# NeoCoder Integration Points Analysis
## Core Integration Points
NeoCoder provides several key integration points that enable its extensibility and connectivity with other systems:
## 1. Neo4j Integration
### Connection Management
NeoCoder integrates with Neo4j through the asynchronous Neo4j driver:
```python
from neo4j import AsyncDriver, AsyncSession, AsyncTransaction
```
The connection is configured via:
- Environment variables (`NEO4J_URL`, `NEO4J_USERNAME`, `NEO4J_PASSWORD`, `NEO4J_DATABASE`)
- Configuration JSON file
- Command-line arguments
### Query Execution
The system provides several abstraction layers for Neo4j interaction:
1. **Direct Query Execution**
```python
async def _read_query(self, tx: AsyncTransaction, query: str, params: dict) -> str:
"""Execute a read query and return results as JSON string."""
raw_results = await tx.run(query, params)
eager_results = await raw_results.to_eager_result()
return json.dumps([r.data() for r in eager_results.records], default=str)
```
2. **Safe Query Execution**
```python
async def _safe_read_query(self, session, query, params=None):
"""Execute a read query safely, handling all errors internally."""
# Implementation handles transactions and error recovery
```
3. **Schema Management**
```python
async def initialize_schema(self):
"""Initialize the Neo4j schema for this incarnation."""
# Execute schema creation queries
```
## 2. MCP Server Integration
NeoCoder implements the Model Context Protocol (MCP) server interface to communicate with AI assistants:
### Tool Registration
Tools are registered with the MCP server:
```python
async def register_tools(self, server):
"""Register incarnation-specific tools with the server."""
# Get all tool methods from this incarnation
tool_methods = self.list_tool_methods()
# Register each tool directly with the MCP server
for method_name in tool_methods:
# Get the method
method = getattr(self, method_name)
# Register directly with MCP
server.mcp.add_tool(method)
```
### Tool Execution
Tools follow a consistent pattern for integration with the MCP system:
```python
async def some_tool(
self,
param1: str = Field(..., description="Description of parameter 1"),
param2: Optional[int] = Field(None, description="Description of parameter 2")
) -> List[types.TextContent]:
"""Tool description for AI assistant."""
# Implementation
return [types.TextContent(type="text", text="Result")]
```
## 3. File System Integration
NeoCoder integrates with the file system for code and project management:
### Code Reading
```python
# Example from a potential implementation
async def analyze_file(self, file_path: str, ...):
with open(file_path, 'r') as f:
content = f.read()
# Process content
```
### Path Handling
```python
import os
# Path resolution and manipulation
dir_path = os.path.dirname(file_path)
```
## 4. Incarnation System Integration
The incarnation system provides a plugin architecture:
### Dynamic Loading
```python
# Dynamic discovery of incarnations
for filename in os.listdir(incarnations_dir):
if filename.endswith('_incarnation.py'):
# Extract incarnation type and load module
```
### Registration
```python
# Registration with incarnation registry
registry.register_incarnation(incarnation_cls, incarnation_type)
```
### Switching
```python
async def switch_incarnation(self, incarnation_type: str) -> List[types.TextContent]:
"""Switch to a different incarnation."""
# Implementation
```
## 5. External Tool Integration
The system integrates with external tools, particularly in the Code Analysis incarnation:
### AST/ASG Tools
```python
# Example of how code analysis tools might be integrated
async def _process_ast_data(self, ast_data: Dict[str, Any]) -> Dict[str, Any]:
"""Process AST data from external tool."""
# Process and transform data
```
## Extensibility Points
NeoCoder provides several extensibility points for adding new functionality:
## 1. New Incarnations
Creating new incarnations is the primary extension mechanism:
```python
class YourIncarnationNameIncarnation(BaseIncarnation):
"""
Your detailed incarnation description here
"""
# Define the incarnation type
incarnation_type = IncarnationType.YOUR_INCARNATION_TYPE
# Metadata for display in the UI
description = "Your incarnation short description"
version = "0.1.0"
# Initialize schema and add tools here
async def initialize_schema(self):
"""Initialize the schema for your incarnation."""
# Implementation...
# Add tool methods
async def your_tool_name(self, param1: str, param2: Optional[int] = None) -> List[types.TextContent]:
"""Tool description."""
# Implementation...
```
## 2. New Tools
Adding new tools to existing incarnations:
```python
# Add to an existing incarnation class
async def new_tool(
self,
param1: str = Field(..., description="Description of parameter 1"),
param2: Optional[int] = Field(None, description="Description of parameter 2")
) -> List[types.TextContent]:
"""Tool description."""
# Implementation
return [types.TextContent(type="text", text="Result")]
```
## 3. New Templates
Adding new workflow templates:
```cypher
// Create new template
MERGE (t:ActionTemplate {keyword: 'YOUR_KEYWORD', version: '1.0'})
ON CREATE SET t.isCurrent = true
ON MATCH SET t.isCurrent = true
SET t.description = 'Description of your template'
SET t.complexity = 'MEDIUM'
SET t.estimatedEffort = 30
SET t.steps = '
1. First step...
2. Second step...
'
// Make sure this is the only current version
MATCH (old:ActionTemplate {keyword: 'YOUR_KEYWORD', isCurrent: true})
WITH old.version <> '1.0'
SET old.isCurrent = false
```
## 4. Schema Extensions
Extending the Neo4j schema:
```python
# Add to an incarnation's schema_queries list
schema_queries = [
"CREATE CONSTRAINT your_constraint IF NOT EXISTS FOR (n:YourNode) REQUIRE n.id IS UNIQUE",
"CREATE INDEX your_index IF NOT EXISTS FOR (n:YourNode) ON (n.property)",
]
```
## 5. Tool Proposal System
The Tool Proposal system allows for suggesting new tools:
```python
async def propose_tool(
self,
name: str,
description: str,
parameters: List[Dict[str, Any]],
rationale: str,
example_usage: Optional[str] = None,
implementation_notes: Optional[str] = None
) -> List[types.TextContent]:
"""Propose a new tool for the NeoCoder system."""
# Implementation
```
## Integration with AI Assistants
NeoCoder is designed to integrate with AI assistants like Claude:
### System Prompt Integration
The recommended system prompt configures the AI assistant to use NeoCoder:
```
**System Instruction:** You are an AI coding assistant integrated with a Neo4j knowledge graph that defines our standard coding procedures and tracks project changes.
**Your Core Interaction Loop:**
1. **Identify Task & Keyword:** Determine the coding action required (e.g., fix a bug -> `FIX`).
...
```
### Workflow Integration
AI assistants interact with NeoCoder through:
1. **Query Formulation** - Creating Cypher queries to find templates and guides
2. **Tool Execution** - Using MCP tools to interact with Neo4j and file system
3. **Workflow Following** - Executing steps from retrieved templates
4. **Result Logging** - Recording successful workflow executions
### Example Interaction Flow
1. AI identifies that a bug fix is needed
2. AI queries for the FIX template:
```cypher
MATCH (t:ActionTemplate {keyword: 'FIX', isCurrent: true})
RETURN t.steps
```
3. AI follows the steps in the template
4. AI verifies the fix with tests
5. AI logs the successful workflow execution:
```python
log_workflow_execution(
project_id="project-123",
action_keyword="FIX",
summary="Fixed null pointer exception in user authentication",
files_changed=["src/auth.py"]
)
```
## External API Integration Potential
NeoCoder has potential for integration with other systems:
### Version Control Systems
Integration with Git could enable:
- Automatic commit generation
- Branch management
- Pull request creation
### CI/CD Systems
Integration with CI/CD pipelines could enable:
- Automatic testing
- Deployment verification
- Pipeline management
### Development Environments
Integration with IDEs could enable:
- In-editor guidance
- Code analysis visualizations
- Workflow assistance
### Project Management Tools
Integration with project management systems could enable:
- Issue tracking
- Task management
- Progress reporting
## Conclusion
NeoCoder provides a robust set of integration points that enable:
1. **Extensibility** - Adding new incarnations, tools, and templates
2. **Connectivity** - Integrating with Neo4j, file systems, and AI assistants
3. **Adaptability** - Supporting different domains through specialized incarnations
4. **Workflow Integration** - Guiding AI assistants through standardized workflows
The architecture is designed for integration, with clean separation of concerns and well-defined extension points. The plugin-based incarnation system allows for specialized implementations while maintaining a consistent core architecture.
