Codegraphcontext
An MCP server that provides code context for AI assistants by indexing local code into a graph database, supporting code analysis, relationship query, and real - time update functions.
rating : 2.5 points
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What is CodeGraphContext?
CodeGraphContext is an intelligent code analysis tool that can automatically scan your Python projects, build a code knowledge graph, and provide you with functions such as code understanding, relationship analysis, and impact assessment through an AI assistant.How to use CodeGraphContext?
With simple installation and configuration, you can interact with the AI assistant through natural language to query code relationships, analyze the scope of impact, discover unused code, etc.Applicable scenarios
Suitable for scenarios such as software development teams, code reviews, project maintenance, refactoring planning, and code learning, especially for code understanding of large and complex projects.Main features
Code indexing
Automatically analyze the Python code structure, extract elements such as functions, classes, methods, variables, etc., and build a knowledge graph
Relationship analysis
Provide multi - dimensional code relationship query and analysis such as call relationships, inheritance relationships, import relationships, etc.
Real - time updates
Monitor file changes and automatically update the graph to ensure the real - time and accuracy of code information
Interactive setup
Provide a user - friendly command - line wizard to simplify the installation and configuration process
Advantages
No need to manually write complex queries, and you can obtain code insights through natural language
The real - time update mechanism ensures that the code information is always up - to - date
Visualize code relationships to help quickly understand the structure of complex projects
Support the analysis and processing of large - scale code libraries
Limitations
Currently mainly supports the Python language, and support for other languages is limited
Requires configuring a graph database environment, and the initial setup is relatively complex
It may take a long initial indexing time for very large projects
How to use
Install the tool
Install the CodeGraphContext package via pip
Run the setup wizard
Use the interactive command - line tool to complete the initial configuration
Start the server
Start the MCP server to start the service
Index the code
Add your project code to the graph for indexing
Usage examples
Code impact analysis
Before modifying an important function, understand which other parts of the code will be affected by the modification
Code navigation and understanding
Quickly find and understand the implementation and usage of specific code
Dependency analysis
Understand the usage of third - party libraries in the project
Code quality check
Discover potentially unused code in the project
Frequently Asked Questions
What kind of graph database is required?
Which programming languages are supported?
How long does it take to index a large project?
How to monitor the indexing progress?
Related resources
Official documentation
Detailed installation, configuration, and usage guides
Neo4j graph database
The official website of the graph database, providing installation and learning resources
MCP protocol specification
Official documentation of the Model Context Protocol

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