Borrowing it
Nothing to install: this file belongs to smorand/mcp-instagram. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/smorand/mcp-instagram/main/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/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<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="Reviewed on agentmods" width="80" 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 5.1 | $0.00968 | $0.00968 |
| Opus 5.5 | $0.00387 | $0.00387 |
| Sonnet 5.5 | $0.00194 | $0.00194 |
| Haiku 4.5 | $0.00097 | $0.00097 |
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 1mo 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 — 72 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, MediaMetadata (all carry an optionaldescription= full post caption)src/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) - Captions: yt-dlp puts the full caption in
info["description"];titleis only"Video by <user>"/"Post by <user>". instaloader exposes it asPost.caption. Both go through_caption()(strip, blank becomes None) and land in thedescriptionfield. Never truncate it in the model; truncate only at display time (_CAPTION_DISPLAY_LIMIT, 500 chars) dl --jsonprints the raw model as JSON on stdout (logs stay on stderr) and forces quiet logging; it is the way for an agent to get the untruncated caption- Rich printing of user content uses
markup=False: a caption containing[...]would otherwise be swallowed as rich markup - 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.
- 1mo ago Changed · +3 lines · +173 tokens per session b1dd8a914e58
- 2mo 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 1mo ago), licensed MIT. It adds 968 tokens to every session, about $0.0039 per session on Opus 5.5. 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.
mcp-instagram AGENTS.md compared with instructions from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| mcp-instagram AGENTS.mdsmorand/mcp-instagram | Instructions file | 0 | 1mo ago | MIT | A | 968 | Codex, OpenCode |
| vscode buildNext.instructions.mdmicrosoft/vscode | Instructions file | 195k | today | MIT | A | 9,719 | GitHub Copilot |
| next.js AGENTS.mdvercel/next.js | Instructions file | 143k | today | MIT | A | 7,461 | Codex, OpenCode |
| vscode oss-third-party-notices.instructions.mdmicrosoft/vscode | Instructions file | 195k | today | MIT | A | 5,685 | GitHub Copilot |
| langchain AGENTS.mdlangchain-ai/langchain | Instructions file | 149k | yesterday | MIT | A | 4,680 | Codex, OpenCode |
| vscode copilot-instructions.mdmicrosoft/vscode | Instructions file | 195k | today | MIT | A | 3,093 | GitHub Copilot |
| vscode model-prompts.instructions.mdmicrosoft/vscode | Instructions file | 195k | today | MIT | A | 2,022 | GitHub Copilot |