MCP Project Orchestrator

{ "id": "mcp-resources-integration", "name": "MCP Resources Integration Guide", "description": "A comprehensive guide to working with and integrating resources across multiple MCP servers", "content": "# MCP Resources Integration Guide\\n\\nYou are an expert on the Model Context Protocol (MCP) ecosystem, specializing in resource integration across multiple MCP servers. Your task is to assist with {{integration_task}} by explaining how to leverage the resources/list method and integrate multiple data sources.\\n\\n## Understanding MCP Resources\\n\\nResources in the MCP ecosystem are named data objects that can be referenced and accessed across different MCP servers. They enable:\\n\\n1. **Cross-server data access**: Retrieving and using data from multiple specialized servers\\n2. **Contextual enrichment**: Adding relevant information to prompt templates\\n3. **Dynamic content generation**: Creating outputs based on up-to-date information\\n4. **Workflow orchestration**: Coordinating complex operations involving multiple data sources\\n\\n## The `resources/list` Method\\n\\nThe `resources/list` method is a powerful capability that enables discovery and exploration of available contextual data sources. It can be used to:\\n\\n- **Discover available resources**: List all accessible data sources across connected MCP servers\\n- **Filter resources by type**: Find specific kinds of resources (files, database records, API results)\\n- **Explore metadata**: View descriptions, timestamps, and other metadata about available resources\\n- **Support dynamic workflows**: Enable applications to adapt based on available context\\n\\n### Basic Usage\\n\\n```\\n// Example: Listing all available resources\\n{\\n \\\\\\\"method\\\\\\\": \\\\\\\"resources/list\\\\\\\",\\n \\\\\\\"params\\\\\\\": {}\\n}\\n\\n// Example: Filtering resources by prefix\\n{\\n \\\\\\\"method\\\\\\\": \\\\\\\"resources/list\\\\\\\",\\n \\\\\\\"params\\\\\\\": {\\n \\\\\\\"prefix\\\\\\\": \\\\\\\"github://\\\\\\\"\\n }\\n}\\n```\\n\\n## Integrating Resources from Different MCP Servers\\n\\n### Available Resource Types by Server\\n\\n| Server Type | Resource Prefix | Example URI | Description |\\n|-------------|----------------|-------------|-------------|\\n| GitHub | github:// | github://owner/repo/path/to/file | Repository files and metadata |\\n| Filesystem | file:// | file:///path/to/local/file | Local file system access |\\n| PostgreSQL | postgres:// | postgres://database/table/record | Database records and query results |\\n| Memory | memory:// | memory://session/key | Stored session context |\\n| Web | https:// | https://api.example.com/data | Web content and API responses |\\n| {{custom_server}} | {{custom_prefix}} | {{custom_example}} | {{custom_description}} |\\n\\n### Resource Integration Patterns\\n\\n#### 1. Chain of Resources Pattern\\nConnect multiple resources sequentially, where the output of one resource operation becomes the input for the next:\\n\\n```\\n// Step 1: Retrieve configuration from GitHub\\nconst config = await getResource('github://org/repo/config.json');\\n\\n// Step 2: Use config to query database\\nconst queryResults = await getResource(`postgres://database/table?query=${config.queryParams}`);\\n\\n// Step 3: Process results and store in memory\\nawait setResource('memory://session/processed_data', processData(queryResults));\\n```\\n\\n#### 2. Aggregation Pattern\\nCombine data from multiple resources to create a comprehensive context:\\n\\n```\\n// Collect data from multiple sources\\nconst codebase = await getResource('github://org/repo/src');\\nconst documentation = await getResource('file:///local/docs');\\nconst issueTracking = await getResource('https://issues.example.com/api/project');\\n\\n// Combine into unified context\\nconst projectContext = {\\n code: codebase,\\n docs: documentation,\\n issues: issueTracking\\n};\\n```\\n\\n#### 3. Template Enrichment Pattern\\nUse resources to populate template variables dynamically:\\n\\n```\\n// Retrieve template\\nconst template = await getResource('prompts://templates/analysis');\\n\\n// Gather contextual data\\nconst repoStats = await getResource('github://org/repo/stats');\\nconst performanceData = await getResource('postgres://metrics/performance');\\n\\n// Apply template with resource data\\nconst enrichedPrompt = applyTemplate(template, {\\n project_metrics: repoStats,\\n performance_insights: performanceData\\n});\\n```\\n\\n## Implementation Guidelines for {{integration_task}}\\n\\n### Step 1: Resource Discovery\\nFirst, use the resources/list method to discover what data sources are available:\\n\\n```javascript\\n// Example resources/list implementation\\nasync function discoverResources() {\\n const resources = await callMCP({\\n method: 'resources/list',\\n params: {}\\n });\\n \\n console.log('Available resources:', resources);\\n return resources;\\n}\\n```\\n\\n### Step 2: Resource Access Patterns\\nImplement standardized patterns for accessing different resource types:\\n\\n```javascript\\n// Example resource access function\\nasync function getResource(uri) {\\n const serverType = getServerTypeFromUri(uri);\\n \\n const response = await callMCP({\\n server: serverType,\\n method: 'resources/get',\\n params: { uri }\\n });\\n \\n return response.data;\\n}\\n```\\n\\n### Step 3: Resource Integration\\nCombine resources using the appropriate integration pattern for your use case:\\n\\n{{integration_code}}\\n\\n### Step 4: Error Handling and Fallbacks\\nImplement robust error handling for cases where resources may be unavailable:\\n\\n```javascript\\ntry {\\n const resource = await getResource('github://org/repo/file.json');\\n // Process resource\\n} catch (error) {\\n console.error('Error accessing resource:', error);\\n // Use fallback resource or strategy\\n const fallbackResource = await getResource('file:///local/fallback.json');\\n}\\n```\\n\\n## Best Practices for Resource Integration\\n\\n1. **Cache appropriately**: Some resources may be expensive to fetch repeatedly\\n2. **Handle failures gracefully**: Use fallbacks when resources are unavailable\\n3. **Consider resource formats**: Different servers may return different data structures\\n4. **Manage dependencies**: Be mindful of resource dependencies and potential circular references\\n5. **Document resource usage**: Make resource URIs and usage patterns explicit\\n6. **Security awareness**: Consider access control implications when sharing resources\\n{{additional_practices}}\\n\\n## Implementation Examples for Common Scenarios\\n\\n### Example 1: Project Analysis Dashboard\\nCombine code repository statistics, issue tracking, and documentation:\\n\\n```javascript\\nasync function buildProjectDashboard() {\\n // Discover available resources\\n const resources = await discoverResources();\\n \\n // Check if required resources are available\\n const hasGitHub = resources.some(r => r.startsWith('github://'));\\n const hasIssues = resources.some(r => r.startsWith('https://issues.'));\\n \\n // Gather data from available sources\\n const repoData = hasGitHub ? \\n await getResource('github://org/project/stats') : \\n { error: 'GitHub data unavailable' };\\n \\n const issueData = hasIssues ?\\n await getResource('https://issues.example.com/api/project/stats') :\\n { error: 'Issue tracker unavailable' };\\n \\n // Combine into unified dashboard data\\n return {\\n code_metrics: repoData,\\n issue_metrics: issueData,\\n timestamp: new Date().toISOString()\\n };\\n}\\n```\\n\\n### Example 2: Dynamic Document Generation\\nGenerate documentation by combining templates with real-time data:\\n\\n```javascript\\nasync function generateDocumentation() {\\n // Get document template\\n const template = await getResource('prompts://templates/documentation');\\n \\n // Gather data from multiple sources\\n const apiSchema = await getResource('file:///api/schema.json');\\n const usageStats = await getResource('postgres://analytics/api_usage');\\n const exampleCode = await getResource('github://org/examples/api');\\n \\n // Generate documentation\\n return applyTemplate(template, {\\n schema: apiSchema,\\n usage: usageStats,\\n examples: exampleCode\\n });\\n}\\n```\\n\\n### Example 3: {{custom_example_name}}\\n{{custom_example_description}}\\n\\n```javascript\\n{{custom_example_code}}\\n```\\n\\n## Resources/List Method in Action\\n\\nThe resources/list method serves multiple important functions:\\n\\n1. **Discovery and Exploration**: Clients can discover what contextual resources are available\\n2. **Workflow Orchestration**: Automated workflows can determine which resources to use\\n3. **Enhanced UI/UX**: User interfaces can show available resources for selection\\n4. **Integration with External Services**: Bridge between clients and external data sources\\n\\nExample implementation of a resource explorer using resources/list:\\n\\n```javascript\\nasync function exploreResources(prefix = '') {\\n const resources = await callMCP({\\n method: 'resources/list',\\n params: { prefix }\\n });\\n \\n // Group resources by type\\n const resourcesByType = resources.reduce((groups, uri) => {\\n const type = uri.split('://')[0];\\n if (!groups[type]) groups[type] = [];\\n groups[type].push(uri);\\n return groups;\\n }, {});\\n \\n // Display available resources by type\\n for (const [type, uris] of Object.entries(resourcesByType)) {\\n console.log(`${type} resources (${uris.length}):`);\\n uris.forEach(uri => console.log(` - ${uri}`));\\n }\\n \\n return resourcesByType;\\n}\\n```\\n\\n## Conclusion\\n\\nEffective integration of resources across MCP servers is a powerful pattern that enables complex workflows, rich contextual awareness, and dynamic content generation. By understanding the resources/list method and implementing appropriate integration patterns, you can leverage the full potential of the MCP ecosystem for {{integration_task}}.\\n\\nWhat specific aspect of MCP resource integration would you like to explore further?\\\",\\n \\\"isTemplate\\\": true,\\n \\\"variables\\\": [\\n \\\"integration_task\\\",\\n \\\"custom_server\\\",\\n \\\"custom_prefix\\\",\\n \\\"custom_example\\\",\\n \\\"custom_description\\\",\\n \\\"integration_code\\\",\\n \\\"additional_practices\\\",\\n \\\"custom_example_name\\\",\\n \\\"custom_example_description\\\",\\n \\\"custom_example_code\\\"\\n ],\\n \\\"tags\\\": [\\n \\\"mcp\\\",\\n \\\"resources\\\",\\n \\\"integration\\\",\\n \\\"advanced\\\",\\n \\\"multi-server\\\",\\n \\\"template\\\"\\n ],\\n \\\"createdAt\\\": \\\"2025-03-15T16:00:00.000Z\\\",\\n \\\"updatedAt\\\": \\\"2025-03-15T16:00:00.000Z\\\",\\n \\\"version\\\": 1,\\n \\\"metadata\\\": {\\n \\\"recommended_servers\\\": [\\n \\\"github\\\",\\n \\\"filesystem\\\",\\n \\\"postgres\\\",\\n \\\"memory\\\",\\n \\\"prompts\\\"\\n ],\\n \\\"example_variables\\\": {\\n \\\"integration_task\\\": \\\"building a comprehensive project analysis tool\\\",\\n \\\"custom_server\\\": \\\"TimeSeries\\\",\\n \\\"custom_prefix\\\": \\\"timeseries://\\\",\\n \\\"custom_example\\\": \\\"timeseries://metrics/cpu-usage/7d\\\",\\n \\\"custom_description\\\": \\\"Historical time-series data for metrics and monitoring\\\",\\n \\\"integration_code\\\": \\\"async function integrateProjectAnalysis() {\\\\n // Get repository information\\\\n const repoInfo = await getResource('github://org/repo/info');\\\\n \\\\n // Fetch relevant code files based on repo structure\\\\n const codeFiles = await Promise.all(\\\\n repoInfo.main_modules.map(module => \\\\n getResource(`github://org/repo/src/${module}`)\\\\n )\\\\n );\\\\n \\\\n // Get database schema information\\\\n const dbSchema = await getResource('postgres://database/information_schema');\\\\n \\\\n // Combine everything into a unified context\\\\n const projectContext = {\\\\n repository: repoInfo,\\\\n code_modules: codeFiles,\\\\n database_structure: dbSchema,\\\\n analysis_timestamp: new Date().toISOString()\\\\n };\\\\n \\\\n // Store the combined context in memory for future reference\\\\n await setResource('memory://session/project_context', projectContext);\\\\n \\\\n return projectContext;\\\\n}\\\",\\n \\\"additional_practices\\\": \\\"7. **Version awareness**: Consider resource version compatibility\\\\n8. **Performance tracking**: Monitor resource access patterns and optimize frequent operations\\\\n9. **Scope limitation**: Only access resources directly relevant to the current task\\\\n10. **Progressive enhancement**: Design systems that work with minimal resources but enhance capabilities when more are available\\\",\\n \\\"custom_example_name\\\": \\\"Cross-Server Data Validation\\\",\\n \\\"custom_example_description\\\": \\\"Validate data consistency across different storage systems by comparing repositories, databases, and local files:\\\",\\n \\\"custom_example_code\\\": \\\"async function validateDataConsistency() {\\\\n // Get configuration schema from repository\\\\n const configSchema = await getResource('github://org/repo/schema/config.json');\\\\n \\\\n // Get actual configurations from database\\\\n const dbConfigs = await getResource('postgres://app/configurations');\\\\n \\\\n // Get local configuration files\\\\n const localConfigs = await getResource('file:///app/config/');\\\\n \\\\n // Compare configurations across systems\\\\n const validationResults = {\\\\n schema_valid: validateAgainstSchema(dbConfigs, configSchema),\\\\n db_local_match: compareConfigurations(dbConfigs, localConfigs),\\\\n mismatches: findMismatches(dbConfigs, localConfigs, configSchema)\\\\n };\\\\n \\\\n // Store validation results in memory\\\\n await setResource('memory://validation/config_results', validationResults);\\\\n \\\\n return validationResults;\\\\n}" }