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Claude Agy MCP

by PyModelversion 1.0.3i★ –iRuns on your computer
Registry nameio.github.PyModel/claude-agy-mcp

Install

Overview

Description from the maker (original English)

Delegate heavy tasks from Claude Code to the Antigravity CLI (Gemini) with quota-aware failover.

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: Other

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).
  • You fill in yourself: AGY_PATH, AGY_TIMEOUT, AGY_MAX_RUNTIME, AGY_MAX_OUTPUT_CHARS, AGY_DEFAULT_MODEL, AGY_ON_FAILURE

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": {
    "claude-agy": {
      "command": "npx",
      "args": [
        "-y",
        "@pymodel/claude-agy-mcp"
      ],
      "env": {
        "AGY_PATH": "your-value",
        "AGY_TIMEOUT": "your-value",
        "AGY_MAX_RUNTIME": "your-value",
        "AGY_MAX_OUTPUT_CHARS": "your-value",
        "AGY_DEFAULT_MODEL": "your-value",
        "AGY_ON_FAILURE": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add claude-agy --env AGY_PATH=your-value --env AGY_TIMEOUT=your-value --env AGY_MAX_RUNTIME=your-value --env AGY_MAX_OUTPUT_CHARS=your-value --env AGY_DEFAULT_MODEL=your-value --env AGY_ON_FAILURE=your-value -- npx -y @pymodel/claude-agy-mcp

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

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

{
  "mcpServers": {
    "claude-agy": {
      "command": "npx",
      "args": [
        "-y",
        "@pymodel/claude-agy-mcp"
      ],
      "env": {
        "AGY_PATH": "your-value",
        "AGY_TIMEOUT": "your-value",
        "AGY_MAX_RUNTIME": "your-value",
        "AGY_MAX_OUTPUT_CHARS": "your-value",
        "AGY_DEFAULT_MODEL": "your-value",
        "AGY_ON_FAILURE": "your-value"
      }
    }
  }
}

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": {
    "claude-agy": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@pymodel/claude-agy-mcp"
      ],
      "env": {
        "AGY_PATH": "your-value",
        "AGY_TIMEOUT": "your-value",
        "AGY_MAX_RUNTIME": "your-value",
        "AGY_MAX_OUTPUT_CHARS": "your-value",
        "AGY_DEFAULT_MODEL": "your-value",
        "AGY_ON_FAILURE": "your-value"
      }
    }
  }
}

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.

Values you fill in

  • AGY_PATH env
    Path to the agy binary (defaults to `agy` on PATH)
  • AGY_TIMEOUT env
    Override the runtime ceiling for all tools, in seconds (use AGY_TIMEOUT_ to override a single tool)
  • AGY_MAX_RUNTIME env
    Absolute runtime ceiling in seconds (default 3600); the bridge does not kill on inactivity, only on cancellation, quota exhaustion, or this ceiling
  • AGY_MAX_OUTPUT_CHARS env
    Truncation cap for tool output, in characters (default 50000)
  • AGY_DEFAULT_MODEL env
    Fallback model when no chain entry is available (defaults to Gemini 3.6 Flash (High))
  • AGY_ON_FAILURE env
    Set to `strict` to instruct the calling agent not to absorb failed delegations (default `fallback`)

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 7, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account PyModel, 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 Otheri

  • More stars than 0% of the other 32623 servers in this category
  • Published to the registry more recently than 23% of the other 32623 servers in this category
  • Basic checks equal to or better than 100% of the other 32623 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 Claude Agy MCP 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 (1.0.3) reached the registry 3 months 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: Spec Driven Development, Remote Desktop Commander, Draugr

Alternatives

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

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Remote Desktop Commander

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Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

Runs in the cloud★ 211Updated 2 days ago
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Draugr

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Security scanning for AI agents: SAST, SCA, secrets, IaC, DAST, ranked by real risk.

Runs on your computerUpdated today
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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.

Install · Why Gemini 3.8 Flash? · MCP Power Stack · Tools · Timeouts · Configuration

⚡ Install

npm i @pymodel/claude-agy-mcp
claude mcp add-json -s user claude-agy-mcp \

'{"type":"stdio","command":"npx","args":["-y","@pymodel/claude-agy-mcp"],"timeout":3600000}'

Claude Code delegates heavy tasks to Google's flagship Gemini Flash via the Antigravity CLI (agy) — saving Claude's context window and tokens for what matters.

Claude acts as the orchestrator → claude-agy-mcp routes compute-heavy sub-tasks to the newest Gemini Flash agy offers → only concise answers return. Large files, deep git searches, and log dumps never pollute Claude's context.

User → Claude Code → claude-agy-mcp (MCP) → agy CLI → Gemini 3.8 Flash / Pro / Claude

← ← ← (Clean answers only)

Why Gemini Flash for Claude Code?

Gemini Flash is Google's most intelligent workhorse model for coding and agentic execution. It applies deep multi-step planning, rigorous terminal reasoning, and high first-pass code accuracy.

Gemini 3.8 Flash (High) is the default model for every tool. Each chain leads with gemini-flash@latest-high, which resolves against agy models to the newest Flash at High effort — 3.8 Flash as of 2026-09-11 — and only falls back to Pro or Claude when Flash is unavailable or cooling down. The benchmark table below compares 3.8 Flash against 3.7 Flash, from Google's launch table (2026-09-02); the bridge does not pin that generation.

Benchmark Highlights
Benchmark / CapabilityGemini 3.8 Flash (High)Prior Generation (3.7 Flash)Advantage
DeepSWE v1.173.7%65.3%+8.4 pts in long-horizon software engineering; within 0.3 of Claude Opus 5
Terminal-Bench 2.189.4%85.8%+3.6 pts in agentic CLI execution; ahead of Opus 5 (89.1%) and GPT-5.6 Sol
OSWorld-2.059.0%50.6%+8.4 pts in agentic computer use
HLE-Verified54.9%53.6%Multi-step expert reasoning, ahead of Opus 5 (54.4%)
Vals Finance Agent v261.4%59.0%Leads Opus 5 (58.6%) and GPT-5.6 Sol (53.8%) on quantitative agent work
Token Economics$0.75 / $3.75 (1M)$0.75 / $3.75Same price as 3.7 Flash; up to 10x–20x cheaper than Claude Opus/Sonnet
The Token & Context Multiplier

When Claude Code directly analyzes a 4,000-line database dump or greps 20 files across git history, those thousands of lines stay permanently in Claude's prompt context, inflating cost and pushing you toward compaction.

With claude-agy-mcp:

  1. Claude calls analyze_files or deep_search.
  2. Gemini 3.8 Flash processes the 100k+ tokens in isolation via agy.
  3. Only the exact code-level findings and line citations return into Claude's prompt.
  4. Subsequent questions reuse the same agy session with follow_up without re-sending any files.

The Ultimate AI Engineering MCP Stack

claude-agy-mcp is designed to anchor a modern AI engineer's MCP toolkit alongside complementary specialized servers:

┌─────────────────────────────────────────────────────────────────────────────┐

│ Claude Code (Agent) │ └──────┬──────────────────────┬───────────────────────┬───────────────────────┘ │ │ │ │ ▼ ▼ ▼ ▼ ┌──────────────┐ ┌──────────────┐ ┌──────────────┐ ┌──────────────┐ │claude-agy-mcp│ │ context7 │ │ firecrawl │ │ tavily │ │ (Gemini 3.8 │ │(Official Docs│ │(Web Scraping │ │(Live Search │ │ Delegation) │ │ & API Specs)│ │ & Crawling) │ │ & Research) │ └──────────────┘ └──────────────┘ └──────────────┘ └──────────────┘

MCP ServerPrimary SuperpowerWhen Claude Uses It
`claude-agy-mcp`Heavy Compute & Coding DelegationAnalyzing files >200 lines, repo archaeology (git log/diff/blame), adversarial code reviews, and raw execution via Gemini 3.8 Flash.
`context7`Up-to-date Official DocumentationFetching latest version-accurate API signatures and documentation for libraries (Next.js, React, Tailwind, Prisma, Vite, etc.) to eliminate hallucinated APIs.
`firecrawl`Clean Web Scraping & CrawlingConverting dynamic web pages, documentation sites, and GitHub repos into clean, LLM-ready markdown or structured JSON.
`tavily`Fast Live Search & GroundingLow-latency web search, current news, error message lookups, and technical research.
Recommended MCP Configuration (.agents/mcp_config.json or Claude Code)
{

"mcpServers": { "claude-agy-mcp": { "command": "npx", "args": ["-y", "@pymodel/claude-agy-mcp"], "timeout": 3600000 }, "context7": { "command": "npx", "args": ["-y", "@upstash/context7-mcp@latest"] }, "firecrawl": { "command": "npx", "args": ["-y", "firecrawl-mcp"] }, "tavily": { "command": "npx", "args": ["-y", "tavily-mcp"] } } }


Why this over claude-to-agy?

claude-to-agyclaude-agy-mcp
Tool surface1 generic delegate_to_agy8 purpose-built tools — Claude self-routes reliably
Model selectionnone (agy default only)per-tool family selectors that follow new generations, with quota failover
Multi-turnstatelesssession continuity — follow_up resumes agy conversations without resending context
Output safetyunboundedconfigurable truncation cap protects Claude's context
Sandboxnoread-only tools blocked from writing into the workspace on macOS, optional --sandbox
Honest resultsexit code onlydecides on agy's JSON envelope — reports auto-denied tool actions instead of hiding them
Installuvx (Python)npx (Node) — zero install

Requirements

Install

# 1. Register the MCP server (user scope = all projects).

add-json bakes in a generous client-side timeout so long analyze_files /

delegate calls don't trip Claude Code's tool-call deadline (see Timeouts).

claude mcp add-json -s user claude-agy-mcp \ '{"type":"stdio","command":"npx","args":["-y","@pymodel/claude-agy-mcp"],"timeout":3600000}'

2. Install the bundled skills into every agent found on this machine.

The server gives an agent the tools; the skills tell it when to use them.

npx --package @pymodel/claude-agy-mcp claude-agy-mcp-install-skills

--list to preview, --dir to install somewhere explicit,

--force to replace a skill you have symlinked to your own checkout.

3. Optional: add delegation rules to your project (or ~/.claude/CLAUDE.md).

curl -o CLAUDE.md https://raw.githubusercontent.com/PyModel/claude-agy-mcp/main/CLAUDE.md

Bundled skills

Installing the package installs the skills too, so there is nothing separate to vendor or keep in sync:

SkillWhat it does
agy-delegationRouting rules: which tool to reach for, and when delegating beats doing the work in-context.
agy-delegateThe full delegate-and-review workflow — writing a brief agy can execute blind, dispatching it, reviewing the diff against the brief, and landing it yourself. Includes a CLI-relay fallback for agents that cannot call MCP tools.

The "timeout": 3600000 (60 min, milliseconds) is the client-side tool-call

deadline, matched to the bridge's default AGY_MAX_RUNTIME ceiling. Without it,

a cold-start analyze_files (~40–50s) or a long delegate hits Claude Code's

default and returns timed out waiting for response w

Only the beginning is shown; read the rest in the repo

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