A modular Model Context Protocol (MCP) server for code analysis tools, with a primary focus on ast-grep integration. This server provides a standardized interface for AI assistants and other clients to perform structural code queries and transformations.
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Structural Code Analysis: Find patterns in code using ast-grep's powerful pattern matching capabilities
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Code Transformations: Replace patterns in code with new implementations
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YAML Rule Support: Apply custom lint and transformation rules defined in YAML
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Project-Wide Scanning: Scan entire projects for patterns or rule violations
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Containerized Deployment: Easy deployment with Docker
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Modular Architecture: Designed for easy extension with additional code analysis tools
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Python 3.12.8
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ast-grep CLI tool
-
Docker (for containerized deployment)
Using pip
pip install code-analysis-mcp-server
From source
git clone https://github.com/yourusername/code-analysis-mcp-server.git
cd code-analysis-mcp-server
pip install -e .
Using Docker
docker pull yourusername/code-analysis-mcp-server
# or build locally
docker build -t code-analysis-mcp-server .
# Direct execution
code-analysis-server
# With Docker
docker run -p 8000:8000 -v /path/to/your/project:/project code-analysis-mcp-server
Create a docker-compose.yml file:
version: '3'
services:
code-analysis-mcp:
image: yourusername/code-analysis-mcp-server
ports:
- "8000:8000"
volumes:
- ${PROJECT_DIR:-./sample_project}:/project
environment:
- PROJECT_PATH=/project
restart: unless-stopped
Then run:
PROJECT_DIR=/path/to/your/project docker-compose up -d
Client Example
import asyncio
import json
from fastmcp import Client
from fastmcp.client.transports import SSETransport
async def main():
async with Client(transport=SSETransport("http://localhost:8000/sse")) as client:
# Set project path
project_result = await client.call_tool(
"ast_grep_set_project_path",
{
"project_path": "/project"
}
)
# Process the result correctly
content_item = project_result[0]
result_data = json.loads(content_item.text)
print("Project path result:", result_data)
# Find patterns in a file
find_result = await client.call_tool(
"ast_grep_find_pattern",
{
"file_path": "src/example.cs",
"pattern": "public class $NAME"
}
)
# Process results
content_item = find_result[0]
result_data = json.loads(content_item.text)
print(f"Found {result_data.get('count', 0)} matches")
if __name__ == "__main__":
asyncio.run(main())
The server provides the following tools:
- ast_grep_set_project_path: Set the project path for subsequent operations
- ast_grep_parse_code: Parse code into an AST
- ast_grep_find_pattern: Find patterns in code files
- ast_grep_replace_pattern: Replace patterns in code files
- ast_grep_run_yaml_rule: Run custom YAML rules on code files
- ast_grep_scan_project: Scan entire projects for patterns or rule violations
- ast_grep_initialize_project: Initialize a new ast-grep project
- ast_grep_test_rule: Test ast-grep rules
- Python
- JavaScript
- TypeScript
- Rust
- Go
- Java
- C
- C++
- C#
code-analysis-mcp-server/
├── src/
│ ├── __init__.py
│ ├── server.py # Main MCP server setup
│ ├── tools/
│ │ ├── __init__.py # Tool registration
│ │ ├── ast_grep/
│ │ │ ├── __init__.py
│ │ │ ├── tools.py # ast-grep tool implementations
│ │ └── common/
│ │ ├── __init__.py
│ │ └── utils.py # Shared utilities
│ └── resources/
│ ├── __init__.py
│ └── status.py # System status resource
├── tests/
├── pyproject.toml
├── setup.py
├── requirements.txt
├── Dockerfile
└── README.md
Contributions are welcome! Please feel free to submit a Pull Request.
This project is licensed under the MIT License - see the LICENSE file for details.
MIT License
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