codecity-mcp
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@codecity-mcp Show me the structure and complexity hotspots of ~/code/my-project"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
codecity-mcp
An MCP server that analyzes a local codebase and exposes its structure, per-file summaries, dependency graph, and complexity hotspots as tools Claude (or any MCP client) can call.
This is the data layer for a larger project: a 3D "code city" - a navigable visualization where a codebase becomes a walkable city (files as buildings, folders as districts, imports as roads) with Claude acting as a guide that explains what you're looking at and helps you actually build a mental model of the codebase, not just stare at a pretty render of it. This repo is the first, standalone piece: it's useful on its own, with or without the 3D viewer, to anyone pointing Claude at an unfamiliar codebase.
Tools
Tool | What it does |
| Returns the folder/file tree of a repo, plus totals (file count, size). Start here to get oriented. |
| Structural summary of one file: line count, function/class count, its imports, and a short excerpt. |
| Resolves relative imports between files into a graph (internal edges) plus a list of external package names. |
| Ranks files by a simple size/complexity heuristic, so you know where to look first. |
Related MCP server: forensic-deepdive
Design notes
Zero analysis dependencies. Repo scanning,
.gitignorehandling, and JS/TS structural analysis (function/class/import counts) are hand-rolled with no parser or ignore-matching library. This is a deliberate tradeoff: regex/heuristic-based analysis instead of a full AST walk, in exchange for a small, auditable dependency footprint (just the MCP SDK and zod). The complexity score is explicitly a heuristic, not real cyclomatic complexity - documented insrc/complexity.ts.JS/TS-aware today, extensible later. Non-JS/TS files still get scanned and line-counted; structural analysis (functions, classes, imports) currently only applies to
.ts/.tsx/.js/.jsx/.mjs/.cjs. Adding another language means adding another analyzer, not touching the MCP layer.Tested without the SDK installed.
test/smoke.tsexercises the scanner/analyzer/graph/complexity logic directly (no MCP SDK or zod import), so the core logic is verified independently of the protocol layer. It runs the tool on its own source as a sanity check.
Setup
npm install
npm run buildRunning it
Standalone smoke test (no MCP client needed)
npm testRuns the analysis logic (scanner, analyzer, dependency graph, complexity ranking) directly, with no MCP SDK involved - points it at this repo's own source and prints what it finds. Useful to sanity-check the core logic in isolation before wiring up a client.
With the MCP Inspector
npm run inspectOpens a browser UI to call each tool manually and see raw responses.
With Claude Desktop or Claude Code
Add to your MCP client config (e.g. claude_desktop_config.json):
{
"mcpServers": {
"codecity": {
"command": "node",
"args": ["/absolute/path/to/codecity-mcp/build/index.js"]
}
}
}Restart the client, then ask it something like: "Use codecity to show me the structure of ~/code/some-project, and tell me which files are the most complex."
Roadmap
Orchestrator layer: a small agent loop that decides what to explain next based on what's already been explored, and quizzes the user to check understanding (not just recall) - the piece that turns this from a static analysis tool into a capability-building guide.
3D city renderer (BabylonJS + React) that consumes
get_repo_structureandget_dependency_graphto render the actual city.Language support beyond JS/TS.
License
MIT
Available Tools
4 toolsget_complexity_hotspotsA
Ranks files by a simple size/complexity heuristic (function count, class count, lines of code) so you know which parts of a codebase are worth looking at first.
Inputs: repoPath (required), limit.
get_dependency_graphA
Builds a dependency graph of the repository by resolving relative imports between files. Returns edges (from -> to) for internal files and a separate list of external package names.
Inputs: repoPath (required).
get_file_summaryA
Returns a structural summary of a single file: line count, function/class count, its imports, and a short excerpt - without needing to read the whole file.
Inputs: filePath (required), repoPath (required).
get_repo_structureA
Returns the folder/file tree of a local repository, plus totals (file count, lines of code). Use this first to get oriented before drilling into individual files.
Inputs: repoPath (required).
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
TDQS
Scored across 4 tools
Each tool addresses a distinct aspect of codebase analysis: structure, file summaries, dependency graph, and complexity hotspots. There is no overlap in their purposes, making selection unambiguous.
All tool names follow a consistent get_<noun> pattern, with clear resource names (repo_structure, file_summary, dependency_graph, complexity_hotspots). The naming is uniform and predictable.
With 4 tools, the set is well-scoped for a code analysis server. Each tool covers a core need and none are redundant, making the count appropriate.
The server covers the main exploration workflows: orienting via structure, inspecting files via summaries, understanding dependencies, and identifying complex areas. Missing full file content retrieval is a minor gap since summaries include excerpts.
Maintenance
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