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Grafyx MCP server

by bilal07karadeniz·io.github.bilal07karadeniz/grafyx·v0.2.4·4 stars
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Real-time codebase graph for AI assistants: call graphs, dependencies, symbol lookup.

B80/100grade B
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Safety scan
B80/100

full report

Adoption
Growing

4 stars42 downloads/wk

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Grafyx tools (15)

write = sends, deletes, buys or posts

Read from the package source without running it. The installed server may list more.

  • _is_project_dir

    Check if a directory looks like a project root.

  • find_related_code

    Find functions, classes, and files related to a natural language description.

  • find_related_files

    Find files related to a natural language description by scoring symbols inside them.

  • get_call_graph

    Get the call graph for a function: what it calls and what calls it, recursively up to the specified depth.

  • get_class_context

    Get comprehensive context for a class: methods, properties, inheritance chain, and usages throughout the codebase.

  • get_conventions

    Detect and report coding conventions used in this codebase.

  • get_dependency_graph

    Get the dependency graph for a symbol: what it depends ON and what depends on IT, up to the specified depth.

  • get_file_context

    Get comprehensive context for a file: functions, classes, imports, and relationships to other files.

  • get_function_context

    Get comprehensive context for a function: signature, parameters, callers, callees, dependencies, and docstring.

  • get_module_context

    Get an overview of all symbols in a directory/package.

  • get_project_skeleton

    Get the full project structure with file tree and statistics.

  • get_subclasses

    Find all classes that extend a given class, recursively.

  • get_unused_symbols

    Find functions and classes with zero inbound references (dead code detection).

  • refresh_graph

    Bring the codebase graph up to date with the code on disk.

  • set_project

    Set or change the project directory that Grafyx analyzes.

Public scan report

scanner v0.1.9 · 2026-09-24 · same rubric, same numbers if you re-run it

1 medium
  • Code scan80 source files scanned20/25
  • –Live reliabilityno gateway calls yet and no remote to proben/a
  • –Tool poisoningtools not inspected (local package is not executed); not countedn/a
  • Auth qualitylocal package, no credentials required12/15
  • Maintenancelast push 50 days ago12/15
  • Maintainer identityregistry namespace matches repository owner; GitHub account older than a year8/10

Findings (1)

  • mediumeval / new Function usedexec.eval
    grafyx_mcp-0.2.4/ml/caller_disambiguator/train.py: …───────────────────────── model.eval() val_loss = 0.0 val_cor…
Overall 80/100. Components that don't apply are left out of the denominator. Any critical finding is an F.RubricAppeal a findingJSON

How Grafyx compares

Against every graded MCP server, from our own scans and uptime checks. Updated after each scan run.

Safety score
80/100
higher than 60% of 48,255 servers
Tools
15
the typical server has 7
Tools that change things
0%
typical: 0%. Fewer write tools means less an agent can break
GitHub stars
4
more than 82% of 28,688 servers
Downloads a week
42
more than 34% of 12,191 servers with a package

What its tools let an agent do: 14 read · 1 change

Install Grafyx in Claude Code, Cursor or VS Code

claude mcp add grafyx -- uvx grafyx-mcp
Add to Cursor

What the publisher says

From the Grafyx repository's README, as published. We do not edit it. Read it on GitHub

Grafyx

<!-- mcp-name: io.github.bilal07karadeniz/grafyx -->

Real-time codebase understanding for AI coding assistants.

What is Grafyx?

AI coding tools read raw files with zero architectural understanding -- they don't know what calls what, which classes inherit from where, or how your modules connect. Grafyx fixes this by parsing your entire codebase into a full relationship graph using Graph-sitter (built on tree-sitter), then exposing that graph to any AI assistant through the Model Context Protocol (MCP). Your assistant can trace call chains, map dependencies, find related code by description, detect conventions, and understand your project's architecture -- all in real time, with a file watcher that keeps the graph current as you edit.

Quick Start

Claude Code

# Zero-install (recommended)
claude mcp add --scope user grafyx -- uvx --from grafyx-mcp grafyx

# Or install with pip first
pip install grafyx-mcp
claude mcp add --scope user grafyx -- grafyx

Cursor / Windsurf / Cline

Add to your MCP config file:

  • Cursor: .cursor/mcp.json (project) or ~/.cursor/mcp.json (global)
  • Windsurf: ~/.codeium/windsurf/mcp_config.json
  • Cline: Cline MCP settings in VS Code
{
  "mcpServers": {
    "grafyx": {
      "command": "uvx",
      "args": ["--from", "grafyx-mcp", "grafyx"]
    }
  }
}

VS Code (GitHub Copilot)

Add to .vscode/mcp.json:

{
  "servers": {
    "grafyx": {
      "command": "uvx",
      "args": ["--from", "grafyx-mcp", "grafyx"]
    }
  }
}

Using pip instead of uvx? Replace the command with: "command": "grafyx" (no args needed).

Available Tools

How It Works

Shortened. The full README is on GitHub.

Nothing above is checked by us. What we check is on the safety report.

Grafyx: common questions

Is Grafyx MCP server safe?
Mostly: it is graded B (80/100). Read the Grafyx safety report
How do I install Grafyx?
It runs on your machine. Copy the Claude Code, Cursor, VS Code or Claude Desktop config from the install section.
Does Grafyx need an API key?
Not as far as the registry entry and our scan can tell: no credentials are declared or required.
Is Grafyx maintained?
The last commit was 91 days ago (2026-08-05). The latest release is v0.2.4.
What can I use instead of Grafyx?
Servers from other publishers that do the same job: Codebase Memory MCP server.
How does Grafyx compare with other MCP servers?
safety score 80/100 (higher than 60% of 48,255 servers); tools 15 (the typical server has 7); tools that change things 0% (typical: 0%. Fewer write tools means less an agent can break). Full comparison.

Alternatives to Grafyx

Same job from other publishers: the closest match first, then the best rated.

  • Codebase Memory
    Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.
    C