Borrowing it
Nothing to install: this file belongs to alexyangjie/mcp-server-multi-fetch. 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/alexyangjie/mcp-server-multi-fetch/main/AGENTS.mdgit clone --depth 1 https://github.com/alexyangjie/mcp-server-multi-fetchWrote 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/alexyangjie/mcp-server-multi-fetch/agents-md)<a href="https://agentmods.dev/instructions/alexyangjie/mcp-server-multi-fetch/agents-md"><img src="https://agentmods.dev/badge/instructions/alexyangjie/mcp-server-multi-fetch/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/alexyangjie/mcp-server-multi-fetch/agents-md"><img src="https://agentmods.dev/badge/instructions/alexyangjie/mcp-server-multi-fetch/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 | $0.00863 | $0.00863 |
| Opus 5 | $0.00432 | $0.00432 |
| Sonnet 5 | $0.00173 | $0.00173 |
| Haiku 4.5 | $0.00086 | $0.00086 |
Grade A, and why
mcp-server-multi-fetch 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- mcp-server-multi-fetch CLAUDE.md — 97% identical, 2 lines differ
What it actually says
Codex
Project Overview
- Name: mcp-server-multi-fetch
- Description: A Model Context Protocol (MCP) server providing tools to fetch and convert web content for usage by LLMs.
- License: MIT
Repository Structure
LICENSE # MIT License
pyproject.toml # PEP 621 project metadata and dependencies
uv.lock # Locked dependencies for uv dev environment
README.md # User guide and configuration examples
src/
mcp_server_multi_fetch/
__init__.py # CLI entrypoint (main, serve)
__main__.py # Module entry for `python -m mcp_server_fetch`
server.py # Core server logic: tool & prompt registration, HTTP fetching, HTML-to-Markdown conversion
Build & Packaging
- Build backend: hatchling (
[build-system]in pyproject.toml) - Dev dependencies managed with
uvand locked inuv.lock(e.g.,pyright,ruff) - Docker build: multi-stage, uses
ghcr.io/astral-sh/uv, then Python 3.12-slim - Entry point in container:
mcp-server-multi-fetch
Dependencies & Frameworks
- Python ≥3.10 (3.12 in Docker)
- Async HTTP client:
httpx - HTML simplification:
readabilipy(Readability) - Markdown conversion:
markdownify - Robots.txt parsing:
protego - JSON schemas & validation:
pydanticv2 - MCP integration:
mcplibrary (mcp.server,mcp.types,mcp.shared.exceptions) - CLI & concurrency:
argparse,asyncio - Linting & type checking (dev):
ruff,pyright
Core Components
- CLI (
src/mcp_server_fetch/__init__.py):- Parses flags:
--user-agent,--ignore-robots-txt,--proxy-url - Calls
serve()(async)
- Parses flags:
- Server (
src/mcp_server_fetch/server.py):- Registers MCP tools & prompts:
- Tool:
fetch(Pydantic modelFetch) - Prompt:
fetch - Tool:
fetch_multi(Pydantic modelFetchMulti) - Prompt:
fetch_multi - Tool:
search(Pydantic modelSearch) - Prompt:
search - Implements:
check_may_autonomously_fetch_url(): respects robots.txt or raisesMcpErrorfetch_url(): HTTP GET, error handling, choose raw vs. markdown- Tool handler (
call_tool): enforce schema, fetch content in chunks - Prompt handler (
get_prompt): user-initiated fetch
- Runs via STDIO server:
mcp.server.stdio.stdio_server
Usage
- CLI:
mcp-server-multi-fetch [--user-agent UA] [--ignore-robots-txt] [--proxy-url PROXY_URL] - Python module:
python -m mcp_server_multi_fetch - UVX:
uvx mcp-server-multi-fetch
Development Workflow
- Install dependencies:
uv sync(dev+prod), orpip install . - Lint:
ruff src/ - Type check:
pyright
Notable Conventions & Tips
- HTTP timeouts: 30s
- Default persona User-Agent vs. Autonomous UA
- Chunked fetching via
max_length(default 50000) andstart_index McpErrorused for controlled error signaling over MCP wire- No unit tests included (add as needed)
For the AI Assistant
Refer to this file when:
- Exploring or modifying the server logic (
server.py) - Updating CLI flags or tooling configuration
- Adjusting dependency versions or build settings
- Understanding request-handling flow and error semantics
Keep this codex up-to-date with any structural or conceptual 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.
- 8d ago First seen · 82 lines · 863 tokens per session scan A b30f1599eb70
mcp-server-multi-fetch AGENTS.md is an instructions file published in the GitHub repository alexyangjie/mcp-server-multi-fetch (1 stars, last pushed 1y ago), licensed MIT. It adds 863 tokens to every session, about $0.0043 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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