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Myopic

by SurajKGoyalversion 0.1.11i★ –iRuns on your computer
Registry nameio.github.SurajKGoyal/myopic

Install

Overview

Description from the maker (original English)

Code-review MCP: review a GitLab MR or GitHub PR against the whole codebase, not just the diff.

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": {
    "myopic": {
      "command": "uvx",
      "args": [
        "myopic"
      ]
    }
  }
}

Run this in your terminal

claude mcp add myopic -- uvx myopic

Open in Cursor

Or copy the settings yourself

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

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

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

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 8, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account SurajKGoyal, 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 4924 servers in this category
  • Published to the registry more recently than 40% of the other 4924 servers in this category
  • Basic checks equal to or better than 100% of the other 4924 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 Myopic 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 (0.1.11) reached the registry 2 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

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

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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 5 days 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.

myopic

The code-review MCP with the most ironic name in the registry. It's anything but nearsighted — it reviews your merge request against the *whole* codebase, not just the diff in front of it.

Building in public. Reviews **GitLab merge requests and GitHub pull

requests** — pass either URL. Reads the change, reviews it against the whole

codebase, and can post the review back as inline comments. Issues and PRs welcome.


Why

The bugs that matter rarely live in the diff. They live in what it *doesn't* show: the caller three files away that now breaks, the convention every sibling file follows that this one quietly drops, the helper that already exists so this new one is a duplicate. A reviewer that only reads the patch is myopic.

myopic is an open-source MCP server that gives the AI client you already use (Claude, Cursor, …) the structured context to review like someone who knows the codebase. It runs on your machine — your code never leaves it, there's no per-PR bill, and the review happens in your own agent with your own standards:

  • Read the change precisely — the diff as line-numbered hunks or grouped by function/class, token-safe on any MR size (a 10,000-line diff never overflows the context window).
  • Review it against the whole codebase — who calls the changed code (blast radius), the caller/callee graph, and — optionally — semantically similar code so you catch broken conventions and duplication.

It pairs with amnesic, my MCP server that gives AI persistent memory of SQL databases.


Tools

Everything below works today unless marked planned.

Read the merge request (token-safe by construction):

ToolWhat it does
mr_review_statusMR metadata + every discussion thread + resolved/unresolved, in one call
mr_changed_filesa content-free manifest of changed files (paths, stats, noise flags) — no diff content, so it stays small even on a huge MR
mr_diff_sectionsthe diff grouped by function/class (AST-aware), budget-bounded
mr_diff_linesthe diff as line-numbered hunks — exact positions for inline comments — budget-bounded

On a large MR, the diff tools return a bounded page and list the rest under omitted_files / truncated instead of failing; lockfiles, generated code, and binaries are listed but not expanded. Fetch the rest with files_filter.

Review against the whole codebase (point at a local clone):

ToolWhat it does
dependency_impacteverywhere a changed symbol is used — the blast radius (ripgrep + tree-sitter)
trace_call_chainthe caller/callee graph of a symbol
mr_review_contextthe headline — for each changed symbol: its impact (always), plus semantically similar code when the optional layer is enabled

Semantic layer (built in — needs Ollama) — index_repo, code_search, and the semantic half of mr_review_context. See below.

Close the loop — verify, and (on request) comment:

ToolWhat it does
mr_verify_reviewfor each existing review thread, the diff changes near the commented line — did a follow-up commit address it? (read-only)
mr_post_commentsthe one write — post inline comments, one at a time from a queue with exponential backoff (no drafts, no bulk-publish), so partial progress survives and rate limits are respected

See ROADMAP.md for what's next.


Install

pipx installs myopic isolated and on your PATH:

pipx install myopic

Prefer a plain venv? python3 -m venv ~/.venvs/myopic && ~/.venvs/myopic/bin/pip install myopic, then use that binary where the examples say myopic.

Setup

myopic needs a personal access token with api (or read_api) scope. The wizard walks you through it:

myopic init     # prompts for URL + token, verifies, saves both

myopic test # ✓ Authenticated to https://gitlab.com as myopic doctor # health-check config + (if enabled) the semantic layer

The token is saved to ~/.config/myopic/.env (chmod 600) and referenced from the TOML as ${GITLAB_TOKEN} — never in the config file itself. Rotate it with myopic set-secret, or hand-edit via myopic init --template.

GitHub PRs: just pass a PR URL. Set a GITHUB_TOKEN (a PAT with pull-request read access) in your environment or a [github] section in config.toml. For GitHub Enterprise, set [github].url to your host.

Add to your AI client

Claude Code — one command, no config editing:

/plugin marketplace add https://github.com/SurajKGoyal/myopic-marketplace

/plugin install myopic@myopic

Any other MCP client (Cursor, Claude Desktop, …) — point it at the myopic command:

{

"mcpServers": { "myopic": { "command": "myopic" } } }

If your client can't find it on PATH, use the absolute path (pipx installs to ~/.local/bin/myopic).

Configure inline instead of myopic init

Put the token in the env block and skip the config file — myopic reads GITLAB_TOKEN / GITHUB_TOKEN from the environment:

{

"mcpServers": { "myopic": { "command": "myopic", "env": { "GITLAB_TOKEN": "glpat-…", "MYOPIC_AUTO_PULL": "1" } } } }

MYOPIC_AUTO_PULL=1 (optional) pulls a missing embedding model on first use instead of erroring.

Use

Point your AI at a merge request:

"Review this MR: https://gitlab.com/group/project/-/merge_requests/42"

A good flow the client can follow: mr_changed_files to see the shape → mr_diff_sections (large MRs) or mr_diff_lines to read the change → then, with a local clone checked out, dependency_impact / trace_call_chain (or mr_review_context) on the risky changed symbols to review against everything that depends on them.

The graph tools analyze whatever is checked out at root, so check out the MR's branch first — otherwise you're reviewing the target branch, and the MR's new code isn't there. myopic worktree checks out the MR head in a throwaway worktree (your main checkout untouched) and prints the path to use as root. mr_review_context also warns when root doesn't hold the MR's head.

Fork PRs work too: a fork's branch doesn't exist on your remote, so GitHub PR heads are fetched via refs/pull/N/head, which the base repository serves whether the PR came from a branch or a fork.


Semantic search (built in — needs Ollama)

For "is this consistent with the rest of the codebase?" — duplication, convention drift, similar patterns — the semantic layer covers it. It's bundled in the base install (lancedb + httpx); the only external requirement is a running Ollama.

Embeddings come from a local Ollama server you run — your code never leaves your machine. myopic talks to Ollama over HTTP; it does not bundle or launch it. The one-time prerequisites:

  1. Ollama running (default localhost:11434, or set MYOPIC_OLLAMA_URL).
  2. The embedding model pulled: ollama pull unclemusclez/jina-embeddings-v2-base-code.

myopic doctor checks both and offers to pull the model for you.

Embeddings are stored in an embedded LanceDB index with hybrid (vector + full-text) search, and mr_review_context enriches each changed symbol with semantically similar code. You don't run `index_repo` by hand — it indexes the repo on the first review and refreshes when stale, automatically (disable with MYOPIC_AUTO_INDEX=0; the graph pass needs no index and always runs). index_repo / myopic index remain for explicit/cron use.

Indexing is incremental and freshness-aware. The first index_repo is a full build; after that only files whose content changed are re-embedded, so refreshing is cheap. index_status(root) reports whether the index is fresh, stale (with how many commits behind main), or built on a different model — freshness is measured against the repo's main line, not the current checkout, so reviewing a feature branch never marks the index stale; only main actually moving does. code_search and mr_review_context carry that status so a stale index never silently degrades a review; the AI is told to offer a refresh when it's stale.

The index is per repository, not per checkout — a myopic worktree at an MR's head shares its clone's index, so reviewing a new branch never rebuilds it; only the files that branch changed get re-embedded.

A *separate clone* of the same repo does get its own index, and a repo you delete leaves one behind. Indexing drops such dead copies automatically; to review and reclaim them yourself:

myopic prune            # dry-run: what's stale, and how much it's costing

myopic prune --apply # delete them

A second clone you still use keeps its index — only unreachable ones are removed.

myopic is a stdio server (no background process), so there's no built-in scheduler — but myopic index /path/to/repo is the hook for one. Point cron or launchd at it to keep an index fresh out of band:

# refresh hourly (incremental — usually seconds)

0 * * * * myopic index /path/to/repo

Override the model/endpoint with MYOPIC_EMBED_MODEL / MYOPIC_OLLAMA_URL.


Configuration reference

SourceKeyNotes
config.toml[gitlab].urlGitLab base URL (default https://gitlab.com)
config.toml[gitlab].tokenuse ${GITLAB_TOKEN} — don't hardcode
.env (next to config)GITLAB_TOKENthe actual token value (chmod 600)
env varMYOPIC_GITLAB_URL / GITLAB_URLfallback if no TOML
env varMYOPIC_GITLAB_TOKEN / GITLAB_TOKENfallback if no TOML
env varMYOPIC_CONFIG / MYOPIC_HOMEoverride the config file / directory
env varMYOPIC_EMBED_MODEL / MYOPIC_OLLAMA_URLsemantic layer model + endpoint
env varMYOPIC_AUTO_INDEX0 to disable auto-indexing during review (default on)
env varMYOPIC_AUTO_PULL1 to auto-pull a missing embedding model on first use (default off)

Security

  • One explicit write, everything else read-only. Only mr_post_comments mutates a review, and only when you ask for it — every other tool just reads MR and repo data. The write is never speculative.
  • Your token stays local. It lives in your .env / environment and is sent only to your configured GitLab instance — never to any third party.
  • Auth errors are scrubbed so your token never leaks into error messages.
  • The semantic layer runs entirely locally (your Ollama, an on-disk index) — your code is never sent to a third party.

Development

pip install -e ".[dev]"

pytest # hermetic — no network, Ollama, or lancedb needed

License

MIT © Suraj Goyal

mcp-name: io.github.SurajKGoyal/myopic

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