MCP server · Developer tools
Big Indexer MCP server
by ahmedxuhri
Lets your AI study your codebase's structure and suggest where changes belong.
Big Indexer is a helper for people who work with large codebases and want their AI assistant to understand how the code is put together. It scans your project files and builds a map of which parts behave alike and which parts are tightly connected. If you often ask your AI to add a feature or fix a bug and get suggestions that do not fit your project, this can help.
What is an MCP server? The 30-second version
On its own, your AI can only chat with you. An MCP server is a small helper program that gives your AI a new skill or a connection to something else. This one connects your AI to Big Indexer, which has already looked at your code and built a map of it. Once connected, your AI can ask Big Indexer questions about your code and use the answers in its reply.
What this MCP server does
You first run Big Indexer on your project once, and it writes a couple of map files describing your code. Then you start this MCP server pointing at those files. When you ask your AI something like where a new feature should live, the AI calls Big Indexer through this server. Big Indexer looks up similar code in your project and returns the closest matches, a suggested boundary, and a short checklist. Your AI then uses that to give you a grounded answer instead of a guess.
Click to zoomWhat you can do with it
- Find code in your project that behaves similarly to what you are about to write
- Suggest where a new component boundary should sit before a refactor
- Point out tightly connected parts of your code that may be risky to change
- Give your AI a short checklist to follow when adding a feature
- Ground your AI's suggestions in patterns already used in your repo
Try asking your AI
- “Use twin_context for: Add an endpoint that validates input and saves it to the database. Return the top match, a seam suggestion, and a checklist.”
- “Find code in this repo that behaves like a background job that retries on failure.”
- “Where should the boundary be between the auth code and the user profile code before we refactor?”
- “Which parts of this project are most tightly coupled and risky to change together?”
What it gives back to you
You get answers in the chat, written by your AI but based on what Big Indexer found. Typically that means a short list of similar code units with their file and function names, a suggested boundary or seam, and a small checklist. It does not change your code; it only reads the map files you generated earlier.
Before you start
What you need
- Python installed on your computer
- Big Indexer installed (pip install bigindexer)
- A map file you generate first by running bgi scan on your project
- An AI app that supports MCP servers, like Claude Desktop or Continue
Good to know
It reads your source code to build its map, so be careful about running it on private or sensitive repositories, and remember its suggestions are heuristic, not guaranteed correct.
Install it with your AI
Add Big Indexer MCP server to your AI, no technical skills needed
You don't install anything by hand. You copy one prompt, paste it into an AI that can work on your computer, and it checks, installs and connects the server for you, asking you when it needs something.
Sign in to get the install prompt
Members get a ready-made prompt that lets the Claude desktop app check Big Indexer MCP server, install it and connect it for them, step by step. You don't need any technical skills: you copy, paste and answer a few questions. Your connected AI can also find and install any of the 4,066 MCP servers here for you.
Who it's for
Developers and technical leads working on large or messy codebases who want their AI assistant to respect the project's existing structure.
