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fabdendev

Ferret MCP

by fabdendev
OverviewSchemaRelated ServersScoreDiscussions
Python
Local

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
FERRET_LLM_MODELNoModel nameclaude-haiku-4-5-20251001
FERRET_LLM_API_KEYNoAPI key for Anthropic (required for Anthropic provider)
FERRET_LLM_BASE_URLNoBase URL for OpenAI-compatible providershttp://localhost:11434/v1
FERRET_LLM_PROVIDERNoLLM provider: anthropic or openai (for Ollama, vLLM, LM Studio)anthropic

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Features and capabilities supported by this server

Protocol revision2025-11-25

CapabilityDetails
tools
{
  "listChanged": true
}
logging
{}
prompts
{
  "listChanged": false
}
resources
{
  "subscribe": false,
  "listChanged": false
}
extensions
{
  "io.modelcontextprotocol/ui": {}
}
experimental
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
scanB

Scan a repository and return an overview: languages, file structure, entry points, config files.

Args: path: Absolute path to the repository root directory.

dependenciesA

Extract all dependencies — external packages and internal import graph with core modules.

Args: path: Absolute path to the repository root directory.

architectureB

Analyze repository architecture — layers, patterns (MVC, hexagonal, pipeline, etc.), module breakdown.

Args: path: Absolute path to the repository root directory.

patternsB

Detect code patterns and conventions — design patterns, naming, testing, error handling, config.

Args: path: Absolute path to the repository root directory.

api_surfaceA

Extract the complete API surface — REST endpoints, MCP tools, CLI commands, GraphQL, gRPC, public exports.

Args: path: Absolute path to the repository root directory.

full_extractionA

Run ALL analyses and return a comprehensive knowledge extraction report.

Combines: scan, dependencies, architecture, patterns, and API surface into a single document. Use this for complete repo understanding.

Args: path: Absolute path to the repository root directory.

deepB

AI-powered deep analysis — produces a comprehensive Knowledge Extraction Report.

Uses an LLM (Anthropic or local) to analyze all static extraction data plus key file contents, producing an expert-level architectural analysis with insights about design decisions, data flow, strengths, risks, and learning path.

Requires FERRET_LLM_API_KEY (for Anthropic) or a local LLM server. Configure via env vars: FERRET_LLM_PROVIDER, FERRET_LLM_MODEL, FERRET_LLM_BASE_URL.

Args: path: Absolute path to the repository root directory.

askA

Ask a specific question about a repository, answered by AI with full codebase context.

The LLM receives all static analysis data + key file contents, then answers your question based on that evidence.

Requires FERRET_LLM_API_KEY (for Anthropic) or a local LLM server.

Args: path: Absolute path to the repository root directory. question: The question you want answered about this codebase.

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

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