Understand Anything MCP
About
A MCP server that empowers your AI agents to understand your entire project architecture, and a headless CI gateway to enforce architectural rules before code is merged. Prerequisite: ua-mcp is a lightweight reader tha
Details
- Author
- uamcp
- Downloads
- 246
- Categories
- Developer Tools
Jump to
- Branch Protection / CI Gate: Automatically block high-risk PRs based on the codebase graph
- Architectural Rules: Define custom .ua-rules.json to enforce boundaries
- Blast Radius Analysis: Detect exactly which downstream files will break if a module is modified
- Free Tier: Evaluates blast-radius and logs the risk level
- Pro Tier: Automatically blocks the merge if the risk is HIGH or violates architectural rules
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
Understand Anything MCPCommand (node, npx, python, etc.)Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
The README includes setup instructions such as "command": "npx",.
ua_status
Check the operational status of the Understand-Anything MCP server. Call this to verify if the knowledge graph is successfully loaded and active.
ua_scan
Check if a knowledge graph file is present and currently loaded. Returns instructions on how to generate the graph if missing.
ua_graph_summary
Get a high-level statistical summary of the codebase knowledge graph. Returns total node and edge counts to gauge project size.
ua_architecture_report
Generate a module-level architecture report from the knowledge graph. Returns a breakdown of files per directory to identify main components.
ua_dependency_report
Generate a top-level dependency report from the knowledge graph. Identifies the most heavily depended-on files in the codebase (high fan-in).
ua_explain
Explain a specific part of the codebase by retrieving its 1-hop dependencies. Call this to understand what a file imports and where it is used.
ua_onboarding_doc
Generate an onboarding overview document for new developers. Call this first when entering a new codebase to get oriented.
ua_find_callers
Find all callers of a specific function or file up to a certain depth. Helps trace execution paths.
ua_impact_analysis
Analyze the downstream impact of changing a specific file. Returns a list of files that depend on it.
ua_precheck
Pre-flight architectural risk check. Call this before modifying any critical systems or refactoring to estimate risk radius.
ua_rules
Evaluate architectural constraints against the current knowledge graph. Generates a full violation report.
ua_rules_check
Mid-session continuous audit. Evaluate constraints to ensure recent changes haven't introduced violations.
ua_init_rules
Initialize a starter .ua-rules.json file in the workspace if one doesn't already exist.
ua_ci_check
Run a CI-style impact analysis on a PR diff to identify risk factors. Returns affected files, risk level, and potential issues.
ua_validate_graph
Validate the structural integrity and syntax of the loaded knowledge graph JSON.
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"understand anything mcp": {
"understand-anything": {
"command": "npx",
"args": [
"-y",
"ua-mcp"
],
"env": {
"UA_PROJECT_PATH": "/absolute/path/to/your/project"
}
}
}
}
}
McpServers
{
"understand-anything": {
"command": "npx",
"args": [
"-y",
"ua-mcp"
],
"env": {
"UA_PROJECT_PATH": "/absolute/path/to/your/project"
}
}
}
A MCP server that empowers your AI agents to understand your entire project architecture, and a headless CI gateway to enforce architectural rules before code is merged.
Prerequisite: ua-mcp is a lightweight reader that connects your AI assistant to your local Understand-Anything knowledge graph. It does not build the graph itself. You must install the core scanner from Egonex-AI/Understand-Anything and run /understand in your project to produce the .ua/knowledge-graph.json file. Commit this file to your repository before proceeding.
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