Fastly MCP Server for LangChain 12 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect Fastly through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
async with MultiServerMCPClient({
"fastly": {
"transport": "streamable_http",
"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
}
}) as client:
tools = client.get_tools()
agent = create_react_agent(
ChatOpenAI(model="gpt-4o"),
tools,
)
response = await agent.ainvoke({
"messages": [{
"role": "user",
"content": "Using Fastly, show me what tools are available.",
}]
})
print(response["messages"][-1].content)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Fastly MCP Server
Connect your Fastly account to any AI agent and take full control of your edge cloud delivery and CDN configurations through natural conversation.
LangChain's ecosystem of 500+ components combines seamlessly with Fastly through native MCP adapters. Connect 12 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.
What you can do
- Service Orchestration — Identify bounded underlying Edge Cloud Delivery mappings and extract CDN service IDs aggregating global payload instances natively
- Version Management — Enumerate strictly immutable configuration drafts and promover promoted versions seamlessly to distribute instant security patches
- Live Traffic Auditing — Target specific configuration identities evaluating precise Active Version pointers to validate which architectural instance controls live traffic today
- Edge Deployment — Deploy drafted VCL or Compute@Edge logic instantly to production by promoting Promoted Drafts to Active states synchronously
- Cache Purging — Vaporize the complete Surrogate Cache storing static endpoints globally by issuing absolute HTTP PURGE instructions via chat
- Backend & Origin Control — Locate physical upstream Origins (AWS/GCP) mapped inside configurations and verify port constraints shielding original load-balancers
- Domain Auditing — Extract precise FQDN apex domains terminated at the Fastly Edge to manage routing configurations for specific headers flawlessly
The Fastly MCP Server exposes 12 tools through the Vinkius. Connect it to LangChain in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect Fastly to LangChain via MCP
Follow these steps to integrate the Fastly MCP Server with LangChain.
Install dependencies
Run pip install langchain langchain-mcp-adapters langgraph langchain-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save the code and run python agent.py
Explore tools
The agent discovers 12 tools from Fastly via MCP
Why Use LangChain with the Fastly MCP Server
LangChain provides unique advantages when paired with Fastly through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine Fastly MCP tools with 500+ LangChain components
Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step
LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging
Memory and conversation persistence let agents maintain context across Fastly queries for multi-turn workflows
Fastly + LangChain Use Cases
Practical scenarios where LangChain combined with the Fastly MCP Server delivers measurable value.
RAG with live data: combine Fastly tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query Fastly, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain Fastly tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every Fastly tool call, measure latency, and optimize your agent's performance
Fastly MCP Tools for LangChain (12)
These 12 tools become available when you connect Fastly to LangChain via MCP:
activate_service_version
Activate a specific configuration version for a service
create_service
Create a new Fastly service
delete_service
Delete a specific Fastly service
get_me
Get current API token identity info
get_service
Get details for a specific Fastly service
get_service_stats
Get usage statistics for a specific service
get_service_version
Get details for a specific service version
list_service_versions
List all configuration versions for a service
list_services
List all Fastly services
list_version_backends
List all backend origins for a specific service version
list_version_domains
List all domains for a specific service version
purge_all_cache
Purge all cached content for a specific service
Example Prompts for Fastly in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with Fastly immediately.
"List all active Fastly services"
"Activate version 15 for service 'Prod-Main-CDN'"
"Purge all cache for service '1a2b'"
Troubleshooting Fastly MCP Server with LangChain
Common issues when connecting Fastly to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersFastly + LangChain FAQ
Common questions about integrating Fastly MCP Server with LangChain.
How does LangChain connect to MCP servers?
langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.Which LangChain agent types work with MCP?
Can I trace MCP tool calls in LangSmith?
Connect Fastly with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Fastly to LangChain
Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.