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Veto

by jigyasudhamversion 3.9.0i★ –iRuns on your computer
Registry nameio.github.jigyasudham/veto

Install

Overview

Description from the maker (original English)

93 agentic MCP tools + 49 specialist agents for every major AI CLI. Self-learning, no API keys.

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: Games, sports, food & learning

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

  • npmNode.js installed (for the npx 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": {
    "veto": {
      "command": "npx",
      "args": [
        "-y",
        "@jigyasudham/veto"
      ]
    }
  }
}

Run this in your terminal

claude mcp add veto -- npx -y @jigyasudham/veto

Open in Cursor

Or copy the settings yourself

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

{
  "mcpServers": {
    "veto": {
      "command": "npx",
      "args": [
        "-y",
        "@jigyasudham/veto"
      ]
    }
  }
}

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": {
    "veto": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@jigyasudham/veto"
      ]
    }
  }
}

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 jigyasudham, 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 Games, sports, food & learningi

  • More stars than 0% of the other 1290 servers in this category
  • Published to the registry more recently than 46% of the other 1290 servers in this category
  • Basic checks equal to or better than 100% of the other 1290 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 Veto 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 (3.9.0) reached the registry 34 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.

What can I use instead?

In the same category: CareerMode.xyz, Esavendors, Datingcoaches

Alternatives

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

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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.

veto

93 agentic tools. 49 specialists. Every major AI CLI. Self-learning. Zero extra cost on subscriptions.

An MCP server that runs locally on your machine, plugs into Claude Code, Codex CLI, Gemini CLI, Antigravity CLI, Cursor, Windsurf, Zed, and JetBrains using your existing subscriptions — giving every AI a council of specialist agents, local LLM support, SDD agents, playwright automation, persistent cross-platform memory, a self-learning router that re-tunes its tier thresholds automatically every 20 recorded task outcomes (reviews record outcomes for you; configurable via auto_apply_learning), CI/CD gates, workspace discovery, and bidirectional IDE communication.

Billing note: "Zero cost" applies to subscription plans (Claude Max, Gemini Advanced, etc.). If you are on API/pay-per-token billing, LLM reasoning done for Veto agents (via the agentic loop or MCP Sampling) counts toward your token usage like any other turn. veto init detects API key environment variables and warns you automatically.


Getting Started

# 1. Install the CLI — puts the bare `veto` command on your PATH

npm i -g @jigyasudham/veto

2. Register Veto with every AI client you use (Claude Code, Gemini, Codex, Cursor, …)

veto init

Prefer not to install anything? Every command also works via npx:

npx -y @jigyasudham/veto@latest init

The two are independent by design. veto init writes MCP configs that launch the server with npx -y --package @jigyasudham/veto@latest veto-server — npx re-resolves @latest against the registry on every client restart, so the MCP server auto-updates itself and a global copy can never pin it to an old version. The global install only provides the CLI (veto doctor, veto sessions, the statusline, …); keep it current with npm i -g @jigyasudham/veto@latest when veto doctor says it's behind.


How the Agents Work

No API keys, zero extra cost. Every worker agent is a deterministic expert module at its core, with two optional layers of LLM reasoning on top — all of it delegated to the AI you're already paying for.

Default — Deterministic expert modules

Out of the box, each of the 42 worker agents runs as a hand-written expert module (plan() / analyze() in src/agents/) — not an LLM. They always run, work offline, and cost zero tokens. Their depth varies by design: analysis agents (security scanner, secrets, dependency audit, clone detector, privacy, auth, performance, compatibility, …) apply real algorithms — regex/AST detection, OWASP/CWE rules, hash-based clone matching — while planning agents (coder, debugger, tester, …) are structured expert playbooks: curated steps, checklists, and pitfalls for the task category, built to be reasoned over by the AI you already pay for rather than to reason themselves.

Path A — Agentic loop (most clients: Claude Code, Cursor, Windsurf)

Veto returns the specialist's role, rubric, and an output contract as an llm_upgrade prompt. The host AI reasons as the specialist and passes structured JSON back to complete the operation. This is the primary path — it costs nothing beyond your existing subscription and works on every client.

Path B — MCP Sampling (clients that support server.createMessage)

Where Sampling is available, the same upgrade happens server-side without the extra round-trip. Note: the July 2026 MCP spec revision deprecates Sampling protocol-wide (12-month sunset), so the agentic loop (Path A) is Veto's long-term default; Sampling remains a transparent optimization where it exists.

The 7-agent Council is LLM-first — its value is the multi-agent debate — but it too falls back to a deterministic verdict when no LLM path is available. When multiple agents run, they execute in parallel.


Specialist Roles

49 specialists: 42 deterministic worker agents across 6 domains + a 7-agent Council. The Council debates trade-offs before you build; the worker agents do the hands-on analysis and planning. Each is a deterministic expert module that can upgrade to LLM reasoning — see How the Agents Work. List them anytime with veto agents.

Council (7) Lead Dev · PM · Architect · UX · Devil's Advocate · Legal · Security

Development (12) Coder · Code Reviewer · Tester · Debugger · Refactor · Database · API · Frontend · Backend · DevOps · Performance · Migration

Security (6) Security Scanner · Auth Agent · Data Privacy · Secrets Agent · Dependency Audit · Penetration Tester

Memory (5) Context Manager · Decision Logger · Project Mapper · Pattern Learner · Knowledge Base

Research (7) Researcher · Tech Advisor · Cost Analyzer · Competitor Analyzer · Risk Assessor · Estimator · Ethics & Bias

Quality (5) Code Quality · Documentation · Accessibility · Compatibility · Error Handling

Workflow (7) Task Planner · Task Coordinator · File Manager · Git Agent · Search Agent · Reporter · Automation


MCP Tools (93)

CategoryTools
Sessionveto_status · veto_session_save · veto_session_restore · veto_sessions_list · veto_autosave_status · veto_session_replay
Routerveto_route_task · veto_rate_status
Councilveto_council_debate · veto_benchmark · veto_adr
Agentsveto_agent_plan · veto_execute_parallel · veto_explain · veto_compose_agents · veto_delegate
Reviewveto_code_review · veto_security_scan · veto_secrets_scan · veto_diff_review · veto_full_review · veto_pr_review
Pipelinesveto_ci_gate · veto_pre_commit · veto_new_feature · veto_workflow · veto_task_parse
Advancedveto_local_llm · veto_semantic_search · veto_sdd_agent · veto_playwright · veto_notify_ide
Qualityveto_clone_detector · veto_lint_rules · veto_api_contract · veto_a11y_advisor · veto_type_coverage · veto_test_gaps
Advisorsveto_dep_advisor · veto_dep_verify · veto_query_advisor · veto_bundle_advisor · veto_dead_code · veto_hitl_checkpoint · veto_drift_check
Watchingveto_watch · veto_watch_poll · veto_watch_stop
Memoryveto_memory_store · veto_memory_search · veto_memory_delete · veto_decisions · veto_project_map_update · veto_project_map_get · veto_pattern_store · veto_patterns_list · veto_memory_export · veto_memory_import
Learningveto_record_outcome · veto_learning_stats · veto_learning_apply
Handoffveto_handoff · veto_continue · veto_platform_setup
Observabilityveto_usage_status · veto_audit_log · veto_health · veto_metrics · veto_snapshot
Discoverveto_discover · veto_summarize · veto_git_blame · veto_changelog · veto_onboard · veto_debt_register
DevToolsveto_docs_fetch · veto_context_status · veto_openapi_gen · veto_flag_auditor · veto_env_setup · veto_commit_message · veto_pr_description · veto_pr_post · veto_prompt_optimizer · veto_sre_advisor · veto_diagram · veto_rca · veto_doc_gen · veto_postmortem · veto_release_notes · veto_translate · veto_merge_conflict
Pluginsveto_plugins

Compact Mode — 93 tools without the context tax

93 tool schemas cost a client ~20K context tokens before the user types a word. Compact mode advertises a surface that is 5–6× smaller: seven core tools (veto_status, veto_session_save, veto_session_restore, veto_route_task, veto_council_debate, veto_memory_search, veto_record_outcome) plus two meta-tools — veto_find_tools searches the full catalog by keyword and returns matching schemas on demand; veto_call invokes any catalog tool by name. Every tool remains directly callable in both modes; compact only changes what is advertised up front.

Enable it with VETO_COMPACT=1 in your MCP server config env, or "compact_tools": true in ~/.veto/config.json:

{

"mcpServers": { "veto": { "command": "npx", "args": ["-y", "--package", "@jigyasudham/veto@latest", "veto-server"], "env": { "VETO_COMPACT": "1" } } } }

Dependency-Hallucination Guard

LLMs propose plausible-but-nonexistent package names, and adversaries register those names on public registries (slopsquatting) — a supply-chain attack class with no pre-install check in most AI workflows. veto_dep_verify checks every proposed package against the live registry before you install:

veto_dep_verify { packages: ["axios", "axois", "left-padd"], ecosystem: "npm" }

→ axios verified (14 years old, 40M downloads/month) → axois HIGH_RISK (1 edit from "axios" — possible typosquat) → left-padd NOT_FOUND (likely hallucinated — do NOT retry the install later: nonexistent AI-suggested names are prime slopsquat targets)

Signals per package: registry existence, age, monthly downloads, version history, deprecation, and typo-distance from popular packages. Supports npm, PyPI, and crates.io. Network failures return unverifiable — never silently safe.

Decision-Drift Enforcement

AI assistants forget architectural decisions and re-litigate them sessions later — the most common complaint about long-running AI projects. Veto's memory doesn't just store decisions; it enforces them. Record a decision once as a machine-checkable constraint:

veto_decisions {

action: "add", rule: "We use Postgres — no Mongo", why: "Decided 2026-05: relational data, team expertise", forbidden_patterns: ["mongoose", "mongodb"], severity: "block" }

From then on, veto_diff_review and veto_ci_gate automatically fail any diff whose added lines match a forbidden pattern — when an AI quietly adds mongoose to the imports three sessions later, the review fails with the rule and the rationale attached. Patterns are case-insensitive regexes (with substring fallback), optionally scoped to a file glob (src/**/*.ts), per-project or global, severity block or warn. Manage with action: list / check / disable / enable.

You don't have to remember to do this. When a council verdict (the LLM-backed one) or an ADR settles something, its result carries a one-time constraint_invitation: your AI asks you once whether it should become a rule, and passes your answer back as add or decline with the invitation_id. It never asks twice about the same verdict. action: list shows how many invitations were offered, accepted and declined; that count stays on your machine.

A rule can't stall your reviews. add refuses a pattern that could hang the check: one over 200 characters, or a repeated group that itself repeats, like (a+)+. Every check is also time-boxed, so a slow rule turns into a warning instead of blocking veto_ci_gate.

Compounding-Error Circuit Breaker

Agents fail silently in loops — retrying the same broken call, re-hitting the same error, thrashing between two tools — and burn a whole session before anyone notices. veto_drift_check scans the recent tool-call trace for that pattern mid-flight and trips a breaker before the spiral compounds:

veto_drift_check

→ DRIFT DETECTED • 4 consecutive failed calls (veto_diff_review) • same error repeated 3× ("no diff provided") • tool veto_route_task called 6× in a row → remediation (debugger agent): stop retrying; the diff is empty — point at a project_dir with uncommitted changes or pass diff explicitly.

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