agentvet-mcp

agentvet-mcp

MCP server that validates LLM-generated tool-call arguments, lints tool definitions, and produces retry messages for AI assistants.

Category
Visit Server

README

agentvet-mcp

MCP server for @mukundakatta/agentvet. Lets Claude Desktop, Cursor, Cline, Windsurf, Zed, or any other MCP client validate LLM-generated tool-call args before execution and produce LLM-friendly retry messages when something's wrong.

npx -y @mukundakatta/agentvet-mcp

Three tools:

  • validate_tool_args — check args against a small shape spec; returns { valid, error?, retry_hint? } where retry_hint is a ready-to-send LLM feedback message.
  • lint_tool_definition — sanity-check a tool definition for common mistakes that hurt LLM tool-use accuracy.
  • generate_retry_message — given a validation error, build the canonical LLM-facing retry message using agentvet's ToolArgError.toLLMFeedback() formatting.

Add to your client

Claude Desktop

Edit ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows):

{
  "mcpServers": {
    "agentvet": {
      "command": "npx",
      "args": ["-y", "@mukundakatta/agentvet-mcp"]
    }
  }
}

Same shape for Cursor (~/.cursor/mcp.json), Cline, Windsurf, Zed.

Tool examples

validate_tool_args:

{
  "tool_name": "send_email",
  "args": { "to": "a@b.com" },
  "shape": { "to": "string", "subject": "string", "body": "string" }
}

Returns:

{
  "valid": false,
  "error": "missing required field: subject",
  "retry_hint": "send_email rejected your args: missing required field: subject. Please call again with the corrected arguments."
}

lint_tool_definition:

{
  "tool": {
    "name": "BadName",
    "inputSchema": { "type": "object", "properties": { "x": { "type": "string" } } }
  }
}

Returns warnings about non-snake_case name, missing description, missing field descriptions, and no required fields.

generate_retry_message:

{
  "tool_name": "send_email",
  "validation_error": "missing required field: subject",
  "attempted_args": { "to": "a@b.com" }
}

Returns the canonical retry feedback string the runtime callers see — so you can prepare retry text outside the live agent loop.

Why a separate MCP server

@mukundakatta/agentvet is a zero-dependency JavaScript library. This MCP server makes its validation primitives accessible from any MCP-aware AI assistant. Useful for quickly auditing a registry of tools, or asking the assistant "is this args object valid for my send_email tool?" without leaving the chat.

For runtime arg validation in your agent loop, use @mukundakatta/agentvet directly inside your Node process (it wraps your tool fn and throws ToolArgError synchronously).

Sibling MCP servers

Part of the agent-stack series:

License

MIT

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured