Agentvet MCP server
Validate tool-call args before execution. Returns LLM-friendly retry hints.
1 stars38 downloads/wk
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If you have run it, two minutes of your experience saves the next person an afternoon.
Agentvet tools (3)
write = sends, deletes, buys or postsRead from the package source without running it. The installed server may list more.
generate_retry_messageGiven a tool name, validation error, and attempted args, build the canonical LLM-facing retry feedback message. Uses agentvet's ToolArgError.toLLMFeedback() formatting so the wording matches what runtime callers see.
lint_tool_definitionSanity-check a tool definition for common mistakes that hurt LLM tool-use accuracy: missing description, vague description, no required fields, schema fields without descriptions, non-snake_case names.
validate_tool_argsValidate a tool-call args object against a small shape spec. Returns { valid, error?, retry_hint? } where retry_hint is a ready-to-send LLM feedback message describing exactly what was wrong.
Public scan report
scanner v0.1.9 · 2026-09-27 · same rubric, same numbers if you re-run it
- Code scan2 source files scanned25/25
- –Live reliabilityno gateway calls yet and no remote to proben/a
- –Tool poisoningtools not inspected (local package is not executed); not countedn/a
- Auth qualitylocal package, no credentials required12/15
- Maintenancelast push 58 days ago12/15
- Maintainer identityregistry namespace matches repository owner; GitHub account older than a year8/10
How Agentvet compares
Against every graded AI and agents MCP server, from our own scans and uptime checks. Updated after each scan run.
- Safety score
- 88/100
- higher than 80% of 4,464 AI and agents servers
- Tools
- 3
- the typical AI and agents server has 6
- Tools that change things
- 0%
- typical: 0%. Fewer write tools means less an agent can break
- GitHub stars
- 1
- more than 50% of 2,697 AI and agents servers
- Downloads a week
- 38
- more than 30% of 1,515 AI and agents servers with a package
What its tools let an agent do: 2 read · 1 create
Install Agentvet in Claude Code, Cursor or VS Code
Runs npx -y @mukundakatta/agentvet-mcp on your machine. Read the scan report first; the gateway never runs local packages.
claude mcp add agentvet -- npx -y @mukundakatta/agentvet-mcp
What the publisher says
From the Agentvet repository's README, as published. We do not edit it. Read it on GitHub
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-mcpThree tools:
- validatetoolargs — check args against a small shape spec; returns { valid, error?, retryhint? } where retryhint is a ready-to-send LLM feedback message.
- linttooldefinition — sanity-check a tool definition for common mistakes that hurt LLM tool-use accuracy.
- generateretrymessage — 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/claudedesktopconfig.json (macOS) or %APPDATA%\Claude\claudedesktopconfig.json (Windows):
{
"mcpServers": {
"agentvet": {
"command": "npx",
"args": ["-y", "@mukundakatta/agentvet-mcp"]
}
}
}Same shape for Cursor (~/.cursor/mcp.json), Cline, Windsurf, Zed.
Tool examples
validatetoolargs:
{
"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."
}linttooldefinition:
{
"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.
generateretrymessage:
{
"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:
- @mukundakatta/agentfit-mcp — Fit it.
- @mukundakatta/agentguard-mcp — Sandbox it.
- @mukundakatta/agentsnap-mcp — Test it.
- @mukundakatta/agentvet-mcp — Vet it. (this)
- @mukundakatta/agentcast-mcp — Validate it.
License
MIT
Nothing above is checked by us. What we check is on the safety report.
Agentvet: common questions
- Is Agentvet MCP server safe?
- Yes, by our scan: it is graded A (88/100). Read the Agentvet safety report
- How do I install Agentvet?
- It runs on your machine. Copy the Claude Code, Cursor, VS Code or Claude Desktop config from the install section.
- Does Agentvet need an API key?
- Not as far as the registry entry and our scan can tell: no credentials are declared or required.
- Is Agentvet maintained?
- The last commit was 93 days ago (2026-08-01). The latest release is v0.1.0.
- What can I use instead of Agentvet?
- Servers from other publishers that do the same job: Decionis MCP server, Ausca MCP server and AKShare MCP server.
- How does Agentvet compare with other AI and agents MCP servers?
- safety score 88/100 (higher than 80% of 4,464 AI and agents servers); tools 3 (the typical AI and agents server has 6); tools that change things 0% (typical: 0%. Fewer write tools means less an agent can break). Full comparison.
Alternatives to Agentvet
Same job from other publishers: the closest match first, then the best rated.
- DecionisAuthorize consequential AI agent actions before executionnot reviewedEstablishedA
- AuscaPay-per-call APIs and MCP services for agents, no accounts or keys, with verifiable receipts.not reviewedEstablishedA
- AKShareLet a model explore AKShare's 1000+ China market data functions on its own — search, inspect, callnot reviewedEstablishedA
- ClawdcursorSafe cross-OS desktop control for any AI agent - the fallback execution layer.not reviewedEstablishedC
- adrkit decision memoryDeterministic, offline, read-only ADR decision memory for coding agents. No model or network calls.not reviewedEstablishedA