The Nuanced MCP Server enables LLMs to analyze and understand code structure through function call graphs in Python repositories.
Initialize and manage code graphs: Initialize, switch between, and list all initialized repositories
Analyze function relationships: Retrieve call graphs for specific functions and analyze dependencies between functions or modules
Assess change impact: Understand the potential effects of modifying specific functions
Generate prompts: Create prompts for analyzing functions, dependencies, and change impacts
Access summaries: Retrieve overviews of code graphs and detailed function information
Provides call graph analysis tools for Python codebases, allowing for initialization of code graphs, exploration of function call relationships, dependency analysis, and impact assessment of code changes.
Nuanced MCP Server
A Model Context Protocol (MCP) server that provides call graph analysis capabilities to LLMs through the nuanced library.
Overview
This MCP server enables LLMs to understand code structure by accessing function call graphs through standardized tools and resources. It allows AI assistants to:
Initialize call graphs for Python repos
Explore function call relationships
Analyze dependencies between functions
Provide more contextually aware code assistance
API
Tools
initialize_graph
Initialize a code graph for the given repository path
Input:
repo_path
(string)
switch_repository
Switch to a different initialized repository
Input:
repo_path
(string)
list_repositories
List all initialized repositories
No inputs required
get_function_call_graph
Get the call graph for a specific function
Inputs:
file_path
(string)function_name
(string)repo_path
(string, optional) - uses active repository if not specified
analyze_dependencies
Find all module or file dependencies in the codebase
Inputs (at least one required):
file_path
(string, optional)module_name
(string, optional)
analyze_change_impact
Analyze the impact of changing a specific function
Inputs:
file_path
(string)function_name
(string)
Resources
graph://summary
Get a summary of the currently loaded code graph
No parameters required
graph://repo/{repo_path}/summary
Get a summary of a specific repository's code graph
Parameters:
repo_path
(string) - Path to the repository
graph://function/{file_path}/{function_name}
Get detailed information about a specific function
Parameters:
file_path
(string) - Path to the file containing the functionfunction_name
(string) - Name of the function to analyze
Prompts
analyze_function
Create a prompt to analyze a function with its call graph
Parameters:
file_path
(string) - Path to the file containing the functionfunction_name
(string) - Name of the function to analyze
impact_analysis
Create a prompt to analyze the impact of changing a function
Parameters:
file_path
(string) - Path to the file containing the functionfunction_name
(string) - Name of the function to analyze
analyze_dependencies_prompt
Create a prompt to analyze dependencies of a file or module
Parameters (at least one required):
file_path
(string, optional) - Path to the file to analyzemodule_name
(string, optional) - Name of the module to analyze
Usage with Claude Desktop
Add this to your claude_desktop_config.json
UV
hybrid server
The server is able to function both locally and remotely, depending on the configuration or use case.
Tools
An MCP server that enables LLMs to understand and analyze code structure through function call graphs, allowing AI assistants to explore relationships between functions and analyze dependencies in Python repositories.
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