imagine-mcp: Instructions file for Claude Code

CLAUDE.md

imagine-mcp CLAUDE.md is an instructions file for Claude Code from n24q02m/imagine-mcp. It costs 2,964 tokens per session, scanned A, original, Apache-2.0.

Instructions for an MCP server that understands and generates images and videos using Gemini, OpenAI, or Grok models. MCP is a way for an AI agent to call tools provided by another program.

In plain words
What is it for?
Analyzing images or videos, generating images or short videos, changing server settings, and getting tool help.
Why use it?
It provides one documented interface for choosing a provider, quality level, media type, and output format.

Instructions file for Claude Code

Written for Claude Code: the file is CLAUDE.md. Also seen: reads .claude/ paths.

This is n24q02m/imagine-mcp's own configuration. It tells Claude Code how to work on imagine-mcp itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything imagine-mcp configures →

Needs its repository: it reads a path above its own folder, which exists only inside the repository. The line is cd ../mcp-core && uv run --project scripts/e2e python -m e2e.driver <config-id>.

Reuse

Borrowing it

Nothing to install: this file belongs to n24q02m/imagine-mcp. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/n24q02m/imagine-mcp/main/CLAUDE.md
Clone the repo
git clone --depth 1 https://github.com/n24q02m/imagine-mcp

Made for: Claude Code.

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Per session 2,964 This file is loaded in full into every session.
When invoked 2,964 The same file — it is already loaded in full.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.02964 $0.02964
Opus 5 $0.01482 $0.01482
Sonnet 5 $0.00593 $0.00593
Haiku 4.5 $0.00296 $0.00296

Measured 9d ago against content hash 89da91a579a0, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

imagine-mcp CLAUDE.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

CLAUDE.md · 213 lines

How it starts

The opening of the file, as written. The whole thing — 213 lines — stays where its author put it; the contents beside it link to each section on GitHub.

imagine-mcp

Production-grade MCP server for image/video understanding and generation across Gemini, OpenAI, and Grok.

Architecture

  • Tools (4 total, N+2 layout): understand, generate, config, help
  • Providers: gemini | openai | grok
  • Tiers: poor (cheap/fast) | rich (high quality)
  • Media types: image | video

Tool signatures

understand(media_urls: list[str], prompt: str,
           provider: str | None = None, tier: str = "poor",
           max_tokens: int = 2048,
           model: str | None = None) -> dict

generate(media_type: Literal["image", "video"], prompt: str,
         provider: str | None = None, tier: str = "poor",
         reference_image_url: str | None = None,
         job_id: str | None = None,
         output_mode: Literal["base64", "path", "both"] = "both",
         aspect_ratio: str = "16:9",
         duration_seconds: int = 8,
         model: str | None = None) -> dict

config(action: str, key: str | None = None, value: str | None = None) -> dict

help(topic: str = "understand") -> str

model (litellm provider/model format) selects the model directly for open passthrough -- there is no hardcoded model catalog (#461). For understand it is required unless the UNDERSTAND_MODELS env chain is set (no built-in default). For generate it overrides the GENERATE_MODELS chain and the provider's own minimal built-in default.

Model selection

No hardcoded model-ID catalog: understand is caller-driven only (explicit model= or the UNDERSTAND_MODELS chain; litellm passthrough, any provider). generate stays native per provider (Gemini / OpenAI / Grok) with a minimal built-in default per tier, overridable via model= or GENERATE_MODELS. Capability gaps: OpenAI has no video understanding or generation; Grok production has no video understanding.

Transport modes

Two transports, dispatched in src/imagine_mcp/__main__.py:41-64:

  • Default: stdio -- build_app().run(transport="stdio") on stdin/stdout (single-user, no daemon, no browser). Reads creds from env vars only; exits 1 if all three of GEMINI_API_KEY/OPENAI_API_KEY/XAI_API_KEY are missing. Universal MCP client compatibility.
  • Opt-in: http -- enabled by --http flag, MCP_TRANSPORT=http, or TRANSPORT_MODE=http. Runs run_http() -> mcp-core run_http_server (src/imagine_mcp/server.py:314,341), always multi-user / remote-style. Set PUBLIC_URL + MCP_DCR_SERVER_SECRET to bind publicly with per-JWT-sub credential isolation; otherwise serves on 127.0.0.1:<port> for local self-host. Credentials set via the browser form at /authorize.

Read the full file on GitHub · 213 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 9d ago First seen · 213 lines · 2,964 tokens per session scan A 89da91a579a0

Subscribe to this mod's changes

imagine-mcp CLAUDE.md is an instructions file published in the GitHub repository n24q02m/imagine-mcp (4 stars, last pushed today), licensed Apache-2.0. It adds 2,964 tokens to every session, about $0.0148 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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