Codebase Exploration via Knowledge Graph

Use graph tools for structural code questions. They return precise results in ~500 tokens vs ~80K for grep-based exploration.

Workflow

Step 1: Check if project is indexed

list_projects

If the project is missing from the list:

index_repository(repo_path="/path/to/project")

If already indexed, skip — auto-sync keeps the graph fresh.

Step 2: Get a structural overview

get_graph_schema

This returns node label counts (functions, classes, routes, etc.), edge type counts, and relationship patterns. Use it to understand what's in the graph before querying.

Step 3: Find specific code elements

Find functions by name pattern:

search_graph(label="Function", name_pattern=".*Handler.*")

Find classes:

search_graph(label="Class", name_pattern=".*Service.*")

Find all REST routes:

search_graph(label="Route")

Find modules/packages:

search_graph(label="Module")

Scope to a specific directory:

search_graph(label="Function", qn_pattern=".*services\\.order\\..*")

Step 4: Read source code

After finding a function via search, read its source:

get_code_snippet(qualified_name="project.path.to.FunctionName")

Step 5: Understand structure

For file/directory exploration within the indexed project:

list_directory(path="src/services")

When to Use Grep Instead

• Searching for string literals or error messages →

  search_code

  or Grep
• Finding a file by exact name → Glob
• The graph doesn't index text content, only structural elements

Key Tips

• Results default to 10 per page. Check

  has_more

  and use

  offset

  to paginate.
• Use

  project

  parameter when multiple repos are indexed.
• Route nodes have a

  properties.handler

  field with the actual handler function name.

• exclude_labels

  removes noise (e.g.,

  exclude_labels=["Route"]

  when searching by name pattern).