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FDEP MCP Server

FDEP MCP Server

by juspay
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Python
Hybrid

get_import_graph

Visualize module import relationships in Haskell codebases to analyze dependencies and understand code structure through interactive graphs.

Instructions

Generate module import relationship graph

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_import_graph"
  }
}

Input Schema

NameRequiredDescriptionDefault
root_moduleNoRoot module to start graph from (optional)
depthNoMaximum depth to traverse
include_externalNoInclude external package imports
limitNoMaximum number of nodes in graph

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It mentions 'generate' and 'graph' but doesn't disclose behavioral traits such as output format (e.g., visual graph, JSON data), performance considerations, error handling, or whether it's read-only or has side effects. For a tool with 4 parameters and no annotations, this is a significant gap in transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence with zero waste. It's front-loaded with the core purpose and appropriately sized for the tool's complexity. Every word earns its place without redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 4 parameters, no annotations, and no output schema, the description is incomplete. It doesn't address what the output looks like (e.g., graph format), how to interpret results, or any limitations (e.g., graph size constraints implied by 'limit' parameter). For a tool generating visualizations or complex data, more context is needed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all 4 parameters with descriptions and defaults. The description adds no additional meaning beyond what's in the schema (e.g., it doesn't explain how parameters interact or provide examples). Baseline 3 is appropriate when schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Generate module import relationship graph' clearly states the action (generate) and resource (module import relationship graph). It distinguishes from siblings like 'analyze_imports' or 'get_module_dependencies' by specifying a graph output rather than analysis or dependency listing. However, it doesn't explicitly differentiate from 'build_type_dependency_graph' or 'enhanced_function_call_graph' which might produce similar visualizations.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. With many sibling tools related to imports, dependencies, and graphs (e.g., 'analyze_imports', 'get_module_dependencies', 'build_type_dependency_graph'), there is no indication of specific use cases, prerequisites, or comparisons. Usage is implied by the name but not explicitly stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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