MCP 服务器

Apeiron

Unlimited web access MCP server for AI agents, enabling search, fetch, and learning across multiple sources while bypassing anti-bot protections.

README

<h1 align="center">Apeiron</h1>

<p align="center"> <b>Local-first web search, fetch, and extraction tools for AI agents.</b> </p>

Apeiron gives MCP-compatible agents and Python apps three practical tools:

apeiron_search: search web-oriented sources such as arXiv, Wikipedia, GitHub, and optional local SearXNG.
apeiron_fetch: fetch a URL and return LLM-ready content plus tier/verdict diagnostics.
apeiron_learn: remember the best working fetch strategy for a domain.

It is designed for Claude Code, OpenCode, Cursor, Cline, Windsurf, and local agent workflows where you want a free, inspectable web-access layer before reaching for paid scraping APIs.

Status

Works today:

CLI, Python API, and MCP server surfaces.
Fast HTTP fetch with curl_cffi when the fetch extra is installed.
arXiv, Wikipedia, and GitHub search.
Jina Reader fallback.
Local response cache and per-domain strategy cache.
Structured JSON output for CLI and MCP fetch/learn calls.
apeiron doctor diagnostics for optional dependencies and local services.

Experimental:

Browser tiers: Patchright, CloakBrowser, Camoufox, FlareSolverr, browser-use.
PDF/DOCX/PPTX/XLSX extraction through Markitdown.
YouTube transcript extraction through yt-dlp subtitle metadata.
Reddit search; it is not enabled by default because Reddit requires OAuth for reliable automated use.
Git-based shared learning; local git commits are opt-in with APEIRON_GIT_COMMIT=true.

Install

The PyPI name apeiron belongs to a different package. Until this project is published as apeiron-agent, use the GitHub install path.

From source

git clone https://github.com/insomnia-me/apeiron.git
cd apeiron
python3 -m venv .venv
source .venv/bin/activate
pip install -e ".[fetch,mcp,documents,media]"

One-command local install

curl -fsSL https://raw.githubusercontent.com/insomnia-me/apeiron/main/install.sh | bash

Set APEIRON_INSTALL_PROFILE=all before running the script if you also want browser automation dependencies.

Quickstart

apeiron doctor
apeiron fetch "https://example.com" --json
apeiron search "python web scraping" --sources wikipedia github arxiv --json
apeiron learn "https://example.com" --json

MCP server

Example OpenCode config:

{
  "mcp": {
    "servers": {
      "apeiron": {
        "command": "python",
        "args": ["-m", "apeiron.api.mcp_server"],
        "cwd": "/path/to/apeiron"
      }
    }
  }
}

MCP tools:

Tool	What it returns
`apeiron_search("query")`	JSON array of search hits
`apeiron_fetch("url")`	JSON object with content, tier, verdict, content type, title, elapsed time, and error
`apeiron_learn("url")`	JSON object with learned tier/verdict diagnostics

Python API

from apeiron import fetch_sync, search_sync

result = fetch_sync("https://example.com", cache_ttl=0)
print(result.verdict.value, result.tier.value)
print(result.content[:500])

hits = search_sync("agent web access", max_results=5)
for hit in hits:
    print(hit.source.value, hit.title, hit.url)

Architecture

APEIRON
  search
    arXiv, Wikipedia, GitHub, optional SearXNG
  fetch
    fast HTTP -> browser tiers -> reader fallback
  extract
    Trafilatura, Readability, Markitdown
  learn
    strategies.json, challenge heuristics, opt-in git commits
  api
    CLI, Python API, MCP server

Optional infrastructure

SearXNG and FlareSolverr run through Docker Compose:

bash scripts/start-infra.sh
bash scripts/stop-infra.sh

Docker is optional. Apeiron can run CLI, Python API, MCP, fast fetch, and direct API search without local Docker services.

Safety boundary

Apeiron is for fetching public URLs and converting public content into agent-friendly text. It does not authorize credential bypass, private data access, or ignoring site policies. See SECURITY.md.