Myopic MCP Server

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.

⚠️ Alpha / 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. Follow along, open issues, pitch in. Don't wire it into a critical workflow just yet.

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Why

Most AI code review looks at the diff in isolation. But the bugs that matter live in what the diff 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 MCP server that feeds your AI client (Claude, Cursor, …) the structured context to review like someone who actually knows the codebase:

• 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.

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Tools

Everything below works today unless marked planned.

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

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):

Optional semantic layer (myopic[semantic]) — index_repo, code_search, and the semantic half of mr_review_context. See below.

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

See ROADMAP.md for what's next.

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Install

pipx installs myopic isolated and on your PATH:

pipx install "myopic[semantic]"     # omit [semantic] for the core-only install

Prefer a plain venv? python3 -m venv ~/.venvs/myopic && ~/.venvs/myopic/bin/pip install "myopic[semantic]", 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 <you>
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

Point any MCP client — Claude Code, Cursor, Claude Desktop — 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.

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Optional: semantic search (myopic[semantic])

For "is this consistent with the rest of the codebase?" — duplication, convention drift, similar patterns — enable the semantic layer. It's opt-in so the base install stays lean (no torch, no heavyweight vector DB).

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. pip install "myopic[semantic]" — adds lancedb + httpx.
2. Ollama running (default localhost:11434, or set MYOPIC_OLLAMA_URL).
3. The embedding model pulled: ollama pull unclemusclez/jina-embeddings-v2-base-code.

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

Embeddings are stored in an embedded LanceDB index with hybrid (vector + full-text) search. index_repo indexes a checked-out repo and mr_review_context enriches each changed symbol with semantically similar code. Without the extra, mr_review_context still returns the structural (graph) signal.

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 HEAD), or built on a different model — freshness is keyed to the git commit it was indexed from, not wall-clock time. 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.

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.

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Configuration reference

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 optional 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]"          # + ".[semantic]" to work on the semantic layer
pytest                           # hermetic — no network, Ollama, or lancedb needed

License

MIT © Suraj Goyal

mcp-name: io.github.SurajKGoyal/myopic