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Codesurface

by Codeturionversion 0.8.0i★ –iRuns on your computer
Registry nameio.github.Codeturion/codesurface

Install

Overview

Description from the maker (original English)

Indexes your codebase's public API and serves it via compact MCP tool responses.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Developer tools

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • The registry lists no key to fill in.

You need

  • PyPIPython’s uv installed (for the uvx command)

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "codesurface": {
      "command": "uvx",
      "args": [
        "codesurface"
      ]
    }
  }
}

Run this in your terminal

claude mcp add codesurface -- uvx codesurface

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "codesurface": {
      "command": "uvx",
      "args": [
        "codesurface"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "codesurface": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "codesurface"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 6, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account Codeturion, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Developer toolsi

  • More stars than 0% of the other 1384 servers in this category
  • Published to the registry more recently than 16% of the other 1384 servers in this category
  • Basic checks equal to or better than 100% of the other 1384 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Codesurface safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.8.0) reached the registry 6 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.

What can I use instead?

In the same category: GitHub, Desktop Commander, Cloudflare MCP

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

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by github

GitHub’s official server lets AI read and manage code, issues and pull requests in your account. Use GitHub’s hosted version or run it locally with Docker.

Computer or cloud★ 34,245MITUpdated 3 days ago
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Desktop Commander

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Cloudflare MCP

by cloudflare

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Runs in the cloud★ 4,446Apache-2.0Updated 14 months ago
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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

codesurface

MCP server that indexes your codebase's public API at startup and serves it via compact tool responses, saving tokens vs reading source files.

Parses source files, extracts public classes/methods/properties/fields/events, and serves them through 5 MCP tools. Works with Claude Code, Cursor, Windsurf, or any MCP-compatible AI tool.

Supported languages: C# (.cs), C++ headers (.h, .hpp, .hxx, .h++), Go (.go), Java (.java), Python (.py), TypeScript/JavaScript (.ts, .tsx, .js, .jsx)

Quick Start

Add to your .mcp.json:

{

"mcpServers": { "codesurface": { "command": "uvx", "args": ["codesurface", "--project", "/path/to/your/src"] } } }

Point --project at any directory containing supported source files (a Unity Assets/Scripts folder, a Spring Boot project, a .NET src/ tree, a Node.js/React project, a Python package, etc.). Languages are auto-detected.

Restart your AI tool and ask: *"What methods does MyService have?"*

CLAUDE.md Snippet

Add this to your project's CLAUDE.md (or equivalent instructions file). This step is important. Without it, the AI has the tools but won't know when to reach for them.

## Codebase API Lookup (codesurface MCP)

Use codesurface MCP tools BEFORE Grep, Glob, Read, or Task (subagents) for any class/method/field lookup. This applies to you AND any subagents you spawn.

ToolUse whenExample
searchFind APIs by keywordsearch("MergeService")
get_signatureNeed exact signatureget_signature("TryMerge")
get_classSee all members on a classget_class("BlastBoardModel")
get_statsCodebase overviewget_stats()

Every result includes file path + line numbers. Use them for targeted reads:

  • File: Service.cs:32 → Read("Service.cs", offset=32, limit=15)
  • File: Converter.java:504-506 → Read("Converter.java", offset=504, limit=10)

Never read a full file when you have a line number. Only fall back to Grep/Read for implementation details (method bodies, control flow).

Tools

ToolPurposeExample
searchFind APIs by keyword"MergeService", "BlastBoard", "GridCoord"
get_signatureExact signature by name or FQN"TryMerge", "CampGame.Services.IMergeService.TryMerge"
get_classFull class reference card with all public members"BlastBoardModel" → all methods/fields/properties
get_statsOverview of indexed codebaseFile count, record counts, namespace breakdown
reindexIncremental index update (mtime-based)Only re-parses changed/new/deleted files. Also runs automatically on query misses

search, get_signature, and get_class accept two optional filters:

  • file_path: scope results to a directory prefix or exact file (e.g. "src/services/" or "src/services/MergeService.ts")
  • include_tests: include test files in results (default false). Detects __tests__/, tests/, test/, *.test.*, *.spec.*, *_test.*, test_*

Tested On

ProjectLanguageFilesRecordsTime
vscodeTypeScript6,61188,2939.3s
PaperJava2,90933,9732.3s
client-goGo2192,7600.4s
langchainPython1,88012,4181.1s
pydanticPython3659,6480.3s
guavaJava8918,3772.4s
immichTypeScript9197,9570.6s
fastapiPython8815,7130.5s
ant-designTypeScript2,9475,4520.9s
difyTypeScript4,9035,0381.9s
crawlee-pythonPython3862,4730.3s
flaskPython63872<0.1s
cobraGo15249<0.1s
ginGo41574<0.1s
Unity game (private)C#1291,0180.1s

Line Numbers for Targeted Reads

Every record includes line_start and line_end (1-indexed). Multi-line declarations span the full signature:

[METHOD] com.google.common.base.Converter.from

Signature: static Converter from(Function<...> forward, Function<...> backward) File: Converter.java:504-506 ← multi-line signature

[METHOD] server.AlbumController.createAlbum Signature: createAlbum(@Auth() auth: AuthDto, @Body() dto: CreateAlbumDto) File: album.controller.ts:46 ← single-line

This lets AI agents do targeted reads instead of reading full files:

# Instead of reading the entire 600-line file:

Read("Converter.java") # 600 lines, ~12k tokens

Read just the method + context:

Read("Converter.java", offset=504, limit=10) # 10 lines, ~200 tokens

Benchmarks

Measured across 5 real-world projects in 5 languages, each using a 10-step cross-cutting research workflow.

LanguageProjectFilesRecordsMCPSkilledNaiveMCP vs Skilled
C#Unity game1291,0341,0214,45311,82577% fewer
TypeScriptimmich6948,3441,4514,50014,55068% fewer
Javaguava8918,3771,8514,20026,70056% fewer
Gogin385341,7912,77015,30035% fewer
Pythoncodesurface9407532,00010,40062% fewer

Even with follow-up reads for implementation detail, the hybrid MCP + targeted Read approach uses 44% fewer tokens than a skilled Grep+Read agent and 87% fewer than a naive agent:

Per-question breakdown

See workflow-benchmark.md for the full step-by-step analysis across all languages.

Filtering What Gets Indexed

By default, codesurface skips common vendored, build, and VCS directories: node_modules, vendor, bin, obj, dist, build, target, .git, .venv, __pycache__, and a few dozen others. Git worktrees and submodules are also skipped.

To exclude additional paths:

Project-level (committed): create a .codesurfaceignore file at your project root with one glob per line.

generated/**

docs/ /*.pb.go

Per-instance (CLI): pass --exclude with comma-separated globs.

{

"command": "uvx", "args": ["codesurface", "--project", "src", "--exclude", "generated/,vendor/"] }

Other indexing flags:

  • --include-submodules: index git submodules (skipped by default)
  • --language : pin to a single parser (e.g. --language cpp) instead of auto-detecting

Multiple Projects

Each --project flag indexes one directory. To index multiple codebases, run separate instances with different server names:

{

"mcpServers": { "codesurface-backend": { "command": "uvx", "args": ["codesurface", "--project", "/path/to/backend/src"] }, "codesurface-frontend": { "command": "uvx", "args": ["codesurface", "--project", "/path/to/frontend/src"] } } }

Each instance gets its own in-memory index and tools. The AI agent sees both and can query across projects.

Setup Details

Alternative installation methods

Using pip install:

pip install codesurface
{

"mcpServers": { "codesurface": { "command": "codesurface", "args": ["--project", "/path/to/your/src"] } } }

Project structure

codesurface/

├── src/codesurface/ │ ├── server.py # MCP server with 5 tools │ ├── db.py # SQLite + FTS5 database layer │ ├── filters.py # PathFilter (default exclusions, .codesurfaceignore, --exclude) │ └── parsers/ │ ├── base.py # BaseParser ABC │ ├── cpp.py # C++ header parser │ ├── csharp.py # C# parser │ ├── go.py # Go parser │ ├── java.py # Java parser │ ├── python_parser.py # Python parser │ └── typescript.py # TypeScript/JavaScript parser ├── pyproject.toml └── README.md

Troubleshooting

"No codebase indexed"

  • Ensure --project points to a directory containing supported source files (.cs, .h, .hpp, .go, .java, .py, .ts, .tsx, .js, .jsx)
  • The server indexes at startup. Check stderr for [codesurface] scanning N files... and [codesurface] done: lines

Server won't start

  • Check Python version: python --version (needs 3.10+)
  • Check mcp[cli] is installed: pip install mcp[cli]

Stale results after editing source files

  • The index auto-refreshes on query misses. If you add a new class and query it, the server reindexes and retries automatically
  • You can also call reindex() manually to force an incremental update

Contact

fuatcankoseoglu@gmail.com

License

MIT

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