AI Distiller MCP vs MCP Server

A side-by-side look at the AI Distiller MCP and MCP Server MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.

AI Distiller MCP logoAI Distiller MCPSecurity · Local subprocess (stdio)Extracts essential code structure from large codebases into AI-digestible format, helping AI agents write code that correctly uses existing APIs on the first attempt.65GreatAuth: no auth requiredMCP Server logoMCP ServerSecurity · Local subprocess (stdio)MCP server for RAD Security, providing AI-powered security insights for Kubernetes and cloud environments. This server provides tools for querying the Rad Security API and retrieving security findings, reports, runtime data and many more.65GreatAuth: api key required

Verdict: choose AI Distiller MCP for security work as a local process; choose MCP Server for security as a local process. You can also run both side by side in one mcpServers block.

Which MCP server should you choose?

AI Distiller MCP logoChoose AI Distiller MCP when

  • You need dedicated capabilities in the Security domain.
  • You prefer a local stdio subprocess transport.
  • Its auth model fits you: No auth required.
  • You want tools like distill_file, distill_directory, distill_with_dependencies.
Explore AI Distiller MCP

MCP Server logoChoose MCP Server when

  • You need dedicated capabilities in the Security domain.
  • You prefer a local stdio subprocess transport.
  • Its auth model fits you: API key required.
  • You want tools like list_containers, get_container_details, list_clusters.
Explore MCP Server

Feature & specification comparison

Rows where the two servers differ are marked.

SpecAI Distiller MCP logoAI Distiller MCPMCP Server logoMCP Server
CategorySecuritySecurity
Quality signal65/100 · Great65/100 · Great
Install commandConfirmedConfirmed
TransportLocal subprocess (stdio)Local subprocess (stdio)
AuthNo auth requiredAPI key required
PricingFreeBYOK (pay the provider)
Required env varsNone listedNone listed
Verified ownerCommunity listingCommunity listing
GitHub stars1726
Directory activity 4 views 0 installs 0 upvotes 3 views 0 installs 0 upvotes
Tools1654

Tools & capabilities

AI Distiller MCP tools 16

  • distill_fileExtracts essential code structure from a single file - the core functionality of AI Distiller. Returns clean, structured code signatures optimized for AI context windows. USAGE: Essential for providing accurate code context to AI assistants. Automatically detects language and extracts API signatures, types, and structure while removing unnecessary implementation details.
  • distill_directoryExtracts essential code structure from entire directories - the core functionality of AI Distiller. Processes all supported programming languages and returns structured API/code signatures optimized for AI context windows. USAGE: Perfect for understanding codebases, API discovery, and providing accurate code context to AI assistants. Supports filtering by visibility levels, file patterns, and content types.
  • distill_with_dependenciesAnalyzes call dependencies and returns distilled code of only relevant methods/classes up to specified depth. This advanced feature traces function/method calls across files and includes only the code that is actually called from the target file, creating focused distillations for deep code analysis. USAGE: Perfect for understanding code execution flows, impact analysis, and creating focused context for AI assistants. Particularly useful for large codebases where you need to understand how specific functionality works across multiple files.
  • aid_hunt_bugsGenerates a bug hunting prompt with distilled code for AI agents to systematically identify potential bugs, logical errors, race conditions, and quality issues. Use when you need AI to analyze code for hidden bugs or perform a comprehensive code health check. OUTPUT: Generates a markdown file with bug hunting prompt and distilled code. The response includes the file path - AI agents should read this file and follow instructions to perform the actual bug analysis.
  • aid_suggest_refactoringGenerates a refactoring analysis prompt with distilled code for AI agents to identify specific refactoring opportunities. Use when you need AI to suggest improvements for code quality, readability, maintainability, or performance. OUTPUT: Generates a markdown file with refactoring prompt and distilled code. The response includes the file path - AI agents should read this file and follow instructions to provide refactoring suggestions with before/after examples.
  • aid_generate_diagramGenerates a diagram creation prompt with distilled code for AI agents to create architectural diagrams in Mermaid format. Use when you need AI to generate flowcharts, sequence diagrams, class diagrams, and architecture overviews. OUTPUT: Generates a markdown file with diagram generation prompt and distilled code. The response includes the file path - AI agents should read this file and follow instructions to create 10+ Mermaid diagrams.
  • aid_analyze_securityGenerates a security analysis prompt with distilled code for AI agents to perform comprehensive security audits with OWASP Top 10 focus. Use when you need AI to identify vulnerabilities, security anti-patterns, and weak points. OUTPUT: Generates a markdown file with security audit prompt and distilled code. The response includes the file path - AI agents should read this file and follow instructions to analyze security vulnerabilities and suggest remediation.
  • aid_generate_docsGenerates documentation creation prompts with distilled code for AI agents to create comprehensive documentation including API references, usage examples, and developer guides. Use when you need AI to generate technical documentation from code. OUTPUT: Generates markdown files with documentation prompts and distilled code. The response includes file paths - AI agents should read these files and follow instructions to create the actual documentation.
  • aid_deep_file_analysisGenerates task lists and prompts for systematic file-by-file analysis. Creates a structured workflow where AI agents analyze each file across multiple dimensions (Security, Performance, Maintainability, Readability). Perfect for comprehensive codebase reviews. OUTPUT: Generates task list, summary template, and directory structure for organizing analysis results. AI agents should read the task list and follow instructions systematically.
  • aid_multi_file_docsCreates documentation workflow prompts with file relationships. Generates structured prompts that guide AI agents to create interconnected documentation covering multiple files, their relationships, and overall system architecture. OUTPUT: Generates workflow files that AI agents can follow to create comprehensive documentation with proper cross-references.
  • aid_complex_analysisEnterprise-grade analysis prompt with full codebase context. Generates comprehensive prompts for architecture analysis, compliance checks, and detailed findings. Best suited for large codebases requiring deep architectural insights. OUTPUT: Generates analysis prompt with distilled code that AI agents can use to create architecture diagrams, identify patterns, and provide strategic recommendations.
  • aid_performance_analysisPerformance optimization prompt with complexity focus. Generates analysis prompts that guide AI agents to identify performance bottlenecks, analyze algorithmic complexity, and suggest optimization strategies. OUTPUT: Generates performance analysis prompt focusing on scalability issues, resource usage, and optimization opportunities.
  • +4 more on the listing page

MCP Server tools 54

  • list_containersList containers secured by RAD Security with optional filtering by image name, image digest, namespace, cluster_id, or free text search
  • get_container_detailsGet detailed information about a container secured by RAD Security
  • list_clustersList Kubernetes clusters managed by RAD Security
  • get_cluster_detailsGet detailed information about a specific Kubernetes cluster managed by RAD Security
  • who_shelled_into_podGet k8s audit logs with information about users who shelled into a pod
  • list_imagesList container images with optional filtering by page, page size, sort, and search query
  • list_image_vulnerabilitiesList vulnerabilities in a container image with optional filtering by severity
  • get_top_vulnerable_imagesGet the most vulnerable images from your account
  • get_image_sbomGet the SBOM of a container image
  • ignore_cveIgnore a CVE for this account so it no longer appears in vulnerability reporting. Use for confirmed false positives, accepted risks, or won't-fix decisions. Do NOT use for remediated CVEs — those drop off automatically on the next scan.
  • unignore_cveRemove an account-wide CVE disposition, restoring the CVE to vulnerability reporting.
  • list_cve_dispositionsList active CVE dispositions (ignored / false positive) for this account, with reason and author.
  • +42 more on the listing page

Ready-to-paste client configs

Paste either block (or both) into your client config, e.g. claude_desktop_config.json or ~/.cursor/mcp.json. We only show a config when the install command is confirmed.

AI Distiller MCP

mcpServers (Claude Desktop / Cursor)
{
  "mcpServers": {
    "janreges-ai-distiller-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "@janreges/ai-distiller-mcp"
      ]
    }
  }
}

MCP Server

mcpServers (Claude Desktop / Cursor)
{
  "mcpServers": {
    "rad-security-mcp-server": {
      "command": "npx",
      "args": [
        "-y",
        "@rad-security/mcp-server"
      ]
    }
  }
}

Frequently asked questions

AI Distiller MCP is categorized under Security and uses a local stdio subprocess. MCP Server belongs to Security and uses a local stdio subprocess. Pick AI Distiller MCP for security work and MCP Server for security.

Copy the mcpServers block from the config section on this page into your client's config (for example claude_desktop_config.json or ~/.cursor/mcp.json), then fully restart the client.

AI Distiller MCP is listed as free. Auth: no auth required. MCP Server is bring-your-own-key: usage is billed by the API provider you supply a key for. Auth: api key required. If a server needs environment variables such as API keys, define them under the env key in your client's MCP config.

Yes. MCP clients support multiple servers: add janreges-ai-distiller-mcp and rad-security-mcp-server as separate keys in the same mcpServers object, and your assistant will call tools from either one.

On AllMCPs, AI Distiller MCP has a quality signal of 65/100 (Great) with 4 views, 0 installs and 172 GitHub stars. MCP Server has 65/100 (Great) with 3 views, 0 installs and 6 GitHub stars.