GraphPulse C++

Analyzes C++ codebases via AST parsing to build comprehensive, queryable dependency graphs for AI agents.

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What it can do

  • Analyze Codebase: Ingest a C++ codebase and build its dependency graph. This tool does NOT accept 'code_content'. Provide exactly ONE of: repo_url, raw_files, or directory_path. - repo_url: an HTTPS G
  • Get File Functions: List all functions defined in a specific source file. Use the relative path exactly as returned in the analyze_codebase output (e.g., 'src/engine.cpp' or 'main.cpp'). Args: filepat
  • Get File Coupling: Generate a report showing which files depend on which other files. Aggregates cross-file function calls into a per-file-pair summary (e.g., 'src/main.cpp -> src/utils.cpp (3 calls)'

What data it sees

Do you need an account

No: the server works without sign-in

Analyzes C++ codebases via AST parsing to build comprehensive, queryable dependency graphs for AI agents. Maps complex function relationships to identify upstream callers, circular dependencies, and orphan code. Includes GitHub repo ingestion and token-safe Mermaid.js visual exports to guide safe code refactoring.

How to connect

How to connect GraphPulse C++ to Claude

The server address to paste into Claude settings:

https://legacy-mcp-analyzer--labsofuniverse.run.tools

  1. Open Claude (claude.ai or the desktop app).
  2. Go to Settings → Connectors.
  3. Click Add custom connector.
  4. Paste the server address copied below into Remote MCP server URL and click Add.
  5. In a chat, click + → Connectors and switch the new connector on.

Custom connectors are available on Free, Pro, Max, Team and Enterprise plans (Free is limited to one). On Team and Enterprise an organization Owner adds the connector first under Organization settings → Connectors.

Authorization

After you click Add, a sign-in window for the service opens. Sign in with your own account and approve access. Claude never sees your password.

How to connect GraphPulse C++ to ChatGPT

The server address to paste into ChatGPT settings:

https://legacy-mcp-analyzer--labsofuniverse.run.tools

  1. Open ChatGPT in a browser (chatgpt.com). A Plus, Pro, Business, Enterprise or Edu plan is required.
  2. Turn on developer mode once: Settings → Apps → Advanced settings → Developer mode.
  3. Open Settings → Connectors and click Create.
  4. Fill in the form: Name (anything), Description (one line about what the service does), MCP server URL (copy it below).
  5. Under Authentication choose OAuth if the service requires sign-in, otherwise None. Click Create.
  6. In a new chat open + → Apps/Connectors and enable the connector.

OpenAI has renamed this section before (Connectors → Apps/Plugins). If the label differs, search settings for "developer mode". On Business/Enterprise workspaces an admin must allow custom connectors first.

Authorization

On first use ChatGPT opens the service's sign-in window. Sign in and approve access.

How to connect GraphPulse C++ to Cursor

The server address to paste into Cursor settings:

https://legacy-mcp-analyzer--labsofuniverse.run.tools

Fastest: click Open in Cursor below and confirm the prompt.

Manually:

  1. In Cursor open Settings → Cursor Settings → MCP and click Add new global MCP server.
  2. Paste the JSON copied below into ~/.cursor/mcp.json (per project: .cursor/mcp.json in the repo root).
  3. Save the file. The server appears in the MCP list; authorize it there if asked.

Authorization

If the service needs sign-in, an authorize button appears next to the server in the MCP list.

Server tool list (8)

Raw names from tools/list. Only developers need these.

analyze_codebase Ingest a C++ codebase and build its dependency graph. This tool does NOT accept 'code_content'. Provide exactly ONE of: repo_url, raw_files, or directory_path. - repo_url: an HTTPS GitHub URL (e.g. 'https://github.com/user/repo'). Optionally add patch_content (a unified diff string) to overlay uncommitted changes on the cloned repo. - raw_files: for hobby projects or small codebases NOT hosted on GitHub. The user pastes their C++ code directly and you wrap each file into a JSON array of objects with 'filename' and 'content' keys. Example: [ {"filename": "main.cpp", "content": "void main() { helper(); }"}, {"filename": "utils.cpp", "content": "void helper() {}"} ] - directory_path: absolute local filesystem path (local mode only; rejected when the server runs in cloud mode). Args: repo_url: HTTPS URL of a git repository to clone. patch_content: Unified diff to apply after cloning repo_url. raw_files: List of dicts [{"filename": str, "content": str}]. Use this when the user shares code snippets directly and does not have a git repository. directory_path: Local path to scan (local mode only). Returns: Status message with file count and function count.
get_file_functions List all functions defined in a specific source file. Use the relative path exactly as returned in the analyze_codebase output (e.g., 'src/engine.cpp' or 'main.cpp'). Args: filepath: Relative path of the source file within the analyzed workspace. Returns: A newline-separated list of function names, or no-match message.
get_file_coupling Generate a report showing which files depend on which other files. Aggregates cross-file function calls into a per-file-pair summary (e.g., 'src/main.cpp -> src/utils.cpp (3 calls)'). Returns: A formatted coupling report, or a message if no cross-file deps exist.
get_callers List upstream functions that call the given function. Args: function_name: Exact name of the function (e.g., 'calculate_interest'). Returns: Comma-separated list of caller function names.
get_callees List downstream functions that are called by the given function. Args: function_name: Exact name of the function (e.g., 'process_client'). Returns: Comma-separated list of callee function names.
detect_cycles Detect circular dependencies in the current call graph. Returns: Formatted list of cycles, or a message if none found.
get_orphan_functions Identify functions that are defined but never called by any other function. Returns: Comma-separated list of orphan function names.
generate_mermaid_graph Generate a Mermaid.js dependency diagram and return it as a markdown string. The AI can render this diagram inline in the chat. For large graphs, use focus_node and max_depth to keep the output token-efficient. Args: focus_node: Optional function name to centre the graph on. max_depth: Max hops from focus_node (default 2). Returns: A Mermaid-fenced markdown string for inline rendering.