Asterisk MCP Server
@getAsterisk
About Asterisk MCP Server
Asterisk Model Context Protocol (MCP) server.
Basic information
Config
No standard config provided
This server doesn't expose a parseable MCP config block in its README. See the repository for install instructions.
RepositoryTools
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Overview
What is Asterisk MCP Server?
A middleware server that connects to the Asterisk security API to provide real‑time security analysis of code. It implements the Model Context Protocol (MCP) to expose security scanning tools to AI assistants (e.g., Claude, Cursor, Cline, Windsurf) so they can analyze code for vulnerabilities.
How to use Asterisk MCP Server?
Install with pipx or uvx, then run with command‑line arguments (e.g., --api-url, --key, --transport). Configuration can also be done through the graphical settings UI. A sample MCP client configuration is provided in the README.
Key features of Asterisk MCP Server
- Code Snippet Scanning for security vulnerabilities
- Codebase Scanning with accurate context coverage
- Change Verification for code in chat history
- Graphical Settings UI (dearpygui)
- Flexible stdio and SSE transport protocols
- Comprehensive logging with configurable verbosity
Use cases of Asterisk MCP Server
- Scan a code snippet for vulnerabilities during development
- Scan an entire codebase for security issues
- Verify that code changes do not introduce new vulnerabilities
- Integrate real‑time security analysis into AI‑assisted coding
FAQ from Asterisk MCP Server
How do I get an API key?
Get your API key from https://app.mcp.asterisk.so.
What transport protocols are supported?
The server supports stdio and sse (set via the --transport argument).
What are the system requirements?
Python 3.10+, pipx / uvx, and dependencies including httpx, mcp[cli], and dearpygui (for the settings UI).
How do I resolve authentication errors?
Check that your API key is correctly set and has the necessary permissions. Regenerate the key from the dashboard if needed.
How do I fix timeout errors for large codebases?
Increase the API timeout setting, analyze smaller portions of code separately, or check your network connection stability.
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