Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Beschreibung vom Entwickler (englisches Original)
Code & logic calculator for AI agents: 31 languages, symbolic math, SMT/logic solving, Big-O.
Diese drei werden nie zu einer Punktzahl zusammengefasst: Meinungen, Messungen und Beliebtheit sind verschiedene Dinge.
Für diesen Server haben wir noch keine Zusammenfassung in einfacher Sprache geschrieben. Unten stehen die Fakten, die wir aus der Registry gelesen haben.
Wähle die KI-App, die du nutzt, und kopiere die Einstellungen.
Du brauchst
Welche App nutzt du?
Wähle oben deine App. Wir merken sie uns, damit der Button beim nächsten Mal „In … installieren“ anzeigt.
Öffne Claude Desktop → Settings → Developer → Edit Config und füge dies in claude_desktop_config.json ein
{
"mcpServers": {
"codecalc": {
"command": "uvx",
"args": [
"codecalc"
]
}
}
}Führe das in deinem Terminal aus
claude mcp add codecalc -- uvx codecalcIn .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen
{
"mcpServers": {
"codecalc": {
"command": "uvx",
"args": [
"codecalc"
]
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
In .vscode/mcp.json in deinem Projekt einfügen
{
"servers": {
"codecalc": {
"type": "stdio",
"command": "uvx",
"args": [
"codecalc"
]
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
Dieser Server läuft auf deinem Computer, und ChatGPT kann sich nur mit Servern im Internet verbinden. Wähle eine andere App.
Deine Auswahl bleibt in einem Cookie auf diesem Gerät; kein Konto nötig.
Diese Einstellungen werden aus dem Registry-Eintrag des Entwicklers erzeugt. Wenn in der README etwas anderes steht, folge der README.
Läuft auf deinem Computer; die Tool-Liste erscheint nach der Installation in deiner KI-App.
Wir prüfen Informationen, die jeder sehen kann; den Code haben wir nicht gelesen. Checks, die nicht zutreffen, werden nicht mitgezählt. · Geprüft am 6. Nov. 2026
Der Registry-Name wurde mit dem GitHub-Konto The-40-Thieves bestätigt, dem das Repo gehört
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieser Server läuft auf deinem Computer; es gibt keinen Endpunkt im Internet
Läuft auf deinem Computer und nutzt stattdessen lokale Einstellungen
Läuft auf deinem Computer; Tool-Listen können wir nur von Endpunkten im Internet lesen
Verglichen mit allen aktiven Servern dieser Kategorie in der Registry. Sterne zählen nur, wenn dem Herausgeber das Repo gehört.
Er hat 1 von 1 zutreffenden Basischecks bestanden. Den Code haben wir nicht gelesen. Bevor du einen Schlüssel oder Token hinzufügst, sieh nach, welche Zugriffe der Server verlangt, und nutze einen Schlüssel, der nur die Berechtigungen hat, die du brauchst.
Die Registry nennt keinen erforderlichen Schlüssel, manche Server bitten dich aber bei der ersten Nutzung, dich anzumelden.
Er läuft auf deinem Computer. Deine KI-App startet ihn bei Bedarf, und die Daten laufen nicht über die Server des Entwicklers (außer der Server ruft selbst einen Onlinedienst auf).
Das GitHub-Repo wurde zuletzt – geändert, und die neueste Version (0.13.0) kam vor 2 Monaten in die Registry.
Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code. Außerdem brauchst du Python (uv) auf deinem Computer.
In derselben Kategorie: Spec Driven Development, Remote Desktop Commander, zanadir
Server derselben Kategorie von anderen Entwicklern, sortiert nach Sternen.
So liest du eine Karte:★ GitHub-SterneiDrei Säulen: Bewertungen · Checks · NutzungiAktualisiert = neueste Version in der Registry veröffentlichti
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
Find what a repository's CI is missing, and which security checks cannot fail the build.
Unverändert aus dem Repo des Entwicklers übernommen. PopNx MCP hat den Inhalt weder geprüft noch empfiehlt es ihn. HTML, Bilder und Skripte wurden entfernt. Links führen von dieser Website weg.
**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:
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).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.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 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 fit | Why |
|---|---|---|
| To just run some Python/JS quickly, zero setup | Your model vendor's built-in interpreter | Already 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 scale | A cloud sandbox (E2B, Modal, Daytona) | Per-tenant Firecracker/gVisor isolation codecalc does not claim by default |
| Pure arithmetic or symbolic math, nothing else | A small calculator or SymPy MCP | Lower token cost; none of the 31-language runtime machinery |
| A model to stop _guessing_ numbers, equivalence, and speedups — locally, privately, with graded evidence | codecalc | Exact 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.
codecalc setupThe 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 | What you get | Link |
|---|---|---|
| PyPI | pip install codecalc / uvx codecalc | pypi.org/project/codecalc |
| crates.io | the codecalc-exec Rust executor crate | crates.io/crates/codecalc-exec |
| GitHub Releases | wheels for every platform, the executor binaries, the .mcpb bundle, an SBOM, and SHA256SUMS | github.com/The-40-Thieves/codecalc/releases |
| MCP registry (official) | the io.github.The-40-Thieves/codecalc server entry server.json publishes to | registry.modelcontextprotocol.io |
| Smithery | hosted listing and one-click client config | smithery.ai/servers/@The-40-Thieves/codecalc |
| Glama | hosted listing and the score badge above | glama.ai/mcp/servers/The-40-Thieves/codecalc |
| MCPB (Claude Desktop) | the drag-and-drop bundle, attached to every GitHub Release | see GitHub Releases, above |
| Docker MCP Catalog | the 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
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:
| install | size | what you get |
|---|---|---|
codecalc | ~32 MB | execute_code, sessions, packages, complexity-free tools |
codecalc[symbolic] | +83 MB | evaluate_expression, solve, limits, truth tables, z3, units |
codecalc[parsing] | +5 MB installed, +89 MB fetched on first use | analyze_complexity via tree-sitter |
codecalc[full] | ~120 MB | everything |
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.
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.
| Edition | Install | What you get |
|---|---|---|
| Full | uvx '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. |
| Core | uvx codecalc / pip install codecalc | Execution + 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. |
| Docker | docker 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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