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FastlyMCP

Fastly MCP brings the power of Fastly's API directly to your AI assistants through the Model Context Protocol (MCP).

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Fastly's API-First Approach

Fastly's API-first design philosophy means:

  • Everything is an API - Every feature available in the Fastly UI is accessible via API

  • Programmatic Control - Full control over services, configurations, and edge logic

  • Automation Ready - Support for CI/CD workflows and infrastructure as code

  • Real-time Changes - API changes propagate globally in seconds, not minutes or hours

What Can I Do With Fastly API?

Fastly's comprehensive API allows you to:

  • Manage CDN Services - Create, configure, and deploy content delivery services

  • Control Caching - Set up cache strategies and perform instant purges

  • Configure Security - Manage WAF, DDoS protection, and TLS certificates

  • Monitor Performance - Access real-time metrics and historical stats

  • Implement Edge Logic - Deploy custom VCL or Compute@Edge applications

  • Automate Workflows - Integrate with CI/CD pipelines and infrastructure tools

Your API Key Stays Safe!

The AI assistant never sees your Fastly API key. It talks to a local helper (FastlyMCP) which uses the key securely.

What You Can Ask Your AI

With Fastly MCP configured, you can ask your AI assistant questions like:

What You Want To Do

Example AI Request

List your services

"Show me all my Fastly services"

Get domain details

"What domains are configured for my e-commerce service?"

Purge cache

"Purge the cache for my product service"

Check traffic

"What's the traffic pattern for my main site over the last week?"

View configuration

"Show me the backend servers for my API service"

Check performance

"What's my current cache hit ratio?"

"What the traffic pattern my for services over the last week?"

"List all my Fastly services and their domains."

"Build an interactive preformance dashboard about my Fastly serivce."

Related MCP server: @fastly/mcp

Getting Started

Prerequisites

Connect Your AI Assistant

Configure your AI assistant with:

{
  "mcpServers": {
    "fastly": {
      "command": "node",
      "args": ["path/to/fastly-mcp.mjs"],
      "env": {
        "FASTLY_API_KEY": "your_fastly_api_key"
      }
    }
  }
}

Advanced Operation Examples

Task Goal

Example AI Request

Optimize service based on traffic

"Analyze the configuration for [service_id/name] and suggest optimizations based on its traffic profile, prioritizing low latency."

Configure for live video

"Configure [service_id/name] for optimal live video streaming following the best practices outlined in [link_to_guide_or_doc]."

Find config conflicts

"Identify potential configuration conflicts in [service_id/name] compared to standard e-commerce delivery patterns."

Optimize video chunk caching

"Optimize caching for [service_id/name] to handle 10-second video chunks efficiently, minimizing origin load."

Enhance WAF security

"Review the WAF rules for [service_id/name] and suggest stricter settings to mitigate potential SQL injection attacks."

Set up origin mTLS

"Set up Mutual TLS (mTLS) authentication between Fastly and the origin servers for [service_id/name]."

Implement A/B testing (Edge)

"Deploy a Compute@Edge function to [service_id/name] that performs A/B testing by routing 10% of users to backend [backend_name]."

Add dynamic image rewriting (VCL)

"Write and deploy VCL for [service_id/name] to dynamically rewrite image URLs based on the requesting device's user agent."

Troubleshoot 5xx errors

"Analyze logs for [service_id/name] from the past 24 hours to identify the root cause of the recent spike in 5xx errors."

Learn More

License

This project is licensed under the MIT License - see the LICENSE file for details.

Available Tools

2 tools
fastly_apiA

Make requests to the Fastly API. Allows accessing all endpoints of the Fastly API with custom paths, methods and parameters.

IMPORTANT USAGE NOTES FOR LLMs:

  1. When making multiple API calls, summarize the results between calls. The user doesn't see raw API responses.

  2. Base URL is automatically added - just provide the path (e.g. '/service').

  3. Authentication is handled automatically - no need to include API keys or know API keys.

  4. Common paths:

    • List services: GET /service

    • Get service details: GET /service/{service_id}

    • Get domains: GET /service/{service_id}/version/{version}/domain

    • Get backends: GET /service/{service_id}/version/{version}/backend

    • Purge cache: POST /service/{service_id}/purge_all

    • Get stats: GET /stats (with params: service_id, from, to)

  5. Always check status codes in responses. Status 200-299 indicates success.

  6. Include simple explanations of what you're doing and what the results mean before and after each API call.

Creating Fastly Compute@Edge Sites

To create a Compute@Edge site, you can use a combination of API calls and terminal commands. The API handles service creation and configuration, while terminal commands handle the local build and deployment process.

Follow these general steps:

  1. Create a new service using the API: POST /service with {"name": "My Site", "type": "wasm"}

  2. Initialize a local Compute project using the Fastly CLI

  3. Build the project using the appropriate build tools

  4. Deploy using the Fastly CLI with the service ID from step 1

COMMON PITFALLS TO AVOID:

  1. DO NOT use --name flag with fastly compute init (use interactive mode or -d -y flags instead)

  2. PowerShell requires semicolons (;) not ampersands (&&) for command chaining

  3. Fastly compute build creates the package archive AFTER you've built the Wasm binary

  4. Build is a TWO-STEP process: first compile to Wasm, then create the package archive

  5. Deploy command needs -d flag to avoid hanging on interactive prompts

  6. NEVER attempt to extract or use the user's API key directly - auth is handled by MCP

  7. To create a service from scratch, you must use API calls for configuration and CLI for local build

  8. Check current directory paths carefully before running commands

  9. Full URL paths aren't needed in API calls - just use the path portion (e.g. '/service')

See the full guide for detailed instructions on handling common errors and PowerShell-specific commands.

Inputs: path (required), method (required), body, params.

fastly_cliA

Execute Fastly CLI commands securely without exposing API keys.

This tool allows you to run Fastly CLI commands while the MCP server handles authentication automatically. The LLM never sees or needs to handle the API key directly.

USAGE EXAMPLES:

  1. Initialize a Compute project: fastly_cli('compute init --language javascript -d -y')

  2. Build a package: fastly_cli('compute build')

  3. Deploy a service: fastly_cli('compute deploy --service-id SERVICE_ID -d -y')

COMMON COMMANDS:

  • compute init: Initialize a new Compute project

  • compute build: Build a Compute package

  • compute deploy: Deploy a Compute package

  • compute publish: Build and deploy in one step

  • whoami: Check authentication status

SECURITY NOTE: Authentication is handled automatically. Never attempt to pass API keys in commands.

Inputs: command (required), working_directory.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

Loading tool schema changelog…

    TDQS

    A4.1/5.0

    Scored across 2 tools

    Disambiguation5/5

    The two tools have completely distinct purposes: fastly_api handles direct API calls for service management, configuration, and data retrieval, while fastly_cli executes CLI commands for local project development and deployment. There is no overlap in functionality, making it clear when to use each tool.

    Naming Consistency5/5

    Both tools follow a consistent naming pattern with the prefix 'fastly_' followed by a descriptive suffix (_api, _cli). This clear and uniform naming scheme makes it easy to identify the tool's purpose at a glance.

    Tool Count3/5

    With only 2 tools, the server feels thin for covering Fastly's comprehensive CDN and edge computing platform. While the tools cover API interactions and CLI operations, many domain-specific actions (e.g., cache management, analytics, configuration updates) are deferred to generic API calls, which may require more agent effort to construct properly.

    Completeness2/5

    The tool set is severely incomplete for the Fastly domain. While fastly_api provides generic API access, there are no dedicated tools for common operations like purging cache, managing domains/backends, or retrieving statistics—forcing agents to manually construct API paths. The CLI tool helps with Compute@Edge but doesn't cover other Fastly services, leaving significant gaps in coverage.

    Maintenance

    ActivityInactive
    ResponsivenessNo recent community issues

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