consult7

What is Consult7?

Consult7 is a Model Context Protocol (MCP) server designed to enable AI agents to utilize large context window models for analyzing extensive file collections. This includes entire codebases, document repositories, or mixed content that would otherwise exceed the context limits of current AI agents. It supports various providers such as OpenRouter, OpenAI, and Google AI.

How to use Consult7?

Consult7 can be integrated with AI agents like Claude Code and Claude Desktop. For Claude Code, you can add Consult7 as an MCP server using commands like claude mcp add -s user consult7 uvx -- consult7 openrouter your-api-key. For Claude Desktop, you add a configuration to your mcpServers in the Claude Desktop configuration file. Consult7 automatically downloads and runs in an isolated environment using uvx, requiring no manual installation. You specify the model when calling the tool, not at startup.

Key Features of Consult7

• Large Context Analysis: Enables AI agents to process extensive file collections (codebases, documents) that exceed their native context limits.
• Provider Agnostic: Supports OpenRouter, OpenAI, and Google AI models.
• Recursive File Collection: Gathers all files matching a regex pattern from a given path, including subdirectories.
• Single Context Assembly: Assembles collected files into a single context for the large context window model.
• Direct Result Feeding: Feeds the query result directly back to the interacting AI agent.
• Flexible Model Selection: Allows specifying different models and "thinking" modes (e.g., gemini-2.5-flash|thinking) for various providers.
• Easy Integration: Simple installation and configuration with Claude Code and Claude Desktop.

Use Cases of Consult7

• Summarize an entire codebase: Query: "Summarize the architecture and main components of this Python project" with a pattern for Python files.
• Find specific method definitions: Query: "Find the implementation of the authenticate_user method and explain how it handles password verification" with patterns for Python, JavaScript, or TypeScript files.
• Analyze test coverage: Query: "List all the test files and identify which components lack test coverage" with patterns for test files.
• Complex analysis with thinking mode: Query: "Analyze the authentication flow across this codebase. Think step by step about security vulnerabilities and suggest improvements" using models with thinking capabilities.

FAQ about Consult7

Q: Why use Consult7 when my AI agent has a decent context window? A: Consult7 is particularly useful when your AI agent's context window, even if large (e.g., Claude with 200K tokens), is still insufficient to process an entire codebase or document collection in a single query. Consult7 allows leveraging models with even larger context windows for such tasks.

Q: What providers does Consult7 support? A: Consult7 supports OpenRouter, OpenAI, and Google AI.

Q: Do I need to install anything manually? A: No, uvx automatically downloads and runs Consult7 in an isolated environment, so no manual installation is required.

Q: How do I specify the model to use? A: The model is specified when calling the tool, not at startup. The server provides example models for your chosen provider upon startup.

Q: How can I test my API connection with Consult7? A: You can test your API connection using the --test flag with the uvx consult7 command, for example: uvx consult7 openrouter sk-or-v1-... --test.

Q: How do I uninstall Consult7? A: To remove Consult7 from Claude Code, use the command: claude mcp remove consult7 -s user. This is also recommended before reinstalling.

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-flash-lite-preview-06-17" - Ultra fast lite 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-flash-lite-preview-06-17|thinking" - Ultra 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
• "google/gemini-2.5-flash-lite-preview-06-17" - Ultra 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
• "google/gemini-2.5-flash-lite-preview-06-17|thinking" - Ultra fast with reasoning
• "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