What is Consult7

Consult7 is a Model Context Protocol (MCP) server designed to empower AI agents to consult large context window models for analyzing extensive collections of files, such as complete codebases or document repositories, which exceed the agents’ context limits.

Use cases

Common use cases for Consult7 include summarizing the architecture of a codebase, locating specific method implementations in various programming languages, and analyzing test coverage to identify components lacking tests amidst large project files.

How to use

To use Consult7, users must install it via the command line or by configuring it in Claude Desktop. They specify a file collection path, apply a regex pattern to match files, and provide a query to send to the large context window model for analysis.

Key features

Consult7 features recursive file collection based on specified regex patterns, integration with large context window models, and the ability to effortlessly handle extensive queries and responses, significantly enhancing the capability of AI agents in processing large data sets.

Where to use

Consult7 is ideally used in scenarios where AI agents are tasked with analyzing significant amounts of data, such as in software development environments, document analysis within agencies, or any application requiring the extraction of insights from large file collections.

Consult7 MCP Server

Consult7 is a Model Context Protocol (MCP) server that enables AI agents to consult large context window models for analyzing extensive file collections - entire codebases, document repositories, or mixed content that exceed the current agent’s context limits. Supports providers Openrouter, OpenAI, and Google.

Why Consult7?

When working with AI agents that have limited context windows (like Claude with 200K tokens), Consult7 allows them to leverage models with massive context windows to analyze large codebases or document collections that would otherwise be impossible to process in a single query.

“For Claude Code users, Consult7 is a game changer.”

How it works

Consult7 recursively collects all files from a given path that match your regex pattern (including all subdirectories), assembles them into a single context, and sends them to a large context window model along with your query. The result of this query is directly fed back to the agent you are working with.

Example Use Cases

Summarize an entire codebase

• Query: “Summarize the architecture and main components of this Python project”
• Pattern: ".*\.py$" (all Python files)
• Path: /Users/john/my-python-project

Find specific method definitions

• Query: “Find the implementation of the authenticate_user method and explain how it handles password verification”
• Pattern: ".*\.(py|js|ts)$" (Python, JavaScript, TypeScript files)
• Path: /Users/john/backend

Analyze test coverage

• Query: “List all the test files and identify which components lack test coverage”
• Pattern: ".*test.*\.py$|.*_test\.py$" (test files)
• Path: /Users/john/project

Complex analysis with thinking mode

• Query: “Analyze the authentication flow across this codebase. Think step by step about security vulnerabilities and suggest improvements”
• Pattern: ".*\.(py|js|ts)$"
• Model: "gemini-2.5-flash|thinking"
• Path: /Users/john/webapp

Installation

Claude Code

Simply run:

# OpenRouter
claude mcp add -s user consult7 uvx -- consult7 openrouter your-api-key

# Google AI
claude mcp add -s user consult7 uvx -- consult7 google your-api-key

# OpenAI
claude mcp add -s user consult7 uvx -- consult7 openai your-api-key

Claude Desktop

Add to your Claude Desktop configuration file:

{
  "mcpServers": {
    "consult7": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "consult7",
        "openrouter",
        "your-api-key"
      ]
    }
  }
}

Replace openrouter with your provider choice (google or openai) and your-api-key with your actual API key.

No installation required - uvx automatically downloads and runs consult7 in an isolated environment.

Command Line Options

uvx consult7 <provider> <api-key> [--test]

• <provider>: Required. Choose from openrouter, google, or openai
• <api-key>: Required. Your API key for the chosen provider
• --test: Optional. Test the API connection

The model is specified when calling the tool, not at startup. The server shows example models for your provider on startup.

Model Examples

Google

Standard models:

• "gemini-2.5-flash" - Fast model
• "gemini-2.5-pro" - Intelligent model
• "gemini-2.0-flash-exp" - Experimental model

With thinking mode (add |thinking suffix):

• "gemini-2.5-flash|thinking" - Fast with deep reasoning
• "gemini-2.5-pro|thinking" - Intelligent with deep reasoning

OpenRouter

Standard models:

• "google/gemini-2.5-pro" - Intelligent, 1M context
• "google/gemini-2.5-flash" - Fast, 1M context
• "anthropic/claude-sonnet-4" - Claude Sonnet, 200k context
• "openai/gpt-4.1" - GPT-4.1, 1M+ context

With reasoning mode (add |thinking suffix):

• "anthropic/claude-sonnet-4|thinking" - Claude with 31,999 reasoning tokens
• "openai/gpt-4.1|thinking" - GPT-4.1 with reasoning effort=high

OpenAI

Standard models (include context length):

• "gpt-4.1-2025-04-14|1047576" - 1M+ context, very fast
• "gpt-4.1-nano-2025-04-14|1047576" - 1M+ context, ultra fast
• "o3-2025-04-16|200k" - Advanced reasoning model
• "o4-mini-2025-04-16|200k" - Fast reasoning model

O-series models with |thinking marker:

• "o1-mini|128k|thinking" - Mini reasoning with |thinking marker
• "o3-2025-04-16|200k|thinking" - Advanced reasoning with |thinking marker

Note: For OpenAI, |thinking is only supported on o-series models and serves as an informational marker. The models use reasoning tokens automatically.

Advanced: You can specify custom thinking tokens with |thinking=30000 but this is rarely needed.

Testing

# Test OpenRouter
uvx consult7 openrouter sk-or-v1-... --test

# Test Google AI
uvx consult7 google AIza... --test

# Test OpenAI
uvx consult7 openai sk-proj-... --test

Uninstalling

To remove consult7 from Claude Code (or before reinstalling):

claude mcp remove consult7 -s user