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AI Distiller MCP

by janreges

Distills codebases into compact API context and generates prompts for documentation, refactoring, security, and other AI analyses.

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Install AI Distiller MCP

Pick your client, then add it in one click or paste the config.

STDIONode.js
~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "janreges-ai-distiller-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "@janreges/ai-distiller-mcp"
      ]
    }
  }
}

Settings → Developer → Edit Config, merge this into mcpServers, then fully quit and reopen Claude Desktop.

Automated check passed— started and listed 16 tools correctly (1mo ago).

Overview

janreges/ai-distiller-mcp MCP server exposes AI Distiller through MCP tools for extracting concise code structure from files and directories. It preserves public APIs, types, imports, and documentation by default while omitting implementation details and non-public members, with configurable filtering. Additional tools generate prompts for security audits, bug hunting, refactoring, diagrams, documentation, performance, and best-practice reviews. Reach for it when an AI agent needs an efficient structural view of a large codebase rather than raw source files.

Use cases

  • Distill a large source directory before asking an AI agent to modify existing APIs
  • Generate an OWASP Top 10 security-analysis prompt from selected code
  • Create a systematic file-by-file analysis workflow
  • Prepare documentation prompts for multiple related files
  • Inspect directory contents and file statistics before analysis

Key features

  • Distills individual files and directories into compact code structure
  • Filters public APIs, types, imports, documentation, and implementation details
  • Generates prompts for security, refactoring, bugs, documentation, and performance
  • Supports text, Markdown, JSON, JSONL, and XML output formats
  • Provides directory browsing and capability discovery tools
  • Supports custom AI actions through a general analysis tool

Tools16

What AI Distiller MCP lets your agent do. Expand a tool for its parameters.

Verified live~4.8k tokens of context

Security & health

What it can reach and how reliably it runs — from our own checks, not the maintainer’s claims.

ActiveLast checked 1d ago

Recent health check succeeded.

21/21 checks healthy over the last 78d

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 9d ago via OSV.dev · @janreges/ai-distiller-mcp (npm)

Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars172Stargazers on the source repository.
npm downloads176Package downloads in the last 30 days.
Last commit5mo agoMost recent push to the default branch.
Availability100%Our rolling endpoint + install checks that succeeded.
Install checkPassedOur sandbox started it and listed its tools.
Tools exposed16Callable tools this server registers over MCP.
Directory activity4 viewsConfig copies, upvotes, and views on AllMCPs.

How AI Distiller MCP works

What janreges/ai-distiller-mcp MCP server does

janreges/ai-distiller-mcp MCP server makes the AI Distiller code-structure extractor available to MCP-compatible clients. It is intended for projects where sending the entire source tree to an AI model would exceed practical context limits or make API relationships difficult to identify.

The core operation reduces source code to a compact representation of the information an agent usually needs to use existing code: public methods, properties, types, imports, and basic documentation. The default output excludes method bodies and protected, internal, or private members. Filtering options can include those members, implementation details, comments, or other content when a broader view is required.

The repository describes support for more than 12 programming languages and provides text, Markdown, structured JSON, JSONL, and XML output formats. Distillation can target one file or a directory, and the tool can report compression and processing statistics.

How it works

The MCP interface separates browsing, extraction, and analysis-prompt generation. list_files helps an agent inspect directories and view file statistics. distill_file and distill_directory then produce reduced code context for a file or directory. get_capabilities reports available AI Distiller capabilities.

The analysis tools do not perform the underlying review themselves. Instead, they prepare prompts containing distilled code for an AI agent to process. Available workflows cover bug hunting, refactoring, Mermaid diagram generation, OWASP Top 10 security analysis, documentation, systematic file-by-file analysis, multi-file documentation, complex analysis, performance, and coding best practices. aid_analyze provides direct access to the AI actions for custom workflows.

Setup and configuration

Install the MCP package published as @janreges/ai-distiller-mcp from npm, then configure it in an MCP-compatible client. The README explicitly names Claude, Cursor, VS Code, and Windsurf as supported integration targets, and includes a Claude Desktop usage guide in its documentation structure.

The generated prompts are saved to a .aid/ directory by default for workflows that create files; small codebases can instead use standard output according to the CLI behavior described by the project.

Configuration follows AI Distiller's filtering model. Public members, documentation, and imports are included by default, while implementation bodies and non-public visibility levels are excluded. Worker count, output format, comments, docstrings, and summary style can be adjusted through the underlying Distiller options.

Tools and capabilities

The MCP tool set includes:

  • File and directory distillation
  • Directory browsing with file statistics
  • Capability discovery
  • Bug-hunting and refactoring prompt generation
  • Mermaid diagram prompt generation
  • OWASP Top 10 security-analysis prompts
  • Documentation and multi-file documentation workflows
  • Deep file analysis and complex analysis workflows
  • Performance and best-practice analysis prompts
  • A general analysis entry point for custom actions

Limitations and notes

AI Distiller prepares context and prompts; it does not carry out the requested security review, refactoring, documentation task, or other analysis itself. An AI agent must read or execute the generated prompt content.

The project identifies this MCP release as an early version and requests feedback through GitHub discussions or issues.

Read the full README View source on GitHub

Reviews

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Frequently Asked Questions about AI Distiller MCP

Install the `@janreges/ai-distiller-mcp` package from npm and configure it in an MCP-compatible client.

The README includes a Claude Desktop MCP usage guide and states that the package integrates with Claude and other MCP-compatible tools.

Yes. Its `distill_directory` tool extracts structure from directories, while `list_files` provides directory browsing and file statistics.

No. Its security tool generates an OWASP Top 10 analysis prompt with distilled code for an AI agent to process.

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