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Apollo Mcp Server

Official
apollographql·vlatest·agents·MIT

Helps with MCP tools, server as part of orchestrating AI agents and multi-step workflows workflows.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add apollographql/skills --skill apollo-mcp-server -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

apollographql

Matched to the vendor's own GitHub organisation.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill failed 2 of 6 checks. A failure is not proof of bad intent; it means something in the code needs a human to look at it before you run it.

  • No undeclared network calls: failed

    Contacts 1 host that is neither well-known infrastructure nor declared in the skill's frontmatter: mcp.apollo.dev.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

    Hosts contacted

    mcp.apollo.devundeclared127.0.0.1local

    What it found

    • skills/apollo-mcp-server/SKILL.md:27contacts mcp.apollo.dev
      curl -sSL https://mcp.apollo.dev/download/nix/latest | sh
    • skills/apollo-mcp-server/SKILL.md:30contacts mcp.apollo.dev
      iwr 'https://mcp.apollo.dev/download/win/latest' | iex

  • No pipe-to-shell installers: failed

    Runs code fetched at install time in 2 places.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

    What it found

    • skills/apollo-mcp-server/SKILL.md:27remote script piped into a shell
      curl -sSL https://mcp.apollo.dev/download/nix/latest | sh
    • skills/apollo-mcp-server/SKILL.md:30PowerShell download-and-run
      iwr 'https://mcp.apollo.dev/download/win/latest' | iex

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • Pinned to a commit: passed

    Scanned apollographql/skills at 322da824b2.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
322da824b2
Manifest
skills/apollo-mcp-server/SKILL.md
Scanned
4 files, 1,237 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

The apollo-mcp-server skill provides a server component for managing and processing data within AI agent workflows. It enables efficient communication between agents and external systems, supporting real-time updates and scalable operations.

When to use it

  • When deploying an AI agent system that requires centralized data management and coordination.
  • For applications needing real-time interaction with backend services or databases.
  • In scenarios where multiple agents need to share or synchronize data efficiently.

Key capabilities

  • Real-time data synchronization between agents and external systems
  • Scalable server architecture for handling high volumes of agent interactions
  • Secure communication protocols for reliable data exchange

Example prompts

  • "Set up the Apollo MCP Server to handle real-time updates from multiple AI agents."
  • "Configure the server to synchronize agent logs with a central database."
  • "Ensure secure communication between the agent and the Apollo MCP Server using TLS."

Tips & gotchas

  • Ensure your environment meets the system requirements for running the server component.
  • Monitor performance regularly, as high traffic may require additional resources or scaling.