Skip to main content
Glama
rhishi99

agy-headless-bridge MCP server

agy-headless-bridge

Call the Google Antigravity CLI (agy) headlessly — and actually get output back.

Codename PtyGravity · pty + antiGravity

PyPI PyPI downloads MCP Registry tests License: MIT Python Platform

📖 Architecture & docs → rhishi99.github.io/agy-headless-bridge


TL;DR — the problem, before & after

agy -p "<prompt>" prints nothing when its stdout is not a real terminal. So calling it from a subprocess, an MCP server, CI, or another coding agent (Claude Code, Codex, …) returns an empty string and exit 0 — silently. This package gives agy a fresh pseudo-terminal so it emits normally, then cleans the output.

flowchart TB
    subgraph B["❌ BEFORE — agy -p from any non-TTY caller"]
        direction TB
        a1["subprocess · MCP · CI · agent"] --> a2["agy -p &quot;prompt&quot;"]
        a2 --> a3["stdout gated by isatty()"]
        a3 --> a4["(empty string)<br/>exit 0 · no error · no output"]
    end
    subgraph A["✅ AFTER — through agy-headless-bridge"]
        direction TB
        b1["subprocess · MCP · CI · agent"] --> b2["run(prompt)"]
        b2 --> b3["allocate fresh pseudo-terminal"]
        b3 --> b4["agy -p &quot;prompt&quot;<br/>isatty() == True"]
        b4 --> b5["clean() strips ANSI/TUI"]
        b5 --> b6["clean text ✓"]
    end

    classDef bad fill:#2a1313,stroke:#f87171,color:#ffd9d9;
    classDef good fill:#0f2a1e,stroke:#34d399,color:#d7ffe9;
    class a1,a2,a3,a4 bad;
    class b1,b2,b3,b4,b5,b6 good;
# ❌ The problem — plain subprocess
import subprocess
r = subprocess.run(["agy", "-p", "say hi"], capture_output=True, text=True)
print(r.stdout)          # '' — prints nothing, exit 0

# ✅ The fix
from agy_headless_bridge import run
print(run("say hi"))     # 'Hi! How can I help?'

Three entry points around one core:

Entry point

Invoke

Use for

Library

from agy_headless_bridge import run

embedding agy in Python

CLI

agy-bridge "prompt"

shell scripts, quick calls

MCP server

python -m agy_headless_bridge.mcp_server

letting an agent call agy as a tool


Related MCP server: agy MCP Server

The problem in detail — upstream bug #76

agy gates its stdout on isatty(). The instant stdout isn't a terminal, it goes silent — no output, no error, exit 0:

$ agy -p "say hi" | cat
$            # empty. exit 0. nothing.

The common winpty agy -p "..." workaround needs a terminal that already exists, so it still fails from any automated / non-TTY caller.

NOTE

Newer agy releases fixed this upstream: agy -p "..." | cat printed normally on agy 1.2.11 (Windows, checked Sep 2026). The bridge still earns its place there. It works on older agy builds. It kills a hung run on an idle timer and keeps partial output. It turns a failed exit or a spent quota into a typed error (AgyExitError / AgyQuotaError). It strips TUI noise, and it ships a dependency-free MCP server.

The fix — give agy a tty it didn't ask for

Allocate a brand-new pseudo-terminal (one that needs no parent tty) and attach agy to it. Same code path on every OS — only the pty allocator differs.

flowchart TD
    A["Caller — non-TTY<br/>Claude Code · MCP · subprocess · CI"] -->|"prompt"| B{{"run(prompt)"}}
    B --> C["find_agy()<br/>$AGY_PATH → PATH → OS defaults"]
    C --> D{"sys.platform?"}
    D -->|"win32"| E["pywinpty<br/>PtyProcess.spawn"]
    D -->|"posix"| F["stdlib pty<br/>os.openpty + Popen"]
    E --> G(["fresh pseudo-terminal"])
    F --> G
    G --> H["agy -p prompt<br/>isatty == True → emits"]
    H -->|"raw bytes + ANSI/TUI chrome"| I["clean()<br/>strip CSI/OSC · collapse \r repaints · drop spinner glyphs"]
    I -->|"clean text"| A

Platform

pty backend

Status

Windows

ConPTY via pywinpty (PtyProcess)

✅ verified (agy 1.0.6)

Linux / macOS

stdlib pty (os.openpty + subprocess.Popen)

⚠️ pty mechanics verified on Linux CI; real agy round-trip not yet verified on POSIX hardware

TIP

Linux/macOS users wanted. The pty mechanics (the os.openpty + Popen plumbing) are verified on Linux CI via a stub, but nobody has confirmed the real agy round-trip on bare-metal Linux or macOS yet. If you're on POSIX: pip install agy-headless-bridge, try it, and tell us how it went — pass or fail. PRs welcome.

Why not just the existing agy Claude Code plugins? They wrap agy for triggering (slash commands, model selection) but still call agy -p directly — so in any headless context they hit this exact empty-output bug. This package fixes the I/O layer they're missing. Use both together.


Prerequisites

Before installing this bridge you need:

  1. Python 3.9+ — python --version.

  2. The Antigravity CLI (agy), installed and authenticated:

    • Install: https://antigravity.google/cli

    • Authenticate once interactively (agy opens a browser OAuth flow), or set ANTIGRAVITY_API_KEY in your environment if you use an API key.

    • Verify it runs in a real terminal: agy -p "say hi" should print a reply. (On older agy builds it prints nothing from a pipe. That's the bug this package was built to fix.)

  3. Windows only: pywinpty (installed automatically as a dependency). POSIX uses the stdlib pty module — nothing extra.

This package does not install or authenticate agy, and does not bundle any credentials. It only spawns the agy already on your machine.


Install

Requires Python 3.9+.

pip install agy-headless-bridge          # pywinpty auto-installs on Windows only

From source:

git clone https://github.com/rhishi99/agy-headless-bridge
cd agy-headless-bridge
pip install -e .

The bridge locates the binary via, in order: $AGY_PATH → agy on PATH → OS default install paths.

As a Claude Code plugin

This repo is also a Claude Code plugin (.claude-plugin/plugin.json + .mcp.json). Installing it registers one local stdio MCP server, antigravity.

What the plugin runs and fetches:

  • Fetches: nothing from PyPI for this package — the plugin runs the source shipped in the plugin itself. On first start uv run --frozen (from uv) builds a virtualenv inside the plugin's install directory from the committed uv.lock. The only runtime dependency is pywinpty, on Windows only.

  • Runs: agy-mcp-server from that source. Each tool call spawns the agy binary already on your machine inside a pseudo-terminal (ConPTY on Windows, pty on POSIX), passes your prompt to it, and returns the cleaned text output. agy itself contacts Google's Antigravity service using your own agy login or ANTIGRAVITY_API_KEY.

  • Tools: agy_ask and agy_research. By default agy_ask adds the server's working directory (your project) to agy's workspace, so agy can read it; pass workspace: "none" to opt out. agy can edit files or run commands only if agy_ask is called with skip_permissions: true and the server was started with AGY_BRIDGE_ALLOW_SKIP_PERMISSIONS=1; the plugin does not set that variable.

  • Does not: install or authenticate agy, bundle credentials, open network ports, or send data anywhere other than through the agy you run.

Requirements: uv on PATH and an installed, authenticated agy (see Prerequisites). Local MCP servers load in Claude Code and in Cowork sessions running on your computer; claude.ai chat ignores them.


Usage

Library

from agy_headless_bridge import (
    run, AgyExitError, AgyNotFoundError, AgyQuotaError, AgyTimeoutError,
)

try:
    # For a CODING task, pass the repo so agy can see it — the library `run()`
    # is a thin primitive and does NOT auto-add a workspace (the CLI/MCP layers
    # do). Without add_dirs, agy -p runs blind in its own scratch workspace.
    print(run("Summarize this repo", add_dirs=["."], timeout=600))
except AgyTimeoutError as exc:
    print("timed out; partial so far:\n", exc.partial)  # resume with `agy -c`
except AgyQuotaError as exc:                  # subclass of AgyExitError
    print("quota spent; retry in", exc.reset_seconds, "s")  # None if unknown
except AgyExitError as exc:
    print(f"agy failed (exit {exc.returncode}):\n{exc.output}")
except AgyNotFoundError:
    print("install agy first")

run(prompt, timeout=900, agy_path=None, *, add_dirs=None, model=None, idle_timeout=120, extra_args=None, skip_permissions=False) -> str raises:

  • AgyNotFoundError if the binary is missing.

  • AgyTimeoutError, carrying .partial, on the idle or hard timeout.

  • AgyQuotaError, carrying .reset_seconds parsed from agy's message, when agy exits non-zero with a quota or rate-limit message.

  • AgyExitError, carrying .returncode and .output, on any other non-zero exit, such as an unknown --model.

  • ValueError on an empty prompt.

It returns "" only if agy genuinely emitted nothing. add_dirs → agy --add-dir; model → --model. The timeout is the absolute ceiling; idle_timeout ends a run that has gone silent for that many seconds (so a long-but-active task survives the ceiling).

skip_permissions=True passes --dangerously-skip-permissions. Headless agy cannot answer tool-approval prompts, so without it agy silently declines every file edit and command and still exits 0. With it, agy acts unattended inside add_dirs. Opt in only for trusted prompts.

To get the CLI/MCP "default to cwd for coding, none for research" behaviour in your own code, use resolve_add_dirs(explicit, use_cwd_default=...).

CLI

agy-bridge "reply with exactly: OK"
python -m agy_headless_bridge "reply with exactly: OK"   # equivalent

# Coding task: the current directory is auto-added to agy's workspace, so agy
# sees your repo with no extra flags.
agy-bridge "Find and fix the off-by-one in the parser"

# Research / Q&A that needs no repo — opt out of the cwd default:
agy-bridge --no-workspace "Explain idle timeouts in process supervision"

# Add more dirs, pick a model, widen the limits for a big task:
agy-bridge --add-dir ../shared-lib --model gemini-3-pro \
    --timeout 1800 --idle-timeout 180 "Refactor X to match the shared lib"

Flag

Default

Meaning

--add-dir DIR

cwd (auto)

Add a dir to agy's workspace (repeatable).

--no-workspace

off

Don't auto-add cwd (use for research / Q&A).

--model NAME

agy default

agy --model.

--timeout SECS

900

Hard ceiling (absolute wall).

--idle-timeout SECS

120

Kill after this many seconds of no output.

--skip-permissions

off

Let agy edit files / run commands unattended (--dangerously-skip-permissions).

Exit codes: 0 success · agy's own code when agy fails (its message is printed) · 75 quota / rate limit spent (retry later) · 1 timeout or no output · 127 agy not found.

MCP server

claude mcp add --transport stdio antigravity -- agy-mcp-server

agy-mcp-server is the console-script entry point pip install puts on your PATH — it's bound to the exact interpreter you installed the package with, so it sidesteps the "wrong python" problem below entirely. Prefer it over python -m agy_headless_bridge.mcp_server, especially on Windows.

claude mcp add --transport stdio antigravity -- \
    python -m agy_headless_bridge.mcp_server

Windows: use py -3.11 (the Python Launcher) instead of python in the command above. Bare python can resolve to the wrong interpreter or the Windows Store stub, which surfaces as an -32000 MCP connection error. See Troubleshooting.

The server speaks JSON-RPC stdio directly (no MCP SDK dependency) and routes every call through the pty bridge.

Tool schema (what an agent — or you, integrating manually — sees):

Tool

Argument

Type

Required

Description

agy_ask

prompt

string

✅

one-shot prompt sent to agy

agy_ask

workspace

"auto"|"none"

auto (default) adds the server's cwd so agy sees the repo; none for research / Q&A

agy_ask

add_dir

string[]

explicit dirs for agy's workspace (overrides the workspace default)

agy_ask

model

string

agy --model

agy_ask

timeout

number

hard timeout override, seconds

agy_ask

skip_permissions

boolean

let agy edit files / run commands unattended. Refused unless the server was started with AGY_BRIDGE_ALLOW_SKIP_PERMISSIONS=1, because the caller is itself a model

agy_research

query

string

✅

wrapped as a deep-research prompt for agy (never attaches a workspace)

Response shape — a standard MCP tools/call result; the answer is the text content:

{
  "jsonrpc": "2.0",
  "id": 2,
  "result": { "content": [ { "type": "text", "text": "<agy's cleaned answer>" } ] }
}

Failures are still a readable text reply rather than a JSON-RPC error, but the result also carries "isError": true so the client can tell them apart from an answer:

  • Timeout: whatever agy produced before the kill, then an [agy-mcp] TIMEOUT: ...; resume with 'agy -c' note, so partial work isn't lost.

  • Quota spent: agy's message, then [agy-mcp] QUOTA: ...; resets in ~Ns.

  • Anything else: agy's message (if any), then [agy-mcp] ERROR: .... This covers agy missing, a non-zero exit and bad arguments.


Use cases & wiring it into your AI coding tools

The whole point: let one AI coding tool delegate work to Gemini via Antigravity, headlessly. Common setups:

Use case

How

Claude Code asks Gemini for a second opinion / diff review

MCP server → agy_ask tool

A CI step runs an agy prompt and captures the answer

agy-bridge "..." in the workflow

A Python pipeline fans work out to agy

from agy_headless_bridge import run

Codex / any MCP-capable agent delegates to agy

register the same MCP server

Cron / scheduled job summarizes logs via agy

agy-bridge in the script

Wire into Claude Code

Register the MCP server, then prompt Claude to use it:

claude mcp add --transport stdio antigravity -- agy-mcp-server

Prompt to Claude Code: "Use the agy_ask tool to ask Antigravity to review this function for edge cases, then summarize its findings for me."

If you also want slash-command triggering and model selection, pair this bridge with the community antigravity-cc Claude Code plugin — that handles the /agy:* commands and Gemini/Claude model swap; this handles the headless I/O.

Wire into Codex (or any MCP client)

Add the server to the client's MCP config:

{
  "mcpServers": {
    "antigravity": {
      "command": "python",
      "args": ["-m", "agy_headless_bridge.mcp_server"]
    }
  }
}

Prompt to the agent: "Call agy_research with the query 'idiomatic error handling in Rust' and turn the result into a checklist."

Use from a shell / CI script

ANSWER="$(agy-bridge 'Summarize the key risk in this diff in one sentence.')"
echo "$ANSWER"

Configuration

Env var

Default

Meaning

AGY_PATH

auto-detect

Absolute path to the agy binary

AGY_BRIDGE_TIMEOUT

900

Hard ceiling (absolute wall), in seconds

AGY_BRIDGE_IDLE_TIMEOUT

120

Kill after this many seconds of no output from agy

AGY_BRIDGE_ALLOW_SKIP_PERMISSIONS

unset

Set to 1 on the MCP server to allow the skip_permissions tool argument


How clean() works

agy's pty output is a TUI stream, not plain text. clean() removes ANSI escapes (CSI/OSC — colors, cursor moves), \r repaints (a spinner overwrites one line; only the final paint is kept), and box-drawing / spinner glyphs (╭─╮ │ ⠋⠙⠹) — leaving just the model's answer.

What comes off the pty vs. what you get back:

RAW (off the pty)                          CLEANED (returned to you)
─────────────────────────────────────     ─────────────────────────
⠋ thinking…\r⠙ thinking…\r\x1b[2K          A closure is a function that
\x1b[32m╭─────────────╮\x1b[0m              captures variables from the
\x1b[32m│\x1b[0m A closure is a function     scope where it was defined.
that captures variables from the
scope where it was defined.
\x1b[32m╰─────────────╯\x1b[0m

Troubleshooting / FAQ

pip install fails on Windows building pywinpty — pywinpty is a native extension. If pip tries to build from source and errors with a compiler/cl.exe message, install the Microsoft C++ Build Tools (or use a Python where a prebuilt pywinpty wheel exists — recent CPython on Windows has them). Upgrade pip first: python -m pip install -U pip.

-32000 MCP connection error on Windows (interpreter mismatch) — bare python in the claude mcp add command can resolve to the wrong interpreter or the Windows Store stub, so the spawned server can't import the package and the connection fails. Use the Python Launcher instead — register the server with py -3.11 (matching the Python where you installed the package) in place of python. To confirm where the package actually landed, run pip show agy-headless-bridge and check the Location: field; if it points to a different Python than Claude Code spawns, that mismatch is the cause.

AgyNotFoundError — the bridge can't find agy. Set AGY_PATH to the absolute path of the binary, or make sure agy is on your PATH (agy --version should work in your shell).

Empty string returned — agy produced no output. Confirm it works in a real terminal first: agy -p "say hi". If that's also empty, the problem is agy/auth, not the bridge. Re-authenticate (agy interactively) or check ANTIGRAVITY_API_KEY.

AgyTimeoutError — agy hit a limit. Two triggers: the hard ceiling (AGY_BRIDGE_TIMEOUT, default 900s) and the idle timeout (AGY_BRIDGE_IDLE_TIMEOUT, default 120s — fires when agy emits nothing for that long). The error carries .partial (whatever agy produced first), and the CLI prints it before exiting. Widen the limits for long prompts: AGY_BRIDGE_TIMEOUT=1800 agy-bridge "...", --idle-timeout 300, or run(prompt, timeout=1800, idle_timeout=300). To continue a run that timed out, resume the agy session directly with agy -c.

agy stalls until the idle timeout, then times out on what looks like a normal prompt — this bridge never writes to agy's stdin, so if agy pauses mid-run to ask for interactive approval (e.g. "allow this tool call?"), the prompt sits unanswered and the run silently stalls until the idle timeout kills it. This is currently the most common way a run hangs. Configure agy itself to auto-approve (check agy --help / its settings for a non-interactive/auto-approve flag) before delegating tasks that involve tool use, or expect the idle timeout to eventually fire and surface .partial.

Pseudo-terminal allocation fails — rare. On Windows it means pywinpty isn't importable (reinstall it). On POSIX it means the system is out of pty slots or pty.openpty() is denied (containers with no /dev/pts); run with a real pty available.

Garbled / partial output — open an issue with the OS, Python + agy version, and the raw output; clean() may need another glyph rule.

Development & CI

pip install -e ".[dev]"
pytest

Unit tests (cleaning, arg validation, binary discovery) always run. The live agy round-trip test auto-skips when agy isn't installed — so CI runners (which don't have agy) stay green and never need credentials. CI runs on Windows + Linux across Python 3.9 and 3.12.


Scope, non-goals & disclaimer

  • Model selection (Gemini Pro / Flash / Claude inside agy) is not handled here — it's an agy settings.json concern, covered by the antigravity-cc plugin. Pair the two.

  • Does not install or authenticate agy, and ships no credentials.

  • Automating any vendor CLI may interact with that vendor's terms / rate limits. You are responsible for using agy within Google's terms of service. This project only changes how stdout is captured — it does not bypass auth, quotas, or any access control.

  • Not affiliated with Google. Antigravity and agy are Google products.

License

MIT.

Available Tools

2 tools
agy_askB

Send a one-shot prompt to the Google Antigravity CLI (agy) and return its response. Use to delegate a focused coding, debugging, or reasoning task to Gemini via Antigravity.

ParametersJSON Schema
NameRequiredDescriptionDefault
modelNoagy --model (optional)
promptYesThe prompt to send to agy
add_dirNoExplicit directories to add to agy's workspace. Overrides the workspace default below.
timeoutNoHard timeout in seconds (override when a task legitimately needs longer).
workspaceNoauto (default): if no add_dir given, add the server's cwd so agy sees the repo — needed for coding tasks. none: no workspace (use for research / Q&A that needs no repo context).
skip_permissionsNoLet agy edit files / run commands without approval prompts (headless agy otherwise declines them silently). Only honoured if the server was started with AGY_BRIDGE_ALLOW_SKIP_PERMISSIONS=1.

TDQS

B3.3/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full behavioural burden. It conveys 'one-shot' (single turn) and that a response is returned, but omits that agy can edit files and run commands (the skip_permissions param implies a mutation-capable, headless agent), credential/auth requirements, and timeout/long-task behaviour. These side-effect risks are material and unstated in the description.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two tight sentences, front-loaded with the action, zero filler. It could still be marginally more informative without bloating, so not a top mark.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a six-parameter, mutation-capable CLI bridge with no annotations and no output schema, the description is thin: it says nothing about file-editing side effects, permission/skip gating, or result shape. An agent could call it correctly on arguments but would misjudge its blast radius.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents model, prompt, add_dir, timeout, workspace and skip_permissions in detail. The description adds no parameter-level syntax or defaults beyond what the schema provides, making the baseline 3 appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a concrete verb and resource: send a one-shot prompt to the Antigravity CLI (agy) and return its response. This clearly separates it from a stateful/session tool, and the delegation scoping (coding, debugging, reasoning) hints at its niche versus agy_research without naming the sibling explicitly.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives a clear use context: delegate a focused coding, debugging, or reasoning task to Gemini. It stops short of an explicit when-not-to-use rule or naming agy_research as the alternative for research/Q&A, so routing between the two siblings is left partly to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

agy_researchB

Ask Antigravity to research a topic deeply.

ParametersJSON Schema
NameRequiredDescriptionDefault
queryYesResearch query or topic

TDQS

B3.1/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, and the description lacks behavioral details such as whether the tool is read-only, expected response time, or what 'research deeply' entails. The agent is left guessing about side effects or constraints.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is only one sentence, which is concise but sacrifices clarity. It does not fully explain what the tool does or how to use it effectively. Could be more structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the low complexity (1 parameter, no output schema, no annotations), the description is minimally adequate but lacks completeness. No information about return values, depth of research, or usage context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with a clear description for the single parameter 'query'. The description adds no extra semantics beyond what the schema already provides, so baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool performs research on a topic, but it does not differentiate from the sibling tool 'agy_ask'. The phrase 'deeply' hints at more thorough analysis, but the distinction is implicit.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when to use this tool versus 'agy_ask'. The description implies usage for deep research, but no alternatives or exclusions are mentioned.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 1 tool updatev1.3.0
    • Changedagy_ask1 field changed
      • addedInput schema / properties / skip_permissions
        Added value: +{
        +  "description": "Let agy edit files / run commands without approval prompts (headless agy otherwise declines them silently). Only honoured if the server was started with AGY_BRIDGE_ALLOW_SKIP_PERMISSIONS=1.",
        +  "type": "boolean"
        +}
  2. 1 tool updatev1.2.0
    • Changedagy_ask4 fields changed
      • addedInput schema / properties / add_dir
        Added value: +{
        +  "description": "Explicit directories to add to agy's workspace. Overrides the workspace default below.",
        +  "items": {
        +    "type": "string"
        +  },
        +  "type": "array"
        +}
      • addedInput schema / properties / model
        Added value: +{
        +  "description": "agy --model (optional)",
        +  "type": "string"
        +}
      • addedInput schema / properties / timeout
        Added value: +{
        +  "description": "Hard timeout in seconds (override when a task legitimately needs longer).",
        +  "type": "number"
        +}
      • addedInput schema / properties / workspace
        Added value: +{
        +  "description": "auto (default): if no add_dir given, add the server's cwd so agy sees the repo — needed for coding tasks. none: no workspace (use for research / Q&A that needs no repo context).",
        +  "enum": [
        +    "auto",
        +    "none"
        +  ],
        +  "type": "string"
        +}
  3. 2 tool updates
    • First observedagy_ask
    • First observedagy_research

TDQS

B3.3/5.0

Scored across 2 tools

Disambiguation3/5

agy_ask and agy_research both send a prompt to the same Antigravity CLI and return a response, so the boundary is blurred: a user could fulfill research needs by calling agy_ask with a 'research this' prompt. The description hints at a depth/intent difference, but nothing structural distinguishes the two tools (no separate parameters, output shapes, or guarantees).

Naming Consistency5/5

Both tools use the same agy_ prefix with a single lowercase snake_case verb (ask, research), forming a clean, predictable pattern. There is no mixing of conventions or verb styles.

Tool Count3/5

Two tools is thin for a bridge server, and one of them (agy_research) appears to be a thin wrapper around the other, so the surface feels under-scoped rather than deliberately minimal. It is not extreme, but there is little room for distinct capability.

Completeness3/5

The server covers one-shot prompt delegation but lacks any session/multi-turn continuation, file or workspace context parameters, or status/cancel operations that a CLI bridge typically needs. Core workflow (ask something and get an answer) works, but agents will hit dead ends for stateful or long-running tasks.

Maintenance

ActivityMaintained
ResponsivenessNo issues

Related MCP Connectors

Related MCP Servers