Skip to main content
Glama
Marshel2727

Mars MCP Backend Analyzer

by Marshel2727

Mars MCP Backend Analyzer

Mars MCP Backend Analyzer is a local, read-only analyzer for Python backend projects. It is built to work well with Codex and other MCP clients by exposing small, focused tools instead of dumping an entire repository into the model context.

The project focus is simple:

  • scan Python backend projects safely

  • build compact project maps and project briefs

  • find files relevant to a user question

  • outline source files before reading them

  • read only specific line ranges when possible

  • provide a planning step before larger analysis work

Why This Exists

Large codebases are expensive to send to an AI model. Mars works as a local indexer and context compressor:

User question
-> mars_plan_task
-> mars_project_brief
-> mars_find_relevant_files
-> mars_outline_file / mars_search_code
-> mars_read_lines
-> final answer from Codex or another AI client

This keeps token usage lower and makes the analysis process easier to monitor.

Related MCP server: LocalNest MCP

Features

  • Read-only MCP server over stdio

  • CLI fallback for local use

  • Backend-focused file scanner

  • Ignore rules for .env, virtual environments, caches, build output, binary files, and common dependency folders

  • Project brief and project map tools

  • Relevant file selection

  • File outline and line-range reading

  • Deterministic task planner

  • Optional Ollama agent mode

MCP Tools

Mars exposes these tools:

  • mars_plan_task

  • mars_project_brief

  • mars_find_relevant_files

  • mars_project_map

  • mars_backend_strategy_files

  • mars_scan_project

  • mars_search_code

  • mars_outline_file

  • mars_read_lines

  • mars_read_file

  • mars_analyze_backend

Prefer the low-token flow:

mars_plan_task
-> mars_project_brief
-> mars_find_relevant_files
-> mars_outline_file or mars_search_code
-> mars_read_lines
-> final answer

Use mars_read_file only when exact full-file context is required.

Install

python -m venv venv
venv\Scripts\python.exe -m pip install -r requirements.txt

On Git Bash or Linux-like shells:

python -m venv venv
source venv/Scripts/activate
python -m pip install -r requirements.txt

CLI Usage

Show a compact project brief:

./mars project-brief "C:\path\to\backend"

Create a plan before analysis:

./mars plan "C:\path\to\backend" "berikan alur kerja backend ini" --depth normal

Find relevant files:

./mars relevant-files "C:\path\to\backend" "debug error login"

Read only a small range:

./mars read-lines "C:\path\to\backend" app/main.py 1 80

Run the optional Ollama agent:

./mars agent "C:\path\to\backend" "analisis project ini" --depth normal

Codex MCP Config

Example Codex config:

[mcp_servers.mars]
command = "C:\\Windows\\System32\\WindowsPowerShell\\v1.0\\powershell.exe"
args = [
  "-NoProfile",
  "-ExecutionPolicy",
  "Bypass",
  "-File",
  "C:\\project AI\\Mars-MCP-backend-analyzer\\mars-mcp.ps1"
]
cwd = "C:\\project AI\\Mars-MCP-backend-analyzer"

[mcp_servers.mars.env]
MARS_MCP_PYTHON = "C:\\path\\to\\python.exe"

After changing the MCP server code or tool schema, restart Codex or reconnect the MCP server so the updated tools are loaded.

Token Benchmark

The exact token count depends on project size and the question, but the expected shape is:

Approach

Context sent to model

Expected token use

Notes

Without Mars MCP

Many full files copied manually

High

Simple but wasteful for large projects

With mars_project_map

Compact file list and symbols

Medium

Good for overview questions

With mars_project_brief + mars_find_relevant_files + mars_read_lines

Brief, selected files, and small line ranges

Low

Best default for Codex workflows

See docs/token-benchmark.md for the benchmark template.

Testing

Run the test suite:

pytest

Current coverage focuses on the safety-critical local tools:

  • path traversal protection

  • .env blocking

  • ignored directory scanning

  • line read limits

  • search line numbers

Safety Model

Mars is intended to be read-only. The MCP tools are designed to inspect a local project, not modify it. Keep write operations in the AI/client layer explicit and separate from Mars.

Documentation

F
license - not found
-
quality - not tested
C
maintenance

Maintenance

Maintainers
Response time
Release cycle
Releases (12mo)
Commit activity

Resources

Unclaimed servers have limited discoverability.

Looking for Admin?

If you are the server author, to access and configure the admin panel.

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Marshel2727/Mars-MCP-backend-analyzer'

If you have feedback or need assistance with the MCP directory API, please join our Discord server