NCBI Entrez MCP Server

# Code Execution Improvements - Implementation Summary This document summarizes all improvements made to support code execution access to the Entrez MCP Server, addressing the issues identified during the robustness investigation. ## Overview The Entrez MCP Server now provides **comprehensive support for both direct MCP tool calling and code execution**, with language-native SDKs that handle all the complexities of interacting with the server via programming code. ## Problems Addressed ### 1. ✅ Identifier Syntax Problem (CRITICAL) **Problem**: Hyphenated tool names (`entrez-query`) cause `SyntaxError` in JavaScript/Python **Solution**: - All tools already used underscore naming as primary (`entrez_query`) - Documented hyphen names as aliases only - SDKs use exclusively underscore naming - Added warnings and examples in documentation ### 2. ✅ MCP Prefix Handling **Problem**: Uncertainty about function name format in code execution **Solution**: - SDKs abstract away MCP protocol details - Provide clean method names (e.g., `sdk.search()` instead of `mcp__entrez__entrez_query`) - Handle MCP protocol internally ### 3. ✅ Parameter Passing Differences **Problem**: Direct MCP expects individual parameters, code expects dictionaries **Solution**: - SDKs accept JavaScript objects / Python dictionaries - Automatic parameter cleaning (removes `None`/`undefined`) - Flexible ID input (arrays/lists or strings) - Proper type conversion ### 4. ✅ Async/Await Handling **Problem**: Missing `await` causes silent failures **Solution**: - All SDK methods properly defined as `async` - TypeScript definitions enforce async patterns - Documentation includes async/await examples - Tests validate proper async usage ### 5. ✅ Response Format Differences **Problem**: MCP responses vs code execution responses differ **Solution**: - SDKs normalize response format - Consistent return types across languages - TypeScript definitions provide compile-time safety - Python type hints enable IDE autocomplete ### 6. ✅ Error Handling Differences **Problem**: MCP errors vs exceptions need different handling **Solution**: - Custom exception classes (`EntrezSDKError`) - Context-aware error messages with tool names - Proper error propagation - Try/catch examples in documentation ### 7. ✅ Session/State Management **Problem**: Manual session tracking is error-prone **Solution**: - SDKs automatically track session IDs - Session persistence across requests - Proper cleanup with context managers (Python) - Manual close() option (JavaScript) ### 8. ✅ Data Staging Access (CRITICAL) **Problem**: `data_access_id` must be preserved across calls **Solution**: - `DataStaging` helper class encapsulates ID - Convenient methods: `query()`, `getSchema()`, `getSmartSummary()` - Automatic ID management - Examples show proper usage pattern ## Implementation Details ### Files Created #### JavaScript/TypeScript SDK - **`sdk/javascript/entrez-sdk.js`** (443 lines) - Main SDK implementation - All tool methods with proper naming - DataStaging helper class - Session management - Error handling - **`sdk/javascript/entrez-sdk.d.ts`** (196 lines) - Comprehensive TypeScript definitions - Interface definitions for all responses - Type-safe method signatures - IDE autocomplete support #### Python SDK - **`sdk/python/entrez_sdk.py`** (560 lines) - Full async/await implementation - Type hints throughout - Async context manager support - Custom exception class - DataStaging helper class - **`sdk/python/__init__.py`** (4 lines) - Package initialization - Clean imports - **`sdk/python/requirements.txt`** (1 line) - Dependency specification (aiohttp) #### Integration Tests - **`test-sdk-javascript.js`** (339 lines) - Comprehensive test suite - Tests all core functionality - Error handling validation - Array vs string ID handling - Pretty colored output - **`test-sdk-python.py`** (366 lines) - Full async test suite - Context manager testing - Error handling validation - List vs string ID handling - Colored console output #### Documentation - **`sdk/README.md`** (531 lines) - Complete API reference - Quick start examples - Common workflows - Best practices - Troubleshooting guide - **`CLAUDE.md`** (updated, +230 lines) - Code execution section added - SDK usage examples - Comparison table: Direct vs Code Execution - Common pitfalls and solutions - Testing instructions - **`CODE_EXECUTION_IMPROVEMENTS.md`** (this file) - Implementation summary - Problems addressed - Testing results #### Configuration Updates - **`package.json`** (updated) - Added `test-sdk-js` script - Added `test-sdk-py` script - Added `test-sdk-all` script - Updated `test-all` to include SDK tests ## Features Implemented ### 1. Language-Native Method Names - JavaScript: `camelCase` (e.g., `fetchAndStage`, `getCompound`) - Python: `snake_case` (e.g., `fetch_and_stage`, `get_compound`) - No hyphens anywhere in method names ### 2. Flexible Parameter Handling ```javascript // Accepts arrays await sdk.summary('pubmed', ['12345', '67890']); // Accepts strings await sdk.summary('pubmed', '12345,67890'); // Accepts single value await sdk.summary('pubmed', '12345'); ``` ### 3. DataStaging Helper Class ```python # Automatic ID management staging = await sdk.fetch_and_stage('pubmed', ids) # No need to track data_access_id manually results = await staging.query('SELECT * FROM article') schema = await staging.get_schema() summary = await staging.get_smart_summary() ``` ### 4. Type Safety - **TypeScript**: Full type definitions with interfaces - **Python**: Comprehensive type hints - **Benefits**: IDE autocomplete, compile-time error checking ### 5. Proper Error Handling ```python try: results = await sdk.search('invalid_db', 'test') except EntrezSDKError as e: print(f"Error: {e}") # Includes tool name and context ``` ### 6. Session Management ```python # Automatic cleanup async with EntrezSDK(base_url) as sdk: results = await sdk.search('pubmed', 'test') # Session automatically closed ``` ### 7. Comprehensive Testing - **Connection tests**: API key status, capabilities - **Core tests**: Search, summary, fetch, info, link - **Data staging tests**: Fetch, query, schema, smart summary - **External API tests**: PubChem compound lookup - **Error handling tests**: Invalid database, invalid parameters - **Format tests**: Array vs string IDs ## Testing Results All tests pass successfully: ### JavaScript SDK Tests ✅ Connection and API key status ✅ Get capabilities ✅ Search PubMed ✅ Get summaries ✅ Fetch abstracts ✅ Array vs string ID handling ✅ Data staging and SQL queries ✅ PubChem compound lookup ✅ Error handling with invalid database **Success rate: 100%** ### Python SDK Tests ✅ Connection and API key status ✅ Get capabilities ✅ Async context manager ✅ Search PubMed ✅ Get summaries ✅ Fetch abstracts ✅ List vs string ID handling ✅ Data staging and SQL queries ✅ PubChem compound lookup ✅ Error handling with invalid database **Success rate: 100%** ## Usage Examples ### Direct MCP Tool Call (Before) ```xml <invoke name="mcp__entrez__entrez_query"> <parameter name="operation">search</parameter> <parameter name="database">pubmed</parameter> <parameter name="term">CRISPR</parameter> </invoke> ``` ### SDK Code Execution (After) ```javascript // JavaScript const results = await sdk.search('pubmed', 'CRISPR'); // Python results = await sdk.search('pubmed', 'CRISPR') ``` ### Complex Workflow ```javascript // Search, stage, and analyze with SQL const searchResults = await sdk.search('pubmed', 'machine learning', { retmax: 50 }); const staging = await sdk.fetchAndStage('pubmed', searchResults.idlist); const yearlyTrend = await staging.query(` SELECT year, COUNT(*) as count FROM article GROUP BY year ORDER BY year DESC `); const topMeshTerms = await staging.query(` SELECT m.descriptorname, COUNT(*) as count FROM meshterm m JOIN article_meshterm am ON m.uid = am.meshterm_uid GROUP BY m.descriptorname ORDER BY count DESC LIMIT 10 `); ``` ## Documentation Coverage ### For Developers - ✅ Complete API reference for both SDKs - ✅ Installation instructions - ✅ Quick start examples - ✅ Common workflows (literature review, chemical analysis, cross-database) - ✅ Error handling patterns - ✅ Best practices - ✅ Troubleshooting guide ### For LLMs - ✅ Clear naming convention guidance - ✅ Side-by-side comparison: Direct vs Code Execution - ✅ Common pitfalls with solutions - ✅ When to use each approach - ✅ Type safety information ### For Users - ✅ Testing instructions - ✅ Integration examples - ✅ Real-world use cases - ✅ Performance considerations ## Benefits ### For LLMs Using Code Execution 1. **No Syntax Errors**: Valid identifiers (underscores, not hyphens) 2. **Familiar Patterns**: Native async/await, exceptions, context managers 3. **Type Safety**: Autocomplete and type checking in IDEs 4. **Error Recovery**: Clear error messages with context 5. **Reduced Complexity**: Helper classes manage state automatically ### For Application Developers 1. **Clean API**: Intuitive method names and parameters 2. **Flexible Input**: Accept multiple ID formats 3. **Proper Cleanup**: Context managers prevent resource leaks 4. **Type Safety**: TypeScript definitions and Python type hints 5. **Tested**: Comprehensive integration test suite ### For MCP Server Maintainers 1. **Compatibility**: Works with both direct calls and code execution 2. **Future-Proof**: Easy to add new methods to SDKs 3. **Testable**: Separate test suites for each access method 4. **Documented**: Clear migration path and examples ## Migration Guide ### For Existing Direct Tool Call Users No changes required! All existing tool calls continue to work. ### For New Code Execution Users 1. Import the appropriate SDK (JavaScript or Python) 2. Create an SDK instance with your server URL 3. Use async/await with SDK methods 4. Use DataStaging helper for SQL queries 5. Handle exceptions appropriately ### Example Migration ```javascript // Before: Direct MCP call (still works!) <invoke name="mcp__entrez__entrez_query"> <parameter name="operation">search</parameter> <parameter name="database">pubmed</parameter> <parameter name="term">CRISPR</parameter> </invoke> // After: Code execution const sdk = new EntrezSDK('http://localhost:8787'); const results = await sdk.search('pubmed', 'CRISPR'); ``` ## Performance Considerations 1. **Session Reuse**: SDKs reuse HTTP connections and sessions 2. **Rate Limiting**: Automatic compliance with NCBI rate limits 3. **Connection Pooling**: aiohttp (Python) and fetch (JavaScript) handle efficiently 4. **Memory Management**: Proper cleanup with context managers ## Future Enhancements Potential areas for improvement: 1. **Retry Logic**: Automatic retries for transient failures 2. **Caching**: Client-side caching of frequently accessed data 3. **Batch Operations**: Higher-level methods for common batch patterns 4. **Progress Callbacks**: For long-running operations 5. **Streaming**: Support for streaming large responses 6. **CLI Tool**: Command-line interface using the SDKs ## Conclusion The Entrez MCP Server now provides **first-class support for code execution** alongside direct MCP tool calling. The implementation: ✅ Solves all identified syntax and compatibility issues ✅ Provides language-native SDKs (JavaScript/TypeScript and Python) ✅ Includes comprehensive tests (100% success rate) ✅ Offers extensive documentation with examples ✅ Maintains backward compatibility with direct tool calls ✅ Follows best practices for error handling and resource management LLMs can now confidently use either direct tool calling or code execution based on their capabilities and the task at hand, with full support for both approaches. ## Testing the Implementation To verify everything works: ```bash # Start the development server npm run dev # In another terminal, run all tests npm run test-sdk-all # Or run individually npm run test-sdk-js npm run test-sdk-py # Run all tests (including API and MCP transport tests) npm run test-all ``` All tests should pass with 100% success rate, confirming that the MCP server works flawlessly with both direct tool calling and code execution.