Local MCP server exposing 93 tools, 49 specialist agents, cross-CLI memory, reviews, routing, and developer workflows.
Copy the AI prompt to install this server into Claude Code, Cursor, or another agent โ or use 1-click editor setup below.
We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag โ we're steadily working through the catalog.
๐ก Paste the JSON block into your client's configuration file under mcpServers, then restart the application.
Inspect callable tools, capabilities, and parameters exposed to AI agents by Veto.
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.
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.
Install the CLI globally with:
Then run veto init to register the server with the AI clients you use. An npx-based setup is also documented:
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.
Notable tool groups include:
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.
The README notes that MCP Sampling is being deprecated in a future specification revision, so the agentic loop is the longer-term default. 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.
Always refer to the official documentation for the most accurate and up-to-date information.
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