Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add instructions/smorand/mcp-instagram/agents-mdgit clone --depth 1 https://github.com/smorand/mcp-instagramWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/instructions/smorand/mcp-instagram/agents-md)<a href="https://agentmods.dev/instructions/smorand/mcp-instagram/agents-md"><img src="https://agentmods.dev/badge/instructions/smorand/mcp-instagram/agents-md.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00795 | $0.00795 |
| Opus 5 | $0.00398 | $0.00398 |
| Sonnet 5 | $0.00159 | $0.00159 |
| Haiku 4.5 | $0.00080 | $0.00080 |
Grade A, and why
mcp-instagram 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 4d 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.
How it starts
The opening of the file, as written. The whole thing — 69 lines — stays where its author put it; the contents beside it link to each section on GitHub.
mcp-instagram
Overview
MCP server for downloading Instagram content using yt-dlp. Exposes 4 tools:
download_video, download_audio, download_carousel, get_metadata.
Supports stdio and HTTP streamable transports.
download_carousel also handles single image posts (GraphImage): yt-dlp raises
"There is no video in this post", so image-only content (single or sidecar) is fetched
via instaloader metadata + httpx.
Tech Stack: Python 3.13, FastMCP, yt-dlp, Typer, Pydantic, OpenTelemetry
Key Commands
make sync # Install dependencies
make run ARGS='stdio' # Run in stdio mode
make run ARGS='http' # Run in HTTP mode
make run ARGS='skill' # Print CLI usage guide (for LLMs/agents, stdout only)
make check # Full quality gate (lint, format, typecheck, security, tests+coverage)
make docker-build # Build Docker image
Project Structure
src/mcp_instagram.py: CLI entry point + FastMCP server + tool registrations. Theskillcommand printsSKILL_TEXT(CLI usage guide) to stdout for agents; keep it in sync with thedlcommand options.src/downloader.py: InstagramDownloader service (wraps yt-dlp, async via to_thread)src/models.py: Pydantic models: DownloadResult, CarouselResult, MediaMetadatasrc/config.py: Settings via pydantic-settings (MCP_INSTAGRAM_ prefix)src/logging_config.py: Logging setup with rich + file outputsrc/tracing.py: OpenTelemetry tracing with JSONL export
Conventions
- Entry point binary:
mcp-instagram - All yt-dlp calls wrapped in
asyncio.to_thread(sync yt-dlp, async interface) - OTel spans named
instagram.<operation>(e.g.,instagram.download_video) - Logs to
mcp-instagram.log; traces tomcp-instagram-otel.log - Cookies: set
MCP_INSTAGRAM_COOKIES_FILEto Netscape cookies.txt path Settingsusesextra="ignore":.envholds unrelated keys (INSTAGRAM_USERNAME/PASSWORDforscripts/list-saved.py) and pydantic-settings would otherwise raiseextra_forbidden- Image extension comes from the HTTP
Content-Type, not the URL suffix (CDN serves JPEG on.heicpaths) - Expected yt-dlp failures (image posts in
_get_metadata_sync) are silenced via_QuietYdlLogger ffmpeg/ffproberesolved through_ffbin(absolute path viashutil.which, clearRuntimeErrorif missing)
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.
- 4d ago First seen · 69 lines · 795 tokens per session scan A 29d0965134e9
mcp-instagram AGENTS.md is an instructions file published in the GitHub repository smorand/mcp-instagram (0 stars, last pushed 27d ago), licensed MIT. It adds 795 tokens to every session, about $0.0040 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.
Other instructions, from other repositories
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
spec-kit AGENTS.md
AGENTS.md instructions for github/spec-kit, covering agents.md, about spec kit and specify, quickstart — add a new integration in 5 steps, integration architecture and integrationmanifest — file tracking.
codex AGENTS.md
AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
deepseek-harness AGENTS.md
AGENTS.md instructions for deepseek-ai/deepseek-harness, covering agents.md, pre-stable apis and released session data, repository layout, commands and host sandbox failures.