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Veto

by jigyasudham

Local MCP server exposing 93 tools, 49 specialist agents, cross-CLI memory, reviews, routing, and developer workflows.

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Install Veto

Pick your client, then add it in one click or paste the config.

STDIONode.js
~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "jigyasudham-veto": {
      "command": "npx",
      "args": [
        "-y",
        "@jigyasudham/veto@latest"
      ]
    }
  }
}

Settings → Developer → Edit Config, merge this into mcpServers, then fully quit and reopen Claude Desktop.

We couldn’t confirm it starts correctly

We ran the install command but it didn't respond within our test window — this can mean a slow first-time install rather than a real problem.

npx -y @jigyasudham/veto@latest

No response to initialize.

This is an experimental automated check and can have false negatives — missing environment variables, a slow cold install, etc. It doesn’t necessarily mean something’s wrong. Last checked 1mo ago.

Overview

jigyasudham/veto MCP server runs locally and gives supported AI coding clients access to 93 tools backed by 49 specialist agents. It combines deterministic analysis modules with optional reasoning through the host AI or MCP Sampling, plus sessions, memory, routing, reviews, CI gates, and workflow tools. Use it when you want shared project context and structured development assistance across Claude Code, Codex CLI, Gemini CLI, Cursor, Windsurf, and other listed clients without supplying a separate API key.

Use cases

  • Run coordinated code and security reviews across a project
  • Route development tasks to specialist agents
  • Persist project decisions and memory across AI clients
  • Check proposed dependencies before installation
  • Create CI gates and pre-commit workflow checks

Key features

  • 49 specialist agents across six domains
  • 93 MCP tools for development workflows
  • Deterministic analysis with optional LLM reasoning
  • Cross-client sessions and persistent memory
  • Self-learning task router
  • Compact tool advertisement mode

Security & health

What it can reach and how reliably it runs — from our own checks, not the maintainer’s claims.

ActiveLast checked 1d ago

Recent health check succeeded.

5/5 checks healthy over the last 78d

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 9d ago via OSV.dev · @jigyasudham/veto@latest (npm)

Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars4Stargazers on the source repository.
npm downloads2.1kPackage downloads in the last 30 days.
Last commit15d agoMost recent push to the default branch.
Install checkInconclusiveDidn't respond in our test window — often a slow first install.
Directory activity5 viewsConfig copies, upvotes, and views on AllMCPs.

How Veto works

What jigyasudham/veto does

The jigyasudham/veto MCP server adds a broad developer-tool surface to AI coding clients. Its 49 specialists include a seven-agent Council and 42 worker agents covering development, security, memory, research, quality, and workflow tasks. The server exposes 93 MCP tools for code review, security and secrets scanning, task planning, dependency checks, session management, project mapping, documentation, CI gates, and related operations.

The server is intended for local use. It can provide persistent memory across supported clients, coordinate specialist agents, record decisions and outcomes, and route tasks to suitable capabilities. Compact mode reduces the number of schemas advertised initially while retaining access to the full catalog through discovery and invocation tools.

How it works

Worker agents begin as deterministic expert modules. Analysis agents use techniques such as regex or AST detection, OWASP/CWE rules, and hash-based clone matching, while planning agents provide structured playbooks and checklists. They can optionally be upgraded with reasoning from the host AI through an agentic loop, or through MCP Sampling on clients that support server.createMessage.

The Council is designed for multi-agent discussion and can fall back to a deterministic verdict when no LLM path is available. Parallel agent execution is supported. A self-learning router can retune tier thresholds after recorded task outcomes when automatic application is enabled. The dependency verification tool checks proposed packages against a live registry before installation, addressing nonexistent package names and slopsquatting risks.

Setup and configuration

Install the CLI globally with:

Terminal
npm i -g @jigyasudham/veto

Then run veto init to register the server with the AI clients you use. An npx-based setup is also documented:

Terminal
npx -y @jigyasudham/veto@latest init

The generated MCP configuration launches veto-server through the package registry. The global installation supplies the CLI, while the generated server command resolves the latest package on client restarts. Compact mode can be enabled with VETO_COMPACT=1 in the MCP server environment or with compact_tools: true in ~/.veto/config.json.

Tools and capabilities

Notable tool groups include:

  • Sessions, autosave, replay, status, and handoff
  • Task routing, agent planning, delegation, composition, and parallel execution
  • Council debates, ADRs, benchmarking, and decision tracking
  • Code, diff, pull request, security, secrets, dependency, and full reviews
  • CI gates, pre-commit checks, workflows, task parsing, and file watching
  • Persistent memory, project maps, patterns, exports, imports, and search
  • Local LLM, semantic search, SDD agents, Playwright, and IDE notification tools
  • Documentation, OpenAPI generation, release notes, diagrams, RCA, and postmortems

Limitations and notes

No separate API key is required for the documented subscription-based workflow, but LLM reasoning can consume tokens when the host uses API or pay-per-token billing. The server detects API-key environment variables during initialization and warns about this billing mode. Deterministic modules work offline, while LLM-enhanced behavior depends on the client path available.

Compact mode changes the initially advertised tool surface; it does not remove the other catalog tools. The listed integrations include Claude Code, Codex CLI, Gemini CLI, Antigravity CLI, Cursor, Windsurf, Zed, and JetBrains.

Read the full README View source on GitHub

Reviews

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Frequently Asked Questions about Veto

Install the CLI with `npm i -g @jigyasudham/veto`, then run `veto init`. The documented npx alternative is `npx -y @jigyasudham/veto@latest init`.

No separate API key is required for its subscription-based workflow. API or pay-per-token users may incur token charges when LLM reasoning is used.

Enable compact mode with `VETO_COMPACT=1` in the MCP server environment or set `compact_tools` to `true` in `~/.veto/config.json`.

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