WIP

Author: shahar4499

.gitignore

@@ -152,4 +152,30 @@ Desktop.ini
 
 # Repomix output
 repomix-output.txt
-repomix-output.xml
+repomix-output.xml
+
+# Cursor
+.cursor/
+
+# Added by Claude Task Master
+# Logs
+logs
+npm-debug.log*
+yarn-debug.log*
+yarn-error.log*
+dev-debug.log
+# Dependency directories
+node_modules/
+# Environment variables
+# Editor directories and files
+.idea
+.vscode
+*.suo
+*.ntvs*
+*.njsproj
+*.sln
+*.sw?
+# OS specific
+# Task files
+tasks.json
+tasks/

.taskmasterconfig

@@ -0,0 +1,32 @@
+{
+  "models": {
+    "main": {
+      "provider": "anthropic",
+      "modelId": "claude-3-7-sonnet-20250219",
+      "maxTokens": 120000,
+      "temperature": 0.2
+    },
+    "research": {
+      "provider": "perplexity",
+      "modelId": "sonar-pro",
+      "maxTokens": 8700,
+      "temperature": 0.1
+    },
+    "fallback": {
+      "provider": "anthropic",
+      "modelId": "claude-3-5-sonnet-20240620",
+      "maxTokens": 8192,
+      "temperature": 0.1
+    }
+  },
+  "global": {
+    "logLevel": "info",
+    "debug": false,
+    "defaultSubtasks": 5,
+    "defaultPriority": "medium",
+    "projectName": "Taskmaster",
+    "ollamaBaseUrl": "http://localhost:11434/api",
+    "azureOpenaiBaseUrl": "https://your-endpoint.openai.azure.com/",
+    "userId": "1234567890"
+  }
+}

README.md

@@ -1 +1,152 @@
-# tadata-python-sdk
+# Tadata Python SDK
+
+The Tadata Python SDK provides an easy-to-use interface for deploying Model Context Protocol (MCP) servers from OpenAPI specifications.
+
+## Installation
+
+```bash
+# Install with pip
+pip install tadata-sdk
+
+# Or with uv (recommended)
+uv pip install tadata-sdk
+```
+
+## Quickstart
+
+Deploy a Model Context Protocol (MCP) server with your OpenAPI specification:
+
+```python
+from tadata_sdk import deploy, OpenAPISpec
+
+# Deploy from a dictionary
+result = deploy(
+    openapi_spec={
+        "openapi": "3.0.0",
+        "info": {"title": "My API", "version": "1.0.0"},
+        "paths": {"/hello": {"get": {"responses": {"200": {"description": "OK"}}}}},
+    },
+    api_key="your-tadata-api-key",
+    name="My MCP Deployment",  # Optional
+    base_url="https://api.myservice.com",  # Optional
+)
+
+print(f"Deployed MCP server: {result.id}")
+print(f"Created at: {result.created_at}")
+```
+
+## OpenAPI Specification Sources
+
+The SDK supports multiple ways to provide your OpenAPI specification:
+
+```python
+# From a file (JSON or YAML)
+result = deploy(
+    openapi_spec_path="./openapi.json",  # or .yaml
+    api_key="your-tadata-api-key",
+)
+
+# From a URL
+result = deploy(
+    openapi_spec_url="https://example.com/openapi.json",  # or .yaml
+    api_key="your-tadata-api-key",
+)
+
+# From a dictionary
+result = deploy(
+    openapi_spec={
+        "openapi": "3.0.0",
+        "info": {"title": "My API", "version": "1.0.0"},
+        "paths": {"/hello": {"get": {"responses": {"200": {"description": "OK"}}}}},
+    },
+    api_key="your-tadata-api-key",
+)
+
+# From an OpenAPISpec object
+spec = OpenAPISpec.from_file("./openapi.json")
+result = deploy(
+    openapi_spec=spec,
+    api_key="your-tadata-api-key",
+)
+```
+
+## Authentication Handling
+
+You can configure how authentication is handled between the MCP server and your API:
+
+```python
+result = deploy(
+    openapi_spec_path="./openapi.json",
+    api_key="your-tadata-api-key",
+    auth_config={
+        "pass_headers": ["authorization", "x-api-key"],  # Headers to pass through
+        "pass_query_params": ["api_key"],  # Query parameters to pass through
+        "pass_json_body_params": [],  # JSON body parameters to extract
+        "pass_form_data_params": [],  # Form data parameters to extract
+    }
+)
+```
+
+## Error Handling
+
+The SDK provides specific error classes for better error handling:
+
+```python
+from tadata_sdk import deploy, SpecInvalidError, AuthError, ApiError, NetworkError
+
+try:
+    result = deploy(
+        openapi_spec_path="./openapi.json",
+        api_key="your-tadata-api-key",
+    )
+    print(f"Deployed MCP server: {result.id}")
+except SpecInvalidError as e:
+    print(f"Invalid OpenAPI spec: {e}")
+    print(f"Details: {e.details}")
+except AuthError as e:
+    print(f"Authentication failed: {e}")
+except ApiError as e:
+    print(f"API error: {e}, Status: {e.status_code}")
+except NetworkError as e:
+    print(f"Network error: {e}")
+except Exception as e:
+    print(f"Unexpected error: {e}")
+```
+
+## Advanced Usage
+
+### Custom Logging
+
+You can provide your own logger implementation:
+
+```python
+import logging
+from tadata_sdk import deploy
+
+# Configure a custom logger
+logging.basicConfig(level=logging.DEBUG)
+logger = logging.getLogger("tadata-example")
+
+# Use the custom logger
+result = deploy(
+    openapi_spec_path="./openapi.json",
+    api_key="your-tadata-api-key",
+    logger=logger,
+)
+```
+
+### Development Environment
+
+For testing purposes, you can use the development environment:
+
+```python
+result = deploy(
+    openapi_spec_path="./openapi.json",
+    api_key="your-tadata-api-key",
+    dev=True,  # Use development environment
+)
+```
+
+## License
+
+MIT

examples/deploy_mcp.py

@@ -0,0 +1,88 @@
+#!/usr/bin/env python3
+import os
+import sys
+
+# Add the project root to the Python path if running from examples directory
+sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..")))
+
+import logging
+from typing import Dict, Any
+
+from tadata_sdk import deploy
+
+
+# Sample simple OpenAPI spec
+SAMPLE_SPEC: Dict[str, Any] = {
+    "openapi": "3.0.0",
+    "info": {
+        "title": "Sample API",
+        "version": "1.0.0",
+        "description": "A sample API specification for Tadata SDK example",
+    },
+    "paths": {
+        "/hello": {
+            "get": {
+                "summary": "Say hello",
+                "operationId": "sayHello",
+                "responses": {
+                    "200": {
+                        "description": "A hello message",
+                        "content": {
+                            "application/json": {
+                                "schema": {
+                                    "type": "object",
+                                    "properties": {
+                                        "message": {"type": "string"},
+                                    },
+                                }
+                            }
+                        },
+                    }
+                },
+            }
+        }
+    },
+    "servers": [{"url": "https://example.com/api"}],
+}
+
+
+def main() -> None:
+    """Run the example."""
+    # Configure logging
+    logging.basicConfig(level=logging.INFO)
+
+    # Get API key from environment variable
+    api_key = os.environ.get("TADATA_API_KEY")
+    if not api_key:
+        print("Error: TADATA_API_KEY environment variable is required")
+        sys.exit(1)
+
+    print("Deploying MCP server from OpenAPI spec...")
+
+    # Method 1: Using a dictionary directly
+    result = deploy(
+        openapi_spec=SAMPLE_SPEC,
+        api_key=api_key,
+        # Optional: specify a different base URL for the API
+        base_url="https://my-actual-api.example.com/v1",
+        name="Sample API Deployment",
+    )
+
+    print("Successfully deployed MCP server!")
+    print(f"  ID: {result.id}")
+    print(f"  Created at: {result.created_at}")
+    print(f"  Updated: {result.updated}")
+
+    # Method 2: Using an OpenAPISpec object
+    # spec = OpenAPISpec.from_dict(SAMPLE_SPEC)
+    # result = deploy(openapi_spec=spec, api_key=api_key)
+
+    # Method 3: Loading from a file
+    # result = deploy(openapi_spec_path="./openapi.json", api_key=api_key)
+
+    # Method 4: Loading from a URL
+    # result = deploy(openapi_spec_url="https://example.com/openapi.json", api_key=api_key)
+
+
+if __name__ == "__main__":
+    main()