A Dart plugin for implementing Model Context Protocol (MCP) servers. This plugin allows Flutter applications to expose data, functionality, and interaction patterns to Large Language Model (LLM) applications in a standardized way.
This package implements the Model Context Protocol (MCP) specification versions 2024-11-05
and 2025-03-26
.
Add the package to your pubspec.yaml
:
dependencies:
mcp_server: ^0.1.2
Or install via command line:
dart pub add mcp_server
import 'package:mcp_server/mcp_server.dart';
void main() {
// Create a server
final server = McpServer.createServer(
name: 'Example Server',
version: '1.0.0',
capabilities: ServerCapabilities(
tools: true,
resources: true,
prompts: true,
),
);
// Add a simple calculator tool
server.addTool(
name: 'calculator',
description: 'Perform basic calculations',
inputSchema: {
'type': 'object',
'properties': {
'operation': {
'type': 'string',
'enum': ['add', 'subtract', 'multiply', 'divide'],
'description': 'Mathematical operation to perform'
},
'a': {
'type': 'number',
'description': 'First operand'
},
'b': {
'type': 'number',
'description': 'Second operand'
}
},
'required': ['operation', 'a', 'b']
},
handler: (arguments) async {
final operation = arguments['operation'] as String;
final a = (arguments['a'] is int) ? (arguments['a'] as int).toDouble() : arguments['a'] as double;
final b = (arguments['b'] is int) ? (arguments['b'] as int).toDouble() : arguments['b'] as double;
double result;
switch (operation) {
case 'add':
result = a + b;
break;
case 'subtract':
result = a - b;
break;
case 'multiply':
result = a * b;
break;
case 'divide':
if (b == 0) {
return CallToolResult(
[TextContent(text: 'Division by zero error')],
isError: true,
);
}
result = a / b;
break;
default:
return CallToolResult(
[TextContent(text: 'Unknown operation: $operation')],
isError: true,
);
}
return CallToolResult([TextContent(text: 'Result: $result')]);
},
);
// Add a resource
server.addResource(
uri: 'time://current',
name: 'Current Time',
description: 'Get the current date and time',
mimeType: 'text/plain',
handler: (uri, params) async {
final now = DateTime.now().toString();
return ReadResourceResult(
content: now,
mimeType: 'text/plain',
contents: [\
ResourceContent(\
uri: uri,\
text: now,\
),\
],
);
},
);
// Add a template prompt
server.addPrompt(
name: 'greeting',
description: 'Generate a customized greeting',
arguments: [\
PromptArgument(\
name: 'name',\
description: 'Name to greet',\
required: true,\
),\
PromptArgument(\
name: 'formal',\
description: 'Whether to use formal greeting style',\
required: false,\
),\
],
handler: (arguments) async {
final name = arguments['name'] as String;
final formal = arguments['formal'] as bool? ?? false;
final String systemPrompt = formal
? 'You are a formal assistant. Address the user with respect and formality.'
: 'You are a friendly assistant. Be warm and casual in your tone.';
final messages = [\
Message(\
role: MessageRole.system.toString().split('.').last,\
content: TextContent(text: systemPrompt),\
),\
Message(\
role: MessageRole.user.toString().split('.'').last,\
content: TextContent(text: 'Please greet $name'),\
),\
];
return GetPromptResult(
description: 'A ${formal ? 'formal' : 'casual'} greeting for $name',
messages: messages,
);
},
);
// Connect to transport
final transport = McpServer.createStdioTransport();
server.connect(transport);
}
The Server
class is your core interface to the MCP protocol. It handles connection management, protocol compliance, and message routing:
final server = McpServer.createServer(
name: 'My App',
version: '1.0.0',
capabilities: ServerCapabilities(
tools: true,
resources: true,
prompts: true,
),
);
Resources are how you expose data to LLMs. They're similar to GET endpoints in a REST API - they provide data but shouldn't perform significant computation or have side effects:
// Static resource
server.addResource(
uri: 'config://app',
name: 'App Configuration',
description: 'Application configuration data',
mimeType: 'text/plain',
handler: (uri, params) async {
final configData = "app_name=MyApp\nversion=1.0.0\ndebug=false";
return ReadResourceResult(
content: configData,
mimeType: 'text/plain',
contents: [\
ResourceContent(\
uri: uri,\
text: configData,\
),\
],
);
},
);
// Resource with URI template
server.addResource(
uri: 'file://{path}',
name: 'File Resource',
description: 'Access files on the system',
mimeType: 'application/octet-stream',
uriTemplate: {
'type': 'object',
'properties': {
'path': {
'type': 'string',
'description': 'Path to the file'
}
}
},
handler: (uri, params) async {
// Extract path and read file content
final path = params['path'] ?? uri.substring('file://'.length);
final content = await File(path).readAsString();
return ReadResourceResult(
content: content,
mimeType: 'text/plain',
contents: [\
ResourceContent(\
uri: uri,\
text: content,\
),\
],
);
},
);
Tools let LLMs take actions through your server. Unlike resources, tools are expected to perform computation and have side effects:
server.addTool(
name: 'currentDateTime',
description: 'Get the current date and time',
inputSchema: {
'type': 'object',
'properties': {
'format': {
'type': 'string',
'description': 'Output format (full, date, time)',
'default': 'full'
}
},
'required': []
},
handler: (args) async {
final format = args['format'] as String? ?? 'full';
final now = DateTime.now();
String result;
switch (format) {
case 'date':
result = '${now.year}-${now.month.toString().padLeft(2, '0')}-${now.day.toString().padLeft(2, '0')}';
break;
case 'time':
result = '${now.hour.toString().padLeft(2, '0')}:${now.minute.toString().padLeft(2, '0')}:${now.second.toString().padLeft(2, '0')}';
break;
case 'full':
default:
result = now.toIso8601String();
break;
}
return CallToolResult([TextContent(text: result)]);
},
);
Prompts are reusable templates that help LLMs interact with your server effectively:
server.addPrompt(
name: 'codeReview',
description: 'Generate a code review for a code snippet',
arguments: [\
PromptArgument(\
name: 'code',\
description: 'Code to review',\
required: true,\
),\
PromptArgument(\
name: 'language',\
description: 'Programming language of the code',\
required: true,\
),\
],
handler: (args) async {
final code = args['code'] as String;
final language = args['language'] as String;
final systemPrompt = '''
You are an expert code reviewer. Review the provided code with these guidelines:
1. Identify potential bugs or issues
2. Suggest optimizations for performance or readability
3. Highlight good practices used in the code
4. Provide constructive feedback for improvements
Be specific in your feedback and provide code examples when suggesting changes.
''';
final messages = [\
Message(\
role: MessageRole.system.toString().split('.').last,\
content: TextContent(text: systemPrompt),\
),\
Message(\
role: MessageRole.user.toString().split('.').last,\
content: TextContent(text: 'Please review this $language code:\n\n```$language\n$code\n```'),\
),\
];
return GetPromptResult(
description: 'Code review for $language code',
messages: messages,
);
},
);
For command-line tools and direct integrations:
final transport = McpServer.createStdioTransport();
await server.connect(transport);
For HTTP-based communication:
final transport = McpServer.createSseTransport(
endpoint: '/sse',
messagesEndpoint: '/messages',
port: 8080,
);
await server.connect(transport);
The package includes a built-in logging utility:
// Configure logging
log.configure(level: LogLevel.debug, includeTimestamp: true, useColor: true);
// Log messages at different levels
log.debug('Debugging information');
log.info('Important information');
log.warning('Warning message');
log.error('Error message');
The MCP protocol defines three core primitives that servers can implement:
Primitive | Control | Description | Example Use |
---|---|---|---|
Prompts | User-controlled | Interactive templates invoked by user choice | Slash commands, menu options |
Resources | Application-controlled | Contextual data managed by the client application | File contents, API responses |
Tools | Model-controlled | Functions exposed to the LLM to take actions | API calls, data updates |
The server includes built-in caching for resources to improve performance:
// Use built-in caching mechanism
final cached = server.getCachedResource(uri);
if (cached != null) {
return cached.content;
}
// Cache a resource for future use
server.cacheResource(uri, result, Duration(minutes: 10));
// Invalidate cache
server.invalidateCache(uri);
For long-running operations, you can report progress to clients:
server.addTool(
name: 'longRunningOperation',
description: 'Perform a long-running operation with progress reporting',
inputSchema: { /* ... */ },
handler: (args) async {
// Register operation for progress tracking
final operationId = server.registerOperation(sessionId, 'longRunningOperation');
// Update progress as the operation progresses
for (int i = 0; i < 10; i++) {
// Check if operation was cancelled
if (server.isOperationCancelled(operationId)) {
return CallToolResult([TextContent(text: 'Operation cancelled')], isError: true);
}
// Update progress (0.0 to 1.0)
server.notifyProgress(operationId, i / 10, 'Processing step $i of 10...');
// Do work...
await Future.delayed(Duration(seconds: 1));
}
return CallToolResult([TextContent(text: 'Operation completed successfully')]);
},
);
The server provides built-in health metrics:
// Get server health information
final health = server.getHealth();
log.debug('Server uptime: ${health.uptime.inSeconds} seconds');
log.debug('Connected sessions: ${health.connectedSessions}');
log.debug('Registered tools: ${health.registeredTools}');
// Track custom metrics
server.incrementMetric('api_calls');
final timer = server.startTimer('operation_duration');
// ... perform operation
server.stopTimer('operation_duration');
Check out the example directory for a complete sample application.
Please file any issues, bugs, or feature requests in our issue tracker.
This project is licensed under the MIT License - see the LICENSE file for details.