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FDEP MCP Server

by maverox
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Python
Hybrid

FDEP MCP Server

A Static Code Analysis Model Context Protocol (MCP) server delivering 40+ comprehensive analysis tools for enterprise-scale Haskell codebases. Seamlessly integrates with MCP-compatible AI tools and clients to provide real-time code intelligence and architectural insights.

šŸ”Œ MCP Protocol Compliant | šŸ—ļø 40+ Analysis Tools | āš” Real-time Queries

āœØ MCP Server Features

šŸ“Š 40+ Comprehensive Analysis Tools

  • Module Analysis: 7 tools for module structure and dependencies

  • Function Analysis: 8 tools for call graphs and complexity metrics

  • Type System: 6 tools for type relationships and usage patterns

  • Class Analysis: 3 tools for typeclass and instance analysis

  • Import Analysis: 4 tools for dependency visualization

  • Advanced Queries: 4 tools for complex JSON-based code queries

  • Pattern Analysis: 5 tools for code pattern detection

  • Source Location: 3 tools for location-based analysis

  • Enhanced Analysis: 3 tools for advanced structural analysis

šŸš€ Quick Start

Prerequisites

  • Python 3.13+

  • UV package manager

  • PostgreSQL database (must be running)

  • FDEP output from Spider plugin (for comprehensive analysis)

Database Setup

Before installation, ensure PostgreSQL is running and create the required database:

# Start PostgreSQL (if not already running) # On macOS with Homebrew: brew services start postgresql # On Ubuntu/Debian: sudo systemctl start postgresql # Create the database createdb code_as_data # this should match with you $DB_NAME value in .env file (DEFAULT: code_as_data)

Installation

# Clone the repository git clone https://github.com/juspay/fdep-mcp-server.git cd fdep_mcp # Install globally with UV (recommended) uv tool install . # OR install globally with pipx # pipx install . # OR system-wide installation # pip install .vi

Database Setup and Data Import

Important: Complete this step before using the MCP server with any client.

fdep-mcp-server --setup --verbose

This command will:

  • Initialize the PostgreSQL database schema

  • Import and process your FDEP data (if FDEP_PATH is configured)

  • Set up all necessary indexes and relationships

Note: The first run takes time as it processes large FDEP datasets.

Configure Environment

cp .env.example .env # Edit .env with your database settings and FDEP_PATH

šŸ”Œ MCP Client Configuration

After installation, configure your preferred MCP client to connect to the FDEP server:

Claude Code

Add to your ~/.claude/settings.json:

{ "mcpServers": { "fdepAnalyzer": { "command": "fdep-mcp-server", "args": [], "env": { "FDEP_PATH": "/path/to/your/fdep/output" } } } }

Note: The first time running the server takes time as it imports and processes the FDEP data.

Cursor

Add to your Cursor settings (Cmd/Ctrl + , ā†’ Extensions ā†’ MCP):

{ "mcp.servers": { "fdepAnalyzer": { "command": "fdep-mcp-server", "args": [], "env": { "FDEP_PATH": "/path/to/your/fdep/output", "LOG_LEVEL": "INFO" } } } }

Note: The first time running the server takes time as it imports and processes the FDEP data.

VS Code

Install the MCP extension and add to settings.json:

{ "mcp.servers": [ { "name": "fdepAnalyzer", "command": "fdep-mcp-server", "args": [], "env": { "FDEP_PATH": "/path/to/your/fdep/output" } } ] }

Note: The first time running the server takes time as it imports and processes the FDEP data.

Cline

Add to your Cline configuration:

{ "mcpServers": { "fdepAnalyzer": { "command": "fdep-mcp-server", "args": [], "env": { "FDEP_PATH": "/path/to/your/fdep/output" } } } }

Note: The first time running the server takes time as it imports and processes the FDEP data.

Continue.dev

Add to your .continue/config.json:

{ "mcpServers": [ { "name": "fdepAnalyzer", "command": "fdep-mcp-server", "args": [], "env": { "FDEP_PATH": "/path/to/your/fdep/output" } } ] }

Note: The first time running the server takes time as it imports and processes the FDEP data.

Generic MCP Client

For any MCP-compatible client:

{ "server_name": "fdepAnalyzer", "command": "fdep-mcp-server", "args": [], "environment": { "FDEP_PATH": "/path/to/your/fdep/output", "DB_HOST": "localhost", "DB_NAME": "code_as_data", "LOG_LEVEL": "INFO" } }

Note: The first time running the server takes time as it imports and processes the FDEP data.

Environment Variables for All Clients

# Required FDEP_PATH=/path/to/your/fdep/output # Database (if different from defaults) DB_HOST=localhost DB_PORT=5432 DB_NAME=code_as_data DB_USER=postgres DB_PASSWORD=postgres # Optional LOG_LEVEL=INFO DEV_MODE=false

Verify Connection

After configuring your client, verify the connection:

  1. Start your MCP client

  2. Look for "fdepAnalyzer" in available tools/servers

  3. Test with a simple query: list_modules(limit=5)

  4. You should see your Haskell modules listed

šŸ› ļø MCP Tools Available (40+ Total)

šŸ“ Module Analysis (7 tools)

Tool

Description

initialize_database

Setup database and import FDEP data

list_modules

Get list of modules with filtering

get_module_details

Detailed module info with statistics

get_functions_by_module

List all functions in a module

search_modules

Pattern-based module search

get_module_dependencies

Module dependency analysis

get_code_statistics

Comprehensive codebase statistics

āš” Function Analysis (8 tools)

Tool

Description

get_function_details

Detailed function information

search_functions

Search functions by pattern

get_most_called_functions

Find frequently called functions

get_function_call_graph

Function call hierarchy

get_function_callers

Who calls this function

get_function_callees

What functions this calls

analyze_function_complexity

Function complexity metrics

get_function_context

Complete function context with dependencies

šŸ—ļø Type System Analysis (6 tools)

Tool

Description

list_types

Get types by module/pattern with categories

get_type_details

Type info with constructors/fields

search_types

Advanced type search with filtering

get_type_dependencies

Type dependency analysis

analyze_type_usage

Type usage patterns

get_nested_types

Get nested type definitions

šŸ“š Class Analysis (3 tools)

Tool

Description

list_classes

Get class definitions with filtering

get_class_details

Class info with instances

search_classes

Pattern-based class search

šŸ“¦ Import Analysis (4 tools)

Tool

Description

analyze_imports

Import patterns and dependencies

get_import_graph

Module import relationship graphs

find_unused_imports

Potential cleanup candidates

get_import_details

Comprehensive import information

šŸ” Advanced Queries (4 tools)

Tool

Description

execute_query

Basic SQL queries

execute_advanced_query

JSON-based complex queries with joins

execute_custom_query

Custom SQL queries with parameters

find_cross_module_calls

Cross-module function usage

šŸŽÆ Pattern Analysis (5 tools)

Tool

Description

find_similar_functions

Find functions similar to a given function

find_code_patterns

Find recurring code patterns

group_similar_functions

Group functions by similarity

build_type_dependency_graph

Build comprehensive type dependency graph

analyze_type_relationships

Analyze deep type relationships

šŸ“ Source Location (3 tools)

Tool

Description

find_element_by_location

Find code elements by source location

get_location_context

Get context around a source location

generate_function_imports

Generate import statements for functions

šŸ”¬ Enhanced Analysis (3 tools)

Tool

Description

pattern_match_code

Advanced pattern matching for code structures

analyze_cross_module_dependencies

Comprehensive dependency analysis

enhanced_function_call_graph

Enhanced call graphs with advanced options

šŸ” Example Queries

Basic Analysis

# Search for validation functions search_functions(pattern="validation", limit=10) # Get details about main functions get_function_details(function_name="main") # Find most called functions get_most_called_functions(limit=20) # List modules in a specific area list_modules(limit=50)

Advanced Analysis

# Get function call hierarchy get_function_call_graph(function_name="processData", depth=3) # Analyze type dependencies get_type_dependencies(type_name="User", include_dependents=true) # Find cross-module function calls find_cross_module_calls(source_module="Services", target_module="Database") # Complex JSON query execute_advanced_query({ "type": "function", "conditions": [ {"field": "name", "operator": "like", "value": "%Handler%"} ], "limit": 50 })

Architectural Analysis

# Module dependency analysis get_module_dependencies(module_name="Core.Services", include_dependents=true) # Import relationship graph get_import_graph(root_module="Main", depth=3) # Complexity analysis analyze_function_complexity(module_name="BusinessLogic", min_complexity=5) # Comprehensive statistics get_code_statistics(include_details=true)

āš™ļø Configuration

Environment Variables (.env)

# Database DB_USER=postgres DB_PASSWORD=postgres DB_HOST=localhost DB_PORT=5432 DB_NAME=code_as_data # FDEP Data Source FDEP_PATH=/path/to/your/fdep/output # Logging LOG_LEVEL=INFO

Spider Plugin Integration

For Haskell projects using GHC 9.2.8:

  1. Add Spider flake input

  2. Configure cabal with fdep and fieldInspector plugins

  3. Run socket server during build

  4. Generate FDEP output for analysis

Tool Distribution

  • šŸ“ Module Analysis: 7 tools

  • āš” Function Analysis: 8 tools

  • šŸ—ļø Type System: 6 tools

  • šŸ“š Class Analysis: 3 tools

  • šŸ“¦ Import Analysis: 4 tools

  • šŸ” Advanced Queries: 4 tools

  • šŸŽÆ Pattern Analysis: 5 tools

  • šŸ“ Source Location: 3 tools

  • šŸ”¬ Enhanced Analysis: 3 tools

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