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PopNx MCPMCP servers for people who use AI · explained in plain words

skimread

by avikchakraborty060-createversion 0.1.1i★ –iRuns on your computer
Registry nameio.github.avikchakraborty060-create/skimread

Install

Overview

Description from the maker (original English)

Lossless context guard for coding agents: command digests, file outlines, line-range reads.

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": {
    "skimread": {
      "command": "uvx",
      "args": [
        "skimread",
        "mcp"
      ]
    }
  }
}

Run this in your terminal

claude mcp add skimread -- uvx skimread mcp

Open in Cursor

Or copy the settings yourself

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

{
  "mcpServers": {
    "skimread": {
      "command": "uvx",
      "args": [
        "skimread",
        "mcp"
      ]
    }
  }
}

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

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 avikchakraborty060-create, 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 5549 servers in this category
  • Published to the registry more recently than 59% of the other 5549 servers in this category
  • Basic checks equal to or better than 100% of the other 5549 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 skimread 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 (0.1.1) reached the registry 19 days 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:↓ Downloads per weeki★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

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.

by githubWidely used★ 34.2KUpdated 5 days ago

Computer or cloud

Desktop Commander

MCP server for terminal commands, file operations, and process management

by wonderwhy-erWidely used↓ 709.6K/wk★ 10.2KUpdated 17 days ago

Runs on your computer

Cloudflare MCP

Cloudflare MCP servers

by cloudflareWidely used★ 4.4KUpdated 14 months ago

Runs in the cloud✓ mcp.cloudflare.com

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.

skimread — skim before you read

A lossless context guard for AI coding agents. Zero dependencies, runs entirely on your machine, MIT licensed. Works with Claude Code out of the box, and with any other agent (Codex, Cursor, Aider, Copilot, your own) through a CLI and an MCP server.

What is it?

When you use an AI coding agent, you pay for every token it reads. Most of that money goes to two things the agent does not actually need:

  1. Reading big files whole. The agent wants one function and reads all 2,000 lines of the file to find it. Next session it does it again.
  2. Reading noisy command output. pytest -v prints 1,500 PASSED lines to tell you about 2 failures. npm install prints 40 deprecation warnings. cargo build lists every crate it compiled.

skimread sits between the agent and those two sources and hands the agent a *skim* first:

  • For files: an outline instead of the file. When the agent is about to read a large file, skimread gives it a map of the file (functions, classes, headings, keys, each with its line range) and says "read only the slice you need". The agent then reads 60 lines instead of 2,000.
  • For commands: a digest instead of the dump. Noisy commands run through skimread. The agent sees the errors, the failing tests, the stack frames in *your* code, and the summary line. The 1,500 PASSED lines are folded into one line that says so.

The key word is lossless. Nothing is thrown away. Every command's full output is kept on your disk, and every digest ends with a handle (skimread show 42, skimread show 42 120-180, skimread show 42 --grep TypeError). Every outline tells the agent exactly which line range to read next. The agent is never stuck and never has to re-run a build to see what it missed.

Why not one of the existing output compressors?

Tools that compress shell output already exist (RTK, token-saver, condense). They share two limits. They cannot touch the agent's own file-reading tool, which is the bigger token sink. And they are lossy: when the compressor drops the one line the agent needed, the agent re-runs the command, and an independent benchmark found that this can cost *more* than not compressing at all. skimread guards file reads too, and keeps everything retrievable.

What it is not
  • Not a cloud service. No network calls, no accounts, no telemetry. ~/.skimread is the whole state.
  • Not an LLM. Everything is deterministic parsing and folding, so it runs in milliseconds and costs nothing.
  • Not a summariser that guesses. It never rewrites a line; it only hides lines it can name and count, and tells you how to get them back.

Numbers

Measured on real tool output (fixtures in tests/fixtures, reproduce with python bench/bench.py). Token counts are estimates (chars / 3.6).

Command outputlinestokens intokens outsaved
pytest -v (1,504 tests, 2 failing)154633,87647399%
vitest --reporter=verbose (579 tests, 3 failing)6537,75169891%
pytest (65 tests, 3 failing, 60 warnings)2943,45149686%
npm install (649 packages, 23 deprecation warnings)411,04820481%
cargo build (37 crates, 3 warnings)6155925455%
go test -v (1 fail, 1 panic)3530113754%
tsc (48 errors in 8 files)481,08762842%
cargo test (1 fail, backtrace)6871348732%
cargo build (2 errors)39408411-1%
vitest (13 files, 3 failing)76613628-2%

The last two rows are the point: when the output is already pure signal (a short build with two errors), skimread leaves it alone. Savings come from noise, never from hiding failures.

File readlinesfull read (tokens)outline (tokens)saved when the agent then reads a 60-line slice
skimread/outline.py5987,64847784%
skimread/formats.py4634,96156976%
skimread/cli.py3684,08635775%

A 4,063-line Go file (net/http/server.go, ~36k tokens) becomes a ~600-token map of structs and methods with line ranges. skimread stats shows what it has saved you so far, in tokens and dollars.

How to use

1. Install (30 seconds)

Needs Python 3.9 or newer, nothing else.

pipx install skimread          # recommended: isolated, on your PATH

or: uv tool install skimread

or, inside any Python environment: pip install skimread

skimread --version

Latest development version straight from GitHub: pipx install git+https://github.com/avikchakraborty060-create/The-top-innovation.

Everything skimread stores lives under ~/.skimread with owner-only permissions and is pruned after 7 days or 300 runs.

2. Claude Code: one command
skimread setup claude            # global: ~/.claude/settings.json

skimread setup claude --project # or per project: .claude/settings.json

Restart Claude Code. That is all. From then on:

  • When Claude tries to Read a file over 400 lines (or 16 KB) without a line range, it gets the outline and the instruction to read a range instead. A ranged read is always allowed. If Claude asks for the same whole file a second time in the session, it gets it, so it is never stuck.
  • When Claude runs a command known to be noisy (npm, pytest, cargo, go, tsc, docker, git diff, find, and about 100 others) the command is rewritten to run through skimread run. Claude sees the digest and the handle. The permission rule Bash( :*) is added so this causes no extra prompts.

This is what Claude sees instead of a 2,014-line file:

skimread: src/server.py is 2,014 lines (~20k tokens). Read only the part you need: call Read again

with offset and limit chosen from this outline. Any Read that sets offset or limit is allowed; ... Outline: 2,014 lines, ~20k tokens (python) 1-38 imports 12 import statements 41-118 class Config 44-58 def init(self, path: str) -> None 61-90 def load(self) -> dict 121-410 class Server(Base) 123-140 def init(self, cfg: Config) 142-229 def handle_request(self, req: Request) -> Response ...

And this is what Claude sees after pytest -v on a suite of 1,504 tests:

$ pytest -v test_many.py  ·  exit 1 in 1.2s

============================= test session starts ============================== (1502 passing/skipped tests hidden) test_many.py::test_some_fail[1] FAILED [ 99%] test_many.py::test_some_fail[3] FAILED [100%] =================================== FAILURES =================================== ______________________________ test_some_fail[1] _______________________________ ... E AssertionError: role mismatch for user 1 E assert 'dev' == 'ops' test_many.py:10: AssertionError =========================== short test summary info ============================ FAILED test_many.py::test_some_fail[1] - AssertionError: role mismatch for user 1 FAILED test_many.py::test_some_fail[3] - AssertionError: role mismatch for user 3 ======================== 2 failed, 1502 passed in 0.98s ======================== [skimread #42: 1546 lines, ~34k tok → 473. Full/slice/search: skimread show 42 [A-B | --grep RE]]

Tuning:

skimread setup claude --wrap all     # route every safe Bash command through skimread

skimread setup claude --wrap off # Read guard only, leave Bash alone skimread setup claude --uninstall # remove the hook and the permission rule skimread config read_threshold_lines 600 # guard only files longer than this (default 400) skimread config budget 4000 # digest size in characters (default 6000) skimread setup print # just print the settings.json snippet to paste yourself

Safety: the Bash wrapper never touches commands that change shell state (cd at the end, export, source), redirect to files, run in the background, look interactive, or are destructive or privileged (rm, sudo, git push, git commit, curl | sh, and so on). Those run exactly as Claude wrote them, under your normal permission rules. A leading cd dir && … is kept outside the wrapper so the working directory still changes.

3. Codex, Cursor, Aider, Copilot, or your own agent

Any agent that can run shell commands can use skimread through the CLI. Put this in the agent's rules file (AGENTS.md, .cursorrules, a system prompt); skimread setup agents prints a ready-made snippet:

skimread outline src/server.py           # map of the file with line ranges

skimread read src/server.py 142-229 # numbered slice skimread run -c "npm test" # digest + handle (shorthand: skimread npm test) skimread show 42 # full stored output skimread show 42 300-360 # slice skimread show 42 --grep "Error" -C 3 # search with context skimread list # recent runs

Agents that speak MCP can use it as a server instead. skimread mcp is a stdio MCP server with tools run, show, outline, read, list; skimread setup mcp prints the config block for mcpServers. Anything on stdin works too: cmd 2>&1 | skimread pipe --cmd "cmd".

4. See what it saved you
skimread stats                 # tokens and dollars saved, all time, by format

skimread stats --price 15 # use your model's input price per million tokens skimread stats --json

How it works

  1. Normalise. ANSI colours and cursor codes are stripped, \r progress bars resolve to their final state, backspaces are applied.
  2. Format-aware reduction. Reducers for pytest, jest/vitest/mocha, cargo, go, npm/yarn/pnpm/bun, pip/uv/poetry, docker, tsc, git diff, and file/listing commands drop only what carries no decision value: PASSED lines, Compiling lines, deprecation warnings (counted), stdlib stack frames. Everything else stays. Unknown tools get the generic path: progress noise removed, exact duplicates counted (line (x5)), runs of near-identical lines folded (… 847 similar lines (159-1005) …).
  3. Scoring and budget. Lines are scored (errors and stack frames high, summaries medium). If the reduced output still exceeds the budget, the head, the tail, and windows around the highest-scored lines are kept; every cut is replaced by … [768 lines omitted (45-812) — skimread show 42 45-812] ….
  4. Spool. The full normalised output is written to ~/.skimread/out/ .txt before the digest is produced, so the handle in the footer always works.
  5. Outline. Python via the ast module (exact signatures and ranges); JS/TS, Go, Rust, Java/Kotlin/C#/Swift, C/C++, PHP, CSS via declaration regexes plus brace matching; Ruby/Elixir/Lua via indentation; Markdown headings; JSON/YAML/TOML keys; CSV shape; log files (time span, error line numbers); Makefiles, shell functions, SQL statements. Huge files fold members into their parents and truncate with a note rather than pretending to be complete.

Honest limitations

  • Token counts are estimates (chars / 3.6), not tokenizer output. Ratios are what matter and they are unaffected.
  • Outlines for brace languages are regex-based. They are meant for navigation, not correctness; a weird formatting style can miss a symbol. Grep still works.
  • The Read guard costs one extra tool round-trip for files just over the threshold. The default (400 lines) is chosen so the outline plus a slice is still much cheaper than the file; raise it if your agent mostly needs whole files.
  • The Bash wrapper runs the command through bash -c in a child process. Shell functions and aliases defined in Claude Code's persistent shell are not visible to it (environment variables and the working directory are).
  • Only Claude C

Only the beginning is shown; read the rest in the repo

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