runpod-image-mcp: Instructions file for Claude Code

CLAUDE.md

runpod-image-mcp CLAUDE.md is an instructions file for Claude Code from jashwanth0712/runpod-image-mcp. It costs 437 tokens per session, scanned A, original, MIT.

Repository instructions for a RunPod image-generation MCP server, covering setup, commands, testing, publishing, and its API flow. MCP is a standard way for AI assistants to call external tools.

In plain words
What is it for?
Setting up the Python environment with uv, running the local server, testing it, building releases, and working with RunPod image jobs.
Why use it?
It gives an AI coding agent the project-specific steps needed to install, run, test, and publish the server consistently.

Instructions file for Claude Code

Written for Claude Code: the file is CLAUDE.md. Also seen: mentions CLAUDE.md; mentions Claude Code.

This is jashwanth0712/runpod-image-mcp's own configuration. It tells Claude Code how to work on runpod-image-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 runpod-image-mcp configures →

Reuse

Borrowing it

Nothing to install: this file belongs to jashwanth0712/runpod-image-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/jashwanth0712/runpod-image-mcp/main/CLAUDE.md
Clone the repo
git clone --depth 1 https://github.com/jashwanth0712/runpod-image-mcp

Made for: Claude Code.

Wrote this? Show the measurements

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README.md
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Per session 437 This file is loaded in full into every session.
When invoked 437 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 $0.00437 $0.00437
Opus 5 $0.00218 $0.00218
Sonnet 5 $0.00087 $0.00087
Haiku 4.5 $0.00044 $0.00044

Measured 9d ago against content hash cb13d8e4188a, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

runpod-image-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 · 56 lines

What it actually says

CLAUDE.md

This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.

Environment Setup

# Use uv for package management
uv venv
source .venv/bin/activate

# Install in editable mode
uv pip install -e .

Running/Testing

# Run the server locally
RUNPOD_API_KEY=your_key uv run runpod-mcp-server

# Test (when implemented)
pytest

Publishing

uv build
uv publish

RunPod API Integration

Endpoint IDs (hardcoded in constants.py):

  • Seedream V4 T2I: seedream-v4-t2i
  • Nano Banana Pro Edit: nano-banana-pro-edit

Async Job Flow:

  1. Submit job to /v2/{endpoint_id}/run → get job_id
  2. Poll /v2/{endpoint_id}/status/{job_id} with exponential backoff (2s, 4s, 8s, then 15s intervals)
  3. Extract result URL from completed job output

Required Environment Variable:

Architecture

server.py: FastMCP server with 4 tools (generate_image, edit_image, check_job_status, get_api_info). All validation happens here before calling the client. Tools return user-friendly strings (✓/✗ prefixed), never raise exceptions.

runpod_client.py: Async HTTP client handling all RunPod API calls. Raises RuntimeError for API/network errors, TimeoutError for polling timeouts.

config.py: Pydantic settings loading RUNPOD_API_KEY from env vars or .env file (with RUNPOD_ prefix).

constants.py: API constraints (Seedream: 1024-4096px, Nano Banana: 1k/2k/4k resolutions), pricing, and reference info.

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 · 56 lines · 437 tokens per session scan A cb13d8e4188a

Subscribe to this mod's changes

runpod-image-mcp CLAUDE.md is an instructions file published in the GitHub repository jashwanth0712/runpod-image-mcp (0 stars, last pushed 7mo ago), licensed MIT. It adds 437 tokens to every session, about $0.0022 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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