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codecalc

by The-40-Thievesversion 0.13.0i★ –iRuns on your computer
Registry nameio.github.The-40-Thieves/codecalc

Install

Overview

Description from the maker (original English)

Code & logic calculator for AI agents: 31 languages, symbolic math, SMT/logic solving, Big-O.

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: Other

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

Run this in your terminal

claude mcp add codecalc -- uvx codecalc

Open in Cursor

Or copy the settings yourself

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

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

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

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 7, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account The-40-Thieves, 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 Otheri

  • More stars than 0% of the other 32583 servers in this category
  • Published to the registry more recently than 47% of the other 32583 servers in this category
  • Basic checks equal to or better than 100% of the other 32583 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 codecalc 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 (0.13.0) 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: Spec Driven Development, Remote Desktop Commander, sync. labs

Alternatives

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Runs on your computer★ 440MITUpdated 14 months ago
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Remote Desktop Commander

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Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

Runs in the cloud★ 211Updated yesterday
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sync. labs

by synchronicity-labs

Lipsync videos, dub them into other languages, make talking videos and open sync. Studio.

Computer or cloudUpdated today
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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.

codecalc — universal code & logic calculator for AI models

**codecalc is an offline, self-hosted MCP server that gives an AI agent a calculator, a code runner, and a logic checker — so it gets a *correct* answer instead of a guessed one. It runs code in 31 languages, does exact symbolic math, solves SMT/logic problems, and measures complexity, all exposed as 51 MCP tools**.

Fastest path: uvx 'codecalc[full]' setup --write registers codecalc with your MCP client automatically. New to MCP, or want more detail first? See QUICKSTART.md, or the Install section below.

Three things nobody else offers together cleanly:

  • Offline-core — ships no model, no API key, no gateway, no telemetry. The core opens no sockets; network access is opt-in and only where a specific tool's job needs it (the Piston provider, install_package, the runtime-update tools, executed code unless no_net, and a one-time in-process grammar download on first analyze_complexity — full breakdown in the network-boundary table below).
  • Safe execution of untrusted code — an opt-in *strict* isolation boundary (gVisor+Docker on Linux, AppContainer on Windows) layered above the default rlimit sandbox, fail-closed and attested.
  • Verification tools — verify_translation proves a port to another language behaves identically, verify_optimization proves an optimization preserved behavior, and z3_check proves or refutes logic with an SMT solver.

When to use codecalc

Use it when you want a free, local, private, hardened code-runner and verifier that an MCP agent can call directly — no vendor account, no cloud spend, nothing leaving the machine except where a tool's job explicitly requires it.

Reach for something else when you want managed cloud scale instead of self-hosting (a hosted sandbox like E2B or Modal), or when you're not self-hosting at all and the model vendor's built-in code interpreter already covers what you need.

codecalc vs. the alternatives

codecalc is not a general cloud sandbox and not a vendor code interpreter. It overlaps with several things and beats them in only one narrow place — forcing a model to *measure* a claim instead of asserting it. Where that isn't what you need, one of these is the better tool, and this table says so plainly.

You want…Better fitWhy
To just run some Python/JS quickly, zero setupYour model vendor's built-in interpreterAlready there, already sandboxed, nothing to install. Anthropic's code-execution tool has internet access "completely disabled" and cannot install packages at runtime; OpenAI's hosted containers have no outbound network access by default, with an org-level network_policy allowlist as an opt-in. Both return output artifacts by reference (Anthropic a file_id via the Files API, OpenAI a container_file_citation) rather than inline (Anthropic code-execution tool docs, https://platform.claude.com/docs/en/agents-and-tools/tool-use/code-execution-tool; OpenAI shell/container tool guide, https://developers.openai.com/api/docs/guides/tools-shell; both retrieved 2026-09-07)
Heavy or multi-tenant workloads, managed scaleA cloud sandbox (E2B, Modal, Daytona)Per-tenant Firecracker/gVisor isolation codecalc does not claim by default
Pure arithmetic or symbolic math, nothing elseA small calculator or SymPy MCPLower token cost; none of the 31-language runtime machinery
A model to stop _guessing_ numbers, equivalence, and speedups — locally, privately, with graded evidencecodecalcExact rationals, verify_translation/verify_optimization, and unenforced/grade honesty — offline, no account

Do not reach for codecalc if you need multi-tenant or network-exposed isolation (its threat model is explicitly single-operator, local, stdio), if zero-setup convenience matters more than measurement, or if a hosted interpreter already covers your case. It earns its keep only when the *correctness of the claim* — not just "it ran" — is the point.

Install

Quickstart with codecalc setup

The fastest path to a working MCP connection, without reading the rest of this section:

uvx 'codecalc[full]' setup            # prints what it would do — nothing on disk changes

uvx 'codecalc[full]' setup --write # applies it: merges your client's config, copies the skill

It detects which MCP client is installed (Claude Desktop, Claude Code, Cursor, VS Code, Zed — pass --client=NAME if none or several are found), reuses codecalc doctor's own backend/extras/grammar-cache checks, prints the exact config block in that client's own JSON shape with absolute paths already filled in, runs two real canaries (execute_code, evaluate_expression) to prove the connection would work, and ends in one verdict: ready / degraded / not-ready. --write is the only mode that changes anything — it MERGES the codecalc entry into your existing client config (every other server stays exactly as it was) and backs up the original to .codecalc-bak first. codecalc --help lists every subcommand.

[!NOTE]

Published as `codecalc` 0.13.0 on PyPI (pip install codecalc) and the

`codecalc-exec` 0.13.0 executor on crates.io

(#91). Every release

artifact carries a keyless sigstore build-provenance attestation — verify

one with gh attestation verify --repo The-40-Thieves/codecalc; PyPI

wheels additionally carry PEP 740 attestations.

Where to find codecalc
WhereWhat you getLink
PyPIpip install codecalc / uvx codecalcpypi.org/project/codecalc
crates.iothe codecalc-exec Rust executor cratecrates.io/crates/codecalc-exec
GitHub Releaseswheels for every platform, the executor binaries, the .mcpb bundle, an SBOM, and SHA256SUMSgithub.com/The-40-Thieves/codecalc/releases
MCP registry (official)the io.github.The-40-Thieves/codecalc server entry server.json publishes toregistry.modelcontextprotocol.io
Smitheryhosted listing and one-click client configsmithery.ai/servers/@The-40-Thieves/codecalc
Glamahosted listing and the score badge aboveglama.ai/mcp/servers/The-40-Thieves/codecalc
MCPB (Claude Desktop)the drag-and-drop bundle, attached to every GitHub Releasesee GitHub Releases, above
Docker MCP Catalogthe mcp/codecalc image Docker builds from this repo's docker/mcp-server.Dockerfile, for Docker Desktop's MCP Toolkit (docker mcp server enable codecalc)submitted as docker/mcp-registry#5025; listed at hub.docker.com/mcp/server/codecalc once merged

Not yet listed: PulseMCP and mcp.so do not carry a codecalc entry yet; the Docker MCP Catalog entry is pending review. PulseMCP's own submission page (checked 2026-09-08) says it is not accepting new submissions and that publishing to the official MCP registry — already done, row above — is what it indexes from once submissions reopen, so there is nothing to submit there today. mcp.so takes a submission through its own form. See docs/distribution.md for the exact steps, kept there rather than here because submitting is an action for whoever runs it, not a fact about the current release.

The published install (simplest — no build step, and what most people want):

uvx 'codecalc[full]'          # run it directly, no environment to manage

or

pip install 'codecalc[full]' # into your own virtualenv

From source, if you would rather build the executor yourself:

git clone https://github.com/The-40-Thieves/codecalc

cd codecalc uv sync --all-extras # or: pip install -e '.[full]' cargo build --release --manifest-path executor/Cargo.toml mkdir -p bin # bin/ is gitignored, so a fresh clone has none cp executor/target/release/codecalc-exec bin/ uv run codecalc doctor # verify: backend should read rust

Without the cargo build, everything still runs on the pure-Python fallback — doctor will say so, and the network table below says what that costs.

Why `[full]`. The base install is the MCP surface and the sandbox executor: 31 language runtimes, sessions, packages, ~32 MB. The symbolic half — sympy and z3 — is 88.6 MB measured, and a caller who only runs code should not download an SMT solver to do it. So it is an extra:

installsizewhat you get
codecalc~32 MBexecute_code, sessions, packages, complexity-free tools
codecalc[symbolic]+83 MBevaluate_expression, solve, limits, truth tables, z3, units
codecalc[parsing]+5 MB installed, +89 MB fetched on first useanalyze_complexity via tree-sitter
codecalc[full]~120 MBeverything

Nothing fails silently: a tool whose extra is missing returns {"ok": false, "error": "sympy is not installed. It ships in the 'symbolic' extra: pip install 'codecalc[symbolic]' ..."}, and codecalc doctor lists which extras are present before you make a call.

Editions

Four names for the capability sets above, plus the two that live outside pyproject.toml entirely — a Docker image and an opt-in isolation boundary. The invariant that makes "edition" a meaningful word here: in the edition that lists a tool, that tool is functional — never listed-but-missing-its-extra. A tool an edition doesn't have returns the dependency_missing contract error naming the extra that provides it (see above), not a silent failure or a tool that appears to exist and doesn't work.

EditionInstallWhat you get
Fulluvx 'codecalc[full]' / pip install 'codecalc[full]'The recommended local product: the native (Rust) executor, symbolic tools (evaluate_expression, symbolic, z3_check, …), and parsing (analyze_complexity). Everything this README documents actually runs.
Coreuvx codecalc / pip install codecalcExecution + non-symbolic tools only — the base install in the table above. Every symbolic/parsing tool is still *listed* by tools/list (MCP doesn't support per-install schemas), but calling one returns dependency_missing naming the extra, before any other work happens.
Dockerdocker build -f docker/mcp-server.Dockerfile .The MCP server itself, packaged to run as an ordinary container. Core-shaped by default: ships python3/node/ruby/php/perl/gawk/lua/c/cpp/jq/sqlite3 and the default rlimit sandbox — symbolic/parsing are absent by design (no [full] in the base image; see the Dockerfile's own comment for why, including an arm64 z3-solver wheel gap). --build-arg CODECALC_EXTRA=full adds them. This image cannot nest the Strict Host boundary below inside itself (no privileged docker-in-docker), and codecalc doctor inside it says so rather than claiming a boundary it doesn't have.

| Strict Host | opt-in; CODECALC_STRICT_URL (client) or the gVisor+Docker host itself (server) — see docs/deployment/README.md | Not an install, a *boundary*: the gVisor runsc sandbox on Linux, or AppContainer hardening on Windows, layered above whichever install above is already running. Fails closed — no digest pinned, no fallback to unenforced

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