openai-vision-mcp-server: Instructions file for Codex

AGENTS.md

openai-vision-mcp-server AGENTS.md is an instructions file for Codex, OpenCode from ygq-future/openai-vision-mcp-server. It costs 850 tokens per session, scanned A, original, MIT.

Repository instructions for `openai-vision-mcp-server`, a local server that accepts images from file paths, web URLs, or Base64 text and sends them to an OpenAI Chat Completions-compatible vision service for analysis.

In plain words
What is it for?
Use them when building or modifying this TypeScript MCP server, its npm executable, configuration, image handling, diagnostics, tests, or documentation.
Why use it?
They fix the project’s supported interface and runtime choices, while keeping credentials and image data out of logs. They also define how the server should communicate over standard input and output.

Instructions file for CodexOpenCode

Written for Codex and OpenCode: the file is AGENTS.md.

This is ygq-future/openai-vision-mcp-server's own configuration. It tells Codex and OpenCode how to work on openai-vision-mcp-server 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 openai-vision-mcp-server configures →

Reuse

Borrowing it

Nothing to install: this file belongs to ygq-future/openai-vision-mcp-server. 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/ygq-future/openai-vision-mcp-server/main/AGENTS.md
Clone the repo
git clone --depth 1 https://github.com/ygq-future/openai-vision-mcp-server

Made for: Codex, OpenCode.

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Per session 850 This file is loaded in full into every session.
When invoked 850 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 $0.00850 $0.00850
Opus 5 $0.00425 $0.00425
Sonnet 5 $0.00170 $0.00170
Haiku 4.5 $0.00085 $0.00085

Measured 8d ago against content hash 4f5deaf02ad6, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

openai-vision-mcp-server AGENTS.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 8d 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.

AGENTS.md · 71 lines

How it starts

The opening of the file, as written. The whole thing — 71 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Repository Instructions

Project purpose

Build openai-vision-mcp-server, a local stdio MCP server that accepts images from file:// URIs, HTTP(S) URLs, or Base64, preprocesses them, and analyzes them through an OpenAI Chat Completions-compatible vision endpoint.

Fixed product decisions

  • Support only the OpenAI Chat Completions-compatible request and response format.
  • Do not add Anthropic support, provider switching, a provider interface, or a generic adapter layer.
  • Run as a local stdio MCP server and publish an executable npm package for npx usage.
  • Read provider configuration only from the MCP client's per-server environment variables.
  • Keep stdout exclusively for MCP JSON-RPC messages. Send diagnostics to stderr and never log credentials or Base64 payloads.
  • Store project documentation and plans under docs/. This directory is intentionally ignored by Git.

Runtime and package management

  • Use TypeScript with strict type checking and ESM output.
  • Support Node.js 20.19.0 or newer.
  • Use Bun for dependency installation, scripts, tests, packing, and publishing.
  • Commit bun.lock; do not generate npm, pnpm, or Yarn lockfiles.
  • Prefer Node.js built-ins and native fetch. Do not add the OpenAI SDK unless a future requirement cannot be met by the fixed Chat Completions HTTP contract.

Required formatting

Prettier must use exactly:

{
  "singleQuote": true,
  "semi": false,
  "trailingComma": "all",
  "printWidth": 120,
  "tabWidth": 2,
  "arrowParens": "avoid",
  "endOfLine": "lf",
  "bracketSpacing": true,
  "bracketSameLine": true
}

Use ESLint flat configuration with type-aware TypeScript rules. Do not disable a rule inline unless the comment explains the concrete reason.

Architecture constraints

  • Keep image acquisition, validation, normalization, tiling, API calls, aggregation, and MCP transport in separate focused modules.
  • Decode each source once. Generate the overview and detail tiles from the decoded original, never from an already compressed derivative.
  • Do not claim to know semantic content before the first vision call. Overview planning may propose regions; uncertain results must fall back to deterministic overlapping grid coverage.
  • Treat maxTiles as a hard per-call ceiling on detail tiles. The overview does not count toward it.
  • Preserve tile and batch order explicitly. Never rely on promise completion order.
  • When a budget prevents complete coverage, return complete: false with a machine-readable warning; never silently imply complete analysis.
  • Apply configured allowed-root and SSRF policies on every local-file or remote fetch. The current defaults are permissive; documentation must explain how users opt into root restrictions and public-network-only URL access. Redirect limits, timeouts, byte limits, and decoded-pixel limits always remain enforced.

Read the full file on GitHub · 71 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. 8d ago First seen · 71 lines · 850 tokens per session scan A 4f5deaf02ad6

Subscribe to this mod's changes

openai-vision-mcp-server AGENTS.md is an instructions file published in the GitHub repository ygq-future/openai-vision-mcp-server (2 stars, last pushed 14d ago), licensed MIT. It adds 850 tokens to every session, about $0.0042 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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