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dhis2_get_composition_examples

Learn to integrate this DHIS2 MCP server with other MCP servers through practical examples that demonstrate cross-server functionality.

Instructions

Get examples of how to integrate this DHIS2 MCP server with other MCP servers

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • Handler for dhis2_get_composition_examples tool. Calls generateIntegrationExamples() from MultiServerComposition instance and returns the generated markdown content.
    case 'dhis2_get_composition_examples':
      const examples = multiServerComposition.generateIntegrationExamples();
      
      auditLogger.log({
        toolName: name,
        parameters: {},
        outcome: 'success',
        dhis2Instance: dhis2Client?.baseURL,
        userId: currentUser?.username,
        executionTime: Date.now() - startTime
      });
      
      return {
        content: [{
          type: 'text',
          text: examples
        }]
      };
  • Core helper function that generates comprehensive Markdown documentation including compatible server integrations, workflow examples with Mermaid diagrams, JSON workflow templates, and integration benefits for multi-server compositions.
      generateIntegrationExamples(): string {
        return `# DHIS2 MCP Server - Multi-Server Integration Examples
    
    ## 🔗 Compatible Server Integrations
    
    ${this.compatibleServers.size > 0 ? 
      Array.from(this.compatibleServers.values()).map(server => 
        `### ${server.name}
    **Capabilities**: ${server.capabilities.map(cap => cap.domain).join(', ')}
    **Version**: ${server.version}
    `).join('\n') : 'No compatible servers registered yet.'}
    
    ## 🚀 Workflow Examples
    
    ### 1. Data Quality Monitoring
    \`\`\`mermaid
    graph LR
        A[DHIS2: Run Validation] --> B[GitHub: Create Issue]
        B --> C[Slack: Notify Team]
        C --> D[Database: Log Issue]
    \`\`\`
    
    ### 2. Development Pipeline
    \`\`\`mermaid
    graph LR
        A[DHIS2: Generate App] --> B[Git: Commit Changes]
        B --> C[GitHub: Create PR]
        C --> D[Slack: Request Review]
    \`\`\`
    
    ### 3. Data Export Pipeline
    \`\`\`mermaid
    graph LR
        A[DHIS2: Export Data] --> B[Database: Store Copy]
        B --> C[Email: Send Report]
        C --> D[Filesystem: Archive]
    \`\`\`
    
    ## 🛠️ Cross-Server Tool Examples
    
    ### Data Quality → Issue Tracking
    \`\`\`json
    {
      "workflow": "data-quality-monitoring",
      "steps": [
        {
          "server": "dhis2-mcp",
          "tool": "dhis2_run_validation",
          "parameters": { "orgUnit": "country-level" }
        },
        {
          "server": "github-mcp", 
          "tool": "create_issue",
          "parameters": {
            "title": "Data Quality Issues Found",
            "body": "{{previous.validationResults}}"
          }
        }
      ]
    }
    \`\`\`
    
    ### Development → Deployment
    \`\`\`json
    {
      "workflow": "app-deployment",
      "steps": [
        {
          "server": "dhis2-mcp",
          "tool": "dhis2_init_webapp", 
          "parameters": { "appName": "patient-tracker" }
        },
        {
          "server": "git-mcp",
          "tool": "commit_changes",
          "parameters": { "message": "Initial app scaffolding" }
        },
        {
          "server": "slack-mcp",
          "tool": "send_message", 
          "parameters": { "message": "New DHIS2 app created: {{step1.appName}}" }
        }
      ]
    }
    \`\`\`
    
    ## 📊 Integration Benefits
    
    1. **Automated Workflows**: Chain DHIS2 operations with external systems
    2. **Enhanced Monitoring**: Connect DHIS2 analytics to notification systems
    3. **Development Integration**: Seamless connection to development toolchains
    4. **Data Pipeline**: Build comprehensive data processing workflows
    5. **Quality Assurance**: Automated testing and validation across systems
    
    ## 🔧 Setup Instructions
    
    1. **Start DHIS2 MCP Server**: This server (already running)
    2. **Start Compatible Servers**: GitHub, Slack, Database, etc.
    3. **Configure Client**: Point MCP client to all servers
    4. **Define Workflows**: Create cross-server automation rules
    5. **Test Integration**: Verify data flows between servers
    
    ## 📝 Data Exchange Format
    
    All data exported from DHIS2 MCP follows this standard format:
    
    \`\`\`json
    {
      "sourceServer": "dhis2-mcp",
      "timestamp": "2024-01-01T00:00:00.000Z",
      "operationType": "export",
      "metadata": {
        "toolName": "dhis2_get_analytics", 
        "dhis2Instance": "https://play.dhis2.org",
        "dataType": "analytics"
      },
      "data": {
        "/* DHIS2 response data */"
      }
    }
    \`\`\`
    
    This standardized format ensures seamless integration with other MCP servers.`;
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden but only states what the tool does without behavioral details. It doesn't disclose if this is a read-only operation, what format the examples are in, potential rate limits, or any side effects, which is inadequate for a tool with zero annotation coverage.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, clear sentence that efficiently conveys the tool's purpose without unnecessary words. It is front-loaded and appropriately sized for its simple function.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (simple read operation) but lack of annotations and output schema, the description is insufficient. It doesn't explain what the examples include, their format, or how they are returned, leaving gaps in understanding the tool's behavior and output.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has 0 parameters with 100% schema description coverage, so no parameter documentation is needed. The description doesn't add parameter semantics, but this is acceptable given the lack of parameters, aligning with the baseline for 0 params.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Get examples') and resource ('how to integrate this DHIS2 MCP server with other MCP servers'), making the purpose understandable. It doesn't explicitly differentiate from sibling tools like 'dhis2_get_composition_recommendations' or 'dhis2_export_for_composition', but the focus on 'examples' provides some distinction.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives. The description lacks context about prerequisites, timing, or comparisons to sibling tools like 'dhis2_get_composition_recommendations', leaving the agent without usage direction.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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