELECT queries
  • write-query - Execute INSERT/UPDATE/DELETE queries
  • create-table - Create database tables
  • list-tables - List available tables
  • describe-table - Get table schema

Brave Search Server​

Purpose: Web search capabilities Installation: neurolink mcp install brave-search

Available Tools:

  • brave_web_search - Search the web
  • brave_local_search - Search for local businesses

Puppeteer Server​

Purpose: Browser automation Installation: neurolink mcp install puppeteer

Available Tools:

  • puppeteer_navigate - Navigate to URLs
  • puppeteer_screenshot - Take screenshots
  • puppeteer_click - Click elements
  • puppeteer_fill - Fill forms
  • puppeteer_evaluate - Execute JavaScript

🔧 Advanced Usage​

Transport Types​

STDIO Transport (Default)​

Best for local servers and CLI tools:

neurolink mcp add local-server "python server.py" --transport stdio

SSE Transport​

For web-based servers:

neurolink mcp add web-server "http://localhost:8080" --transport sse --url "http://localhost:8080/sse"

HTTP Transport (Streamable HTTP)​

For remote MCP servers with authentication, retry, and rate limiting:

neurolink mcp add remote-api "https://api.example.com/mcp" \
  --transport http \
  --url "https://api.example.com/mcp" \
  --headers '{"Authorization": "Bearer YOUR_TOKEN"}'

Configuration in .mcp-config.json:

{
  "mcpServers": {
    "remote-api": {
      "transport": "http",
      "url": "https://api.example.com/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_TOKEN"
      },
      "httpOptions": {
        "connectionTimeout": 30000,
        "requestTimeout": 60000,
        "idleTimeout": 120000,
        "keepAliveTimeout": 30000
      },
      "retryConfig": {
        "maxAttempts": 3,
        "initialDelay": 1000,
        "maxDelay": 30000,
        "backoffMultiplier": 2
      },
      "rateLimiting": {
        "requestsPerMinute": 60,
        "maxBurst": 10,
        "useTokenBucket": true
      }
    }
  }
}

HTTP Transport Features:

  • Custom headers for authentication (Bearer, API Key)
  • Configurable connection and request timeouts
  • Automatic retry with exponential backoff
  • Rate limiting with token bucket algorithm
  • OAuth 2.1 support with PKCE

See MCP HTTP Transport Guide for complete documentation.

Server Environment Configuration​

Pass environment variables to servers:

neurolink mcp add secure-server "npx secure-mcp" --env '{"API_KEY": "secret", "DEBUG": "true"}'

Working Directory​

Set server working directory:

neurolink mcp add project-server "python local-server.py" --cwd "/path/to/project"

🚀 Advanced MCP Features​

NeuroLink provides advanced MCP capabilities for production environments with multiple servers and complex tool ecosystems.

Tool Router​

Intelligent tool call routing for multi-server environments with round-robin, least-loaded, capability-based, and session affinity strategies.

Tool Cache​

Cache tool results with configurable LRU, FIFO, or LFU eviction strategies, pattern-based invalidation, and cache statistics.

Request Batcher​

Batch multiple tool calls for efficient execution with automatic batch sizing and server-grouped batching.

Tool Annotations​

Add safety metadata to tools (readOnly, destructive, idempotent) with automatic safety level inference and annotation-based filtering.

Custom MCP Servers​

Create custom MCP servers using the MCPServerBase abstract class with built-in tool registration, event emission, and lifecycle management.

Elicitation Protocol​

Interactive tool input during execution supporting text, select, multi-select, confirmation, file upload, and form elicitation types.

Multi-Server Manager​

Load balancing and coordination across multiple MCP servers with server groups and a unified tool interface.

Full Documentation: See the MCP Enhancements Guide for complete API reference, configuration options, and usage examples.

🚨 Troubleshooting​

Common Issues​

Server Not Available​

✖ server: ❌ Not available

Solutions:

  1. Check server installation: npm list -g @modelcontextprotocol/server-*
  2. Verify command path: which npx
  3. Test command manually: npx @modelcontextprotocol/server-filesystem /
  4. Check environment variables
  5. Verify network connectivity (for SSE servers)

Connection Timeout​

❌ Connection failed: Timeout connecting to MCP server

Solutions:

  1. Increase timeout (servers may need time to start)
  2. Check server logs for errors
  3. Verify server supports MCP protocol version 2024-11-05
  4. Test with simpler server first (filesystem)

Authentication Errors​

❌ Connection failed: Authentication required

Solutions:

  1. Set required environment variables
  2. Check API key/token validity
  3. Verify permissions for required resources
  4. Review server documentation for auth requirements

Tool Execution Errors​

❌ Tool execution failed: Invalid parameters

Solutions:

  1. Check tool parameter schema: neurolink mcp test <server>
  2. Validate JSON parameter format
  3. Review tool documentation
  4. Test with minimal parameters first

Debug Mode​

Enable verbose logging for troubleshooting:

export NEUROLINK_DEBUG=true
neurolink mcp test filesystem

🔗 Integration with AI Providers​

Using MCP Tools with AI Generation​

# Generate text that uses MCP tool results
neurolink generate "Analyze the README.md file and suggest improvements" --tools filesystem

# Stream responses that incorporate MCP data
neurolink stream "Create a GitHub issue based on the project status" --tools github

Multi-Tool Workflows​

# Combine multiple MCP servers in workflows
neurolink workflow "
1. Read project files (filesystem)
2. Analyze codebase (ai)
3. Create GitHub issue (github)
4. Update database (postgres)
"

📚 Resources​

Official MCP Resources​

Community Servers​

🚀 What's Next?​

Get Involved​

  • Report issues on GitHub
  • Join the MCP community
  • Contribute server integrations
  • Share usage examples

Ready to extend NeuroLink with unlimited external capabilities! 🌟