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AXE Fleet MCP Server

Exposes over 19,000 Apify Actors as MCP tools for web scraping, data extraction, and OSINT automation. It enables AI agents to dynamically discover and execute scrapers to collect structured data and crawl web content.

glama
Updated
Mar 14, 2026

AXE Fleet MCP Server

Proprietary MCP server for the AXE distributed AI fleet.

Forked from Apify MCP Server (MIT License) and customized for AXE fleet operations.

What This Does

Exposes 19,000+ Apify Actors (web scrapers, automation tools, data extractors) as MCP tools that any AXE fleet node can invoke. Agents can dynamically discover, inspect, and execute scrapers for:

  • OSINT & Intelligence — Google Maps, social media, SERP scraping
  • Web Content Extraction — RAG-ready content crawling for fleet knowledge base
  • Monitoring — Price tracking, change detection, competitive intelligence
  • Data Pipelines — Structured extraction from any website

AXE Modifications

ChangeDetails
Telemetry removedNo Sentry, no Segment analytics. Fleet handles its own observability via ops_centre.py
RebrandedServer identifies as axe-mcp-server / AXE Fleet MCP Server
Telemetry off by defaultDEFAULT_TELEMETRY_ENABLED = false
Skyfire payment removedDirect Apify token auth only
Fleet-readyDesigned to run on any AXE node (JL1-JL3, JLa, JLb)

Quick Start

As Claude Code MCP Server (stdio)

{
  "mcpServers": {
    "axe-actors": {
      "command": "node",
      "args": ["./dist/stdio.js", "--tools", "actors,docs,apify/rag-web-browser"],
      "env": {
        "APIFY_TOKEN": "apify_api_XXXXX"
      }
    }
  }
}

Using Apify's Hosted Endpoint (no local build needed)

{
  "mcpServers": {
    "axe-actors": {
      "url": "https://mcp.apify.com"
    }
  }
}

Build Locally

npm install
npm run build
node dist/stdio.js --tools actors,docs,apify/rag-web-browser

Architecture

src/
├── main.ts              — Express server entry (Apify Actor standby mode)
├── stdio.ts             — CLI/stdio transport entry (for MCP clients)
├── const.ts             — Server config, tool enums, cache settings
├── apify_client.ts      — Apify API client wrapper
├── mcp/
│   ├── server.ts        — Core MCP server (ActorsMcpServer class)
│   ├── actors.ts        — Actor definition loading
│   ├── client.ts        — MCP client for proxying
│   └── proxy.ts         — MCP server proxying
├── tools/
│   ├── common/          — Shared tool implementations (add-actor, search, datasets, KV stores)
│   ├── core/            — Core tool logic (actor execution, response handling)
│   ├── default/         — Default MCP tool wrappers
│   └── openai/          — OpenAI-compatible tool wrappers
├── utils/               — Helpers (auth, schema gen, caching, HTML processing)
├── resources/           — MCP resources (widgets)
├── prompts/             — Built-in prompt templates
└── web/                 — Web UI (React/Tailwind)

Key Tools

ToolPurpose
search-actorsSearch 19K+ Apify Actors by keyword
add-actorDynamically register an Actor as an MCP tool
call-actorExecute any Actor and get results
fetch-actor-detailsGet Actor specs, schema, pricing
get-actor-outputRetrieve full output from a completed run
get-dataset-itemsAccess stored dataset results
search-apify-docsSearch Apify/Crawlee documentation
apify/rag-web-browserBuilt-in web search + content extraction

Fleet Integration

This server can be deployed on any AXE node:

  • JL1 (Nova) — Primary host, M1 Max with Node 22+, build and run here
  • JL3 (Vigil) — Ops hub, coordinates scraping tasks via API
  • JLb (Reaper) — Existing scraping node, can offload to Apify for anti-bot handling

Vigil's autonomous RESEARCH cycles can use Apify Actors to gather intelligence during 4-hour deep-dive sessions.

Requirements

Upstream

Based on apify/apify-mcp-server v0.9.11. To pull upstream changes: git remote add upstream https://github.com/apify/apify-mcp-server.git && git fetch upstream

License

MIT (inherited from upstream)

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