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Agy Bridge

by sshahzaiibversion 0.3.1i★ –iRuns on your computer
Registry nameio.github.sshahzaiib/agy-bridge

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_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": {
    "agy-bridge": {
      "command": "npx",
      "args": [
        "-y",
        "agy-bridge"
      ],
      "env": {
        "AGY_PATH": "your-value",
        "AGY_TIMEOUT": "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 agy-bridge --env AGY_PATH=your-value --env AGY_TIMEOUT=your-value --env AGY_MAX_OUTPUT_CHARS=your-value --env AGY_DEFAULT_MODEL=your-value --env AGY_ON_FAILURE=your-value -- npx -y agy-bridge

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": {
    "agy-bridge": {
      "command": "npx",
      "args": [
        "-y",
        "agy-bridge"
      ],
      "env": {
        "AGY_PATH": "your-value",
        "AGY_TIMEOUT": "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": {
    "agy-bridge": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "agy-bridge"
      ],
      "env": {
        "AGY_PATH": "your-value",
        "AGY_TIMEOUT": "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 per-tool timeouts, in seconds
  • 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
  • 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 6, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account sshahzaiib, 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 32476 servers in this category
  • Published to the registry more recently than 13% of the other 32476 servers in this category
  • Basic checks equal to or better than 100% of the other 32476 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 Agy Bridge 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 (0.3.1) reached the registry 5 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, zanadir

Alternatives

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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.

agy-bridge

An MCP bridge that lets Claude Code delegate heavy tasks to the Antigravity CLI (`agy`) — saving Claude's context window and tokens for what matters.

Claude sends a task → the bridge routes it to the best available model via agy → only the answer comes back. Large files, deep git searches, and web lookups never touch Claude's context.

Listed on

User → Claude Code → agy-bridge (MCP) → agy CLI → Gemini / Claude / GPT-OSS

← ← ←

Why this over claude-to-agy?

claude-to-agyagy-bridge
Tool surface1 generic delegate_to_agy6 purpose-built tools — Claude self-routes reliably
Model selectionnone (agy default only)per-tool routing across all agy models, with availability detection and fallback
Multi-turnstatelesssession continuity — follow_up resumes agy conversations without resending context
Output safetyunboundedconfigurable truncation cap protects Claude's context
Sandboxnooptional --sandbox mode
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 agy-bridge \ '{"command":"npx","args":["-y","agy-bridge"],"timeout":600000}'

2. Add delegation rules to your project (or ~/.claude/CLAUDE.md for global)

curl -o CLAUDE.md https://raw.githubusercontent.com/sshahzaiib/agy-bridge/main/CLAUDE.md

The "timeout": 600000 (10 min, milliseconds) is the client-side tool-call

deadline — without it, a cold-start analyze_files (~40–50s) or a long

delegate can hit Claude Code's default and return `timed out waiting for

response` while the agy run is still going. If your client doesn't honor a

per-server timeout, set the global env var MCP_TOOL_TIMEOUT=600000 instead.

Details and the agy-side budgets are in Timeouts and cancellation.

Tools

ToolUse forModel routing (first available)
analyze_filesFiles >200 lines, >3 files at once, logs, dumps, generated codeGemini Flash (High) → Gemini Pro (Low) → fallback
deep_searchgit log/diff/blame archaeology, repo-wide grepsGemini Flash (Medium) → (High) → fallback
web_lookupDocs, API references, external/current knowledgeGemini Flash (Medium) → (High) → fallback
adversarial_reviewPlan critiques, design and code reviewsGemini Pro (High) → Gemini Flash (High) → fallback
follow_upContinue a prior session by session_id — no context resendinherits the session
delegateAnything else heavyGemini Flash (High) → fallback

All tools accept optional cwd (project root) and model (an id or display name from agy models; validated, with available models listed on mismatch).

Every response ends with a footer:

---

[agy-bridge] model: Gemini Flash (High) | session: 1f0c…-d4 (use follow_up to continue)

Model routing

On first use the bridge runs agy models (cached for the process lifetime) and picks the first available model in the tool's preference chain. Chain entries name a family and tier rather than a version (Gemini * Flash (High)), and * resolves to the newest version agy currently lists, so a Gemini release never silently breaks routing. Chains are Gemini-first; Claude Opus and GPT-OSS are appended as a last resort and only used when no Gemini model is listed. If none is available it falls back to AGY_DEFAULT_MODEL, and finally to agy's own default. agy silently ignores unknown --model values, so the bridge validates names up front instead of letting requests land on the wrong model.

Quota-aware failover

agy never surfaces quota exhaustion in print mode — it silently retries the 429 until its print-timeout, then exits 0 with empty output, which used to look like an indefinite hang. The bridge now watches each run's log file (via --log-file) and on RESOURCE_EXHAUSTED (code 429):

  1. kills the agy process group immediately (no waiting out the timeout),
  2. parses the reset time ("Resets in 4h24m") into an in-process cooldown registry,
  3. retries the same prompt on the next model in the tool's chain,
  4. skips cooled-down models on all subsequent calls until their quota resets.

Failovers are annotated in the response footer (failover: : quota exhausted (resets in 4h24m)). Only when every candidate is exhausted does the call fail — in seconds, with reset times listed — instead of hanging.

Timeouts and cancellation

Each tool has its own default timeout sized to its job: web_lookup 120s, deep_search 180s, analyze_files / adversarial_review / follow_up 300s, delegate 600s. Setting AGY_TIMEOUT explicitly overrides all of them at once. To change a single tool, set AGY_TIMEOUT_ instead (e.g. AGY_TIMEOUT_DEEP_SEARCH=300); a per-tool override takes precedence over the global AGY_TIMEOUT and the tool's default. The full set of per-tool variables is AGY_TIMEOUT_ANALYZE_FILES, AGY_TIMEOUT_DEEP_SEARCH, AGY_TIMEOUT_WEB_LOOKUP, AGY_TIMEOUT_ADVERSARIAL_REVIEW, AGY_TIMEOUT_FOLLOW_UP, and AGY_TIMEOUT_DELEGATE. The kill path escalates SIGTERM → SIGKILL across the whole process group, and the deadline fires even if agy's helper processes hold the output pipes open. Cancelling the tool call from the MCP client (e.g. pressing Esc in Claude Code) also kills the agy run instead of orphaning it.

Two timeout layers — align them. The timeouts above are the _agy-side_ budget. Your MCP client (Claude Code) has its own, separate _tool-call_ timeout, and if it is shorter than the agy budget the client gives up first — you'll see Error: timed out waiting for response (note: agy-bridge's own timeout reads agy timed out after Ns instead). The work is not lost: the agy session persists, so follow_up with the returned session_id retrieves the result. But the real fix is to make the client wait at least as long as agy: the Install command already sets a per-server timeout of 600000ms (scoped to the agy-bridge entry only). If you registered the server without it, re-run the add-json command from Install, or set the global env var MCP_TOOL_TIMEOUT=600000. Rule of thumb: client `timeout` ≥ agy budget.

Expected latency. Most of the perceived "slowness" is cold start: the first call in a session spawns the agy CLI and warms the model. A simple analyze_files over 3 files measures around 40–50s cold (≈46s observed), dropping on subsequent same-session calls. A first call that also hits a quota 429 takes longer while the bridge fails over. So a client timeout below ~60s will intermittently trip on cold starts even for "simple" questions — size it generously.

Configuration

All optional, via environment variables:

VariableDefaultDescription
AGY_PATHagyPath to the agy binary
AGY_TIMEOUTper-toolSeconds; overrides all per-tool timeouts at once (see above), passed as --print-timeout, enforced with a 15s kill grace
AGY_TIMEOUT_ per-toolSeconds; overrides the timeout for a single tool only, e.g. AGY_TIMEOUT_DEEP_SEARCH=300. Wins over AGY_TIMEOUT
AGY_MAX_OUTPUT_CHARS50000Truncation cap for tool output
AGY_DEFAULT_MODELunsetFallback model when no chain entry is available (name, id, or * pattern)
AGY_SKIP_PERMISSIONStruePass --dangerously-skip-permissions to agy
AGY_SANDBOXfalseRun agy with --sandbox
AGY_ON_FAILUREfallbackstrict appends an instruction to failed-tool errors telling the calling agent not to absorb the work itself
Failure behavior

The bridge always fails loudly: agy errors surface as MCP tool errors with agy's actual stderr, and degraded model routing is annotated in the response footer. By default the calling agent (Claude) will typically do the work itself after a failure — visible in the transcript, but easy to stop noticing in a long session. Set AGY_ON_FAILURE=strict to append an explicit "do NOT perform this work yourself — report the fai

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