Nuanced MCP Server
Provides call graph analysis for LLMs using the nuanced library.
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
{
"mcpServers": {
"nuanced": {
"command": "uv",
"args": [
"--directory",
"/path/to/nuanced-mcp",
"run",
"nuanced_mcp_server.py"
]
}
}
}
Verwandte Server
Scout Monitoring MCP
SponsorPut performance and error data directly in the hands of your AI assistant.
Alpha Vantage MCP Server
SponsorAccess financial market data: realtime & historical stock, ETF, options, forex, crypto, commodities, fundamentals, technical indicators, & more
mcp-codebase-index
Structural codebase indexer with 17 query tools. 87% token reduction. Zero dependencies.
MCP Server for Drupal
A TypeScript-based MCP server that acts as a companion to the Drupal MCP module, communicating via STDIO.
공공 API 연동 MCP 샘플
Integrates the Korea Meteorological Administration's public weather API to provide climate data.
Distance Tools MCP
A remote MCP server example deployable on Cloudflare Workers, featuring customizable tools and no authentication.
Mezmo MCP
Mezmo's remote MCP server connects AI assistants to Mezmo's Observability platform so you can run advanced root-cause analysis, discover pipelines, and export logs without hosting anything yourself.
Steadybit
Interact with the Steadybit platform to run chaos engineering experiments.
WebDev MCP
Provides a collection of useful web development tools.
MCP Toolhouse
Provides access to a wide range of tools from the Toolhouse platform.
MCP Framework Starter
A starter project for building Model Context Protocol (MCP) servers with the mcp-framework.
Deep Code Reasoning MCP Server
Performs complementary code analysis by combining Claude Code and Google's Gemini AI.