The Code Analysis MCP Server enables AI models to explore, analyze, and understand codebases through natural language conversations.
Natural Code Exploration: Ask high-level questions about your codebase (e.g., "What are all the different payment providers integrated in the system?").
Deep Code Understanding: Extract insights about data models, system architecture, and data flows.
Dynamic Analysis: Trace relationships and specific code behaviors.
Core Functionalities:
Initialize a code repository for analysis using
initialize_repositoryRetrieve repository details using
get_repo_infoExamine file and directory structure with
get_repo_structureRead and analyze specific files using
read_file
Benefits:
Cost-effective: Uses existing Claude Pro subscriptions
Lightweight: Simple solution for code exploration
Local access: Safely scans local codebases with path validation and .gitignore support
Integrates with Git repositories to analyze code, supporting features like respecting .gitignore files and providing repository structure information.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Code Analysis MCP Servershow me the main database models in the project"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Code Analysis MCP Server
A Model Context Protocol (MCP) server that enables AI models to understand and analyze codebases through natural language conversations.
β¨ Highlights
Natural Code Exploration: Ask high-level questions about your codebase
"What are all the different payment providers integrated in the system?"Deep Code Understanding: Extract insights about data models and system architecture
"How does the user authentication flow work from frontend to database?"Dynamic Analysis: Trace data flows and understand system relationships
"Show me all the places where we calculate transaction fees"
Related MCP server: MCP-Python
Limitations
This tool is a simpler alternative to more sophisticated code analysis tools / copilot like Aider. While it lacks the advanced code analysis capabilities and robustness of tools like Aider, it offers a lightweight solution for codebase exploration if you already have a Claude Pro subscription. The main advantages are:
Cost-Effective: Using your existing Claude Pro subscription means no additional API costs, unlike tools that can get expensive when analyzing large codebases
Simple Setup: Quick to get started with minimal configuration
Basic Analysis: Good for high-level code understanding and exploration
Note that due to its simpler approach to code analysis, it may make more errors or provide less detailed insights compared to more specialized tools.
π Quick Start
Install the server:
git clone https://github.com/saiprashanths/code-analysis-mcp.git
cd code-analysis-mcpInstall Claude Desktop App. For more instructions on setting up an MCP Server with Claude Desktop app, see docs
Configure the server in Claude Desktop's configuration file:
macOS:
~/Library/Application Support/Claude/claude_desktop_config.jsonWindows:
%APPDATA%\Claude\claude_desktop_config.json
{
"mcpServers": {
"code-analysis": {
"command": "uv",
"args": [
"--directory",
"/PATH/TO/YOUR/REPO",
"run",
"code_analysis.py"
]
}
}
}Restart Claude Desktop and start analyzing your code!
Ensure the tool is correctly setup
Clicking the tools icon should display the
code-analysistools
Clicking the integrations button should display the
analyze_code_repositoryprompt
π‘ Example Usage
Here's how you might use the tool to understand a complex codebase:
Start by clicking on the analyze_code_repository prompt shown below. That will guide you through the process
to initialize the repo and get started.
You: How does the transaction processing work in this system?
Claude: Let me analyze the data flow for transactions.
Looking at the codebase, I can see that transaction processing happens through several key components:
1. Raw transaction data is captured in the `TransactionEvent` model with fields for:
- Payment status
- Amount
- Fee calculations
- Processing timestamps
2. This data is then processed through the PaymentSummary model, which:
- Validates payment provider responses
- Calculates processing fees
- Records transaction status
Would you like me to explain any part of this in more detail?
You: What are the key database tables involved?
Claude: The main tables in the transaction processing pipeline are:
1. transaction_events: Stores raw payment events
2. payment_summary: Processed transaction records
3. payment_providers: Provider configuration
4. merchant_accounts: Account-specific settings
Let me know if you'd like to see the schema for any of these tables!π§ Available Tools
initialize_repository
Initialize a code repository for analysis:
initialize_repository("/path/to/repo")
# Output: Successfully initialized code repository at: /path/to/repoget_repo_info
Retrieve information about the initialized repository:
get_repo_info()
# Output:
# Code Repository Information:
# Path: /path/to/repo
# Exists: True
# Is Directory: True
# Found .gitignore fileget_repo_structure
Examine repository file structure:
get_repo_structure(depth=2)
# Output:
# π src/
# π api/
# π routes.py
# π models.py
# π utils/
# π helpers.py
# π main.pyread_file
Read and analyze specific files:
read_file("src/api/models.py")
# Output:
# File: src/api/models.py
# Language: python
# Size: 2.3 KB
#
# [File contents...]βοΈ Technical Details
Default scanning depth: 3 levels
Maximum file size: 1MB
Maximum lines per file: 1000
Ignores paths listed in .gitignore
Local file system access only
Validates file paths to prevent directory traversal
π License
This project is licensed under the MIT License - see the LICENSE file for details.