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.

🔌 MCP Protocol Compliant | 🏗️ 40+ Analysis Tools | ⚡ Real-time Queries

✨ MCP Server Features

📊 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

🚀 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

🔌 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 + , → Extensions → 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:

Start your MCP client
Look for "fdepAnalyzer" in available tools/servers
Test with a simple query: list_modules(limit=5)
You should see your Haskell modules listed

🛠️ MCP Tools Available (40+ Total)

📁 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

⚡ 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

🏗️ 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

📚 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

📦 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

🔍 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

🎯 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

📍 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

🔬 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

🔍 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)

⚙️ 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:

Add Spider flake input
Configure cabal with fdep and fieldInspector plugins
Run socket server during build
Generate FDEP output for analysis

Tool Distribution

📁 Module Analysis: 7 tools
⚡ Function Analysis: 8 tools
🏗️ Type System: 6 tools
📚 Class Analysis: 3 tools
📦 Import Analysis: 4 tools
🔍 Advanced Queries: 4 tools
🎯 Pattern Analysis: 5 tools
📍 Source Location: 3 tools
🔬 Enhanced Analysis: 3 tools

FDEP MCP Server

🔌 MCP Protocol Compliant | 🏗️ 40+ Analysis Tools | ⚡ Real-time Queries

✨ MCP Server Features

📊 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

🚀 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

🔌 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 + , → Extensions → 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:

Start your MCP client
Look for "fdepAnalyzer" in available tools/servers
Test with a simple query: list_modules(limit=5)
You should see your Haskell modules listed

🛠️ MCP Tools Available (40+ Total)

📁 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

⚡ 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

🏗️ 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

📚 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

📦 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

🔍 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

🎯 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

📍 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

🔬 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

🔍 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)

⚙️ 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:

Add Spider flake input
Configure cabal with fdep and fieldInspector plugins
Run socket server during build
Generate FDEP output for analysis

Tool Distribution

📁 Module Analysis: 7 tools
⚡ Function Analysis: 8 tools
🏗️ Type System: 6 tools
📚 Class Analysis: 3 tools
📦 Import Analysis: 4 tools
🔍 Advanced Queries: 4 tools
🎯 Pattern Analysis: 5 tools
📍 Source Location: 3 tools
🔬 Enhanced Analysis: 3 tools