
Fastn MCP: Secure, Scalable,
Multi-Tenant Command Layer for AI Agents
Fastn MCP: Secure, Scalable,
Multi-Tenant Command Layer for AI Agents
Fastn MCP: Secure, Scalable,
Multi-Tenant Command Layer for AI Agents
Fastn MCP is a developer-first layer that abstracts away integration logic. It lets you control external systems (Slack, Teams, Gmail, etc.) through a unified, tenant-aware API designed for agents
Fastn MCP is a developer-first layer that abstracts away integration logic. It lets you control external systems (Slack, Teams, Gmail, etc.) through a unified, tenant-aware API designed for agents.




Go from AI commands to real-world actions
Fastn MCP connects your AI agent to apps like Slack, Shopify, Gmail, and more — without writing any integration logic. Just send a command, and Fastn routes it
Fastn MCP connects your AI agent to apps like Slack, Shopify, Gmail, and more — without writing any integration logic. Just send a command, and Fastn routes it
Unified Command Layer (UCL)
One API that connects to all your systems. You don’t need separate MCP servers for each app, a single endpoint connects them all. You can connect to any number of apps.
Unified Command Layer (UCL)
One API that connects to all your systems. You don’t need separate MCP servers for each app, a single endpoint connects them all. You can connect to any number of apps.
Unified Command Layer (UCL)
One API that connects to all your systems. You don’t need separate MCP servers for each app, a single endpoint connects them all. You can connect to any number of apps.
Unified Command Layer (UCL)
One API that connects to all your systems. You don’t need separate MCP servers for each app, a single endpoint connects them all. You can connect to any number of apps.
Built-in Multitenancy
Different customers. Different apps. One secure platform. With Fastn, each customer {tenant} gets their own secure space. It auto detects their apps and sends the same command to the right one.
Built-in Multitenancy
Different customers. Different apps. One secure platform. With Fastn, each customer {tenant} gets their own secure space. It auto detects their apps and sends the same command to the right one.
Built-in Multitenancy
Different customers. Different apps. One secure platform. With Fastn, each customer {tenant} gets their own secure space. It auto detects their apps and sends the same command to the right one.
Built-in Multitenancy
Different customers. Different apps. One secure platform. With Fastn, each customer {tenant} gets their own secure space. It auto detects their apps and sends the same command to the right one.
Agent-Ready, Built for Production, Not Just Demos
Easy to maintain. Built to scale. Fully observable. Track agent activity, debug with ease, and scale confidently as your workflows grow. Plug into LangGraph, CrewAI, AutoGen, and more.
Agent-Ready, Built for Production, Not Just Demos
Easy to maintain. Built to scale. Fully observable. Track agent activity, debug with ease, and scale confidently as your workflows grow. Plug into LangGraph, CrewAI, AutoGen, and more.
Agent-Ready, Built for Production, Not Just Demos
Easy to maintain. Built to scale. Fully observable. Track agent activity, debug with ease, and scale confidently as your workflows grow. Plug into LangGraph, CrewAI, AutoGen, and more.
Agent-Ready, Built for Production, Not Just Demos
Easy to maintain. Built to scale. Fully observable. Track agent activity, debug with ease, and scale confidently as your workflows grow. Plug into LangGraph, CrewAI, AutoGen, and more.
Where Traditional MCPs Fall Short
Where Traditional MCPs Fall Short
Despite their flexibility, existing MCP implementations weren't built for scale, security, or seamless developer experience:
Core Limitations:
Core Limitations:
Security
Scalability
Reliability
Observability
Enterprise Ready
No Auth or Access Control
Agents share static tokens and unrestricted memory — no isolation, no guardrails.
No Execution SandboxingI
Tools run with full access — no containment if something goes wrong.
Security
Scalability
Reliability
Observability
Enterprise Ready
No Auth or Access Control
Agents share static tokens and unrestricted memory — no isolation, no guardrails.
No Execution SandboxingI
Tools run with full access — no containment if something goes wrong.
Security
Scalability
Reliability
Observability
Enterprise Ready
No Auth or Access Control
Agents share static tokens and unrestricted memory — no isolation, no guardrails.
No Execution SandboxingI
Tools run with full access — no containment if something goes wrong.
Security
Scalability
Reliability
Observability
Enterprise Ready
No Auth or Access Control
Agents share static tokens and unrestricted memory — no isolation, no guardrails.
No Execution SandboxingI
Tools run with full access — no containment if something goes wrong.
How it works
How it works
How it works
Connect your Apps
Step 01
Choose your connectors – Select the apps you want to integrate.
Connect and authorize – Securely link your selected apps.
Define your actions – Specify what you want your AI to do.
Connect your Apps
Step 01
Choose your connectors – Select the apps you want to integrate.
Connect and authorize – Securely link your selected apps.
Define your actions – Specify what you want your AI to do.
Connect your Apps
Step 01
Choose your connectors – Select the apps you want to integrate.
Connect and authorize – Securely link your selected apps.
Define your actions – Specify what you want your AI to do.
Connect your Apps
Step 01
Choose your connectors – Select the apps you want to integrate.
Connect and authorize – Securely link your selected apps.
Define your actions – Specify what you want your AI to do.
Integrate MCP Server
Step 02
Live updates with SSE – Get real-time logs and status updates from your AI agent.
Command-line control – Call your MCP directly from your desktop.
AI-powered execution – Use Fastn’s AI agent to run commands seamlessly.
Integrate MCP Server
Step 02
Live updates with SSE – Get real-time logs and status updates from your AI agent.
Command-line control – Call your MCP directly from your desktop.
AI-powered execution – Use Fastn’s AI agent to run commands seamlessly.
Integrate MCP Server
Step 02
Live updates with SSE – Get real-time logs and status updates from your AI agent.
Command-line control – Call your MCP directly from your desktop.
AI-powered execution – Use Fastn’s AI agent to run commands seamlessly.
Integrate MCP Server
Step 02
Live updates with SSE – Get real-time logs and status updates from your AI agent.
Command-line control – Call your MCP directly from your desktop.
AI-powered execution – Use Fastn’s AI agent to run commands seamlessly.
Observe MCP Clients
Step 03
Natural language commands – Trigger AI actions with simple human-like instructions.
Track your requests – Monitor actions for better visibility.
Error insights – Understand why errors occur and how responses are structured.
Observe MCP Clients
Step 03
Natural language commands – Trigger AI actions with simple human-like instructions.
Track your requests – Monitor actions for better visibility.
Error insights – Understand why errors occur and how responses are structured.
Observe MCP Clients
Step 03
Natural language commands – Trigger AI actions with simple human-like instructions.
Track your requests – Monitor actions for better visibility.
Error insights – Understand why errors occur and how responses are structured.
Observe MCP Clients
Step 03
Natural language commands – Trigger AI actions with simple human-like instructions.
Track your requests – Monitor actions for better visibility.
Error insights – Understand why errors occur and how responses are structured.









Developer-First SDK
Developer-First SDK
Connect to our hosted endpoint and focus on building, not infrastructure.
Context-Aware Execution
Context-Aware Execution
Same command, different systems. Fastn automatically routes your commands to the right service based on tenant configuration.
Same command, different systems. Fastn automatically routes your commands to the right service based on tenant configuration.
Tenant 1 uses Slack? Command goes to Slack.
Tenant 1 uses Slack? Command goes to Slack.
Tenant 1 uses Slack? Command goes to Slack.
Tenant 1 uses Slack? Command goes to Slack.
Tenant 2 uses Microsoft Teams? Same command, different destination.
Tenant 2 uses Microsoft Teams? Same command, different destination.
Tenant 2 uses Microsoft Teams? Same command, different destination.
Tenant 2 uses Microsoft Teams? Same command, different destination.
No rewrites, no conditionals, no headaches.
No rewrites, no conditionals, no headaches.
No rewrites, no conditionals, no headaches.
No rewrites, no conditionals, no headaches.
from fastn import FastnClient client1 = FastnClient( api_key="your_api_key", space_id="your_space_id", tenant_id="tenant 1" ) response = client1.execute_action( prompt="Send an alert to the team 🚀" )
→ Add a new tenant with different tools? No code changes needed.
client2 = FastnClient( api_key="your_api_key", space_id="your_space_id", tenant_id="tenant 2" ) response = client2.execute_action( prompt="Send an alert to the team 🚀" )
client2 = FastnClient( api_key="your_api_key", space_id="your_space_id", tenant_id="tenant 2" ) response = client2.execute_action( prompt="Send an alert to the team 🚀" )
Built for Agentic Workflows
Built for Agentic Workflows
Fastn MCP integrates with leading agent frameworks and AI clients:
Introducing fastn UCL:
The Unified Command Layer
Introducing fastn UCL:
The Unified Command Layer
fastn UCL is our next-gen abstraction built on top of the fastn MCP foundation.
Unified Command Layer
One interface to command any system (Slack, Gmail, Snowflake, internal APIs, etc.)
Unified Command Layer
One interface to command any system (Slack, Gmail, Snowflake, internal APIs, etc.)
Unified Command Layer
One interface to command any system (Slack, Gmail, Snowflake, internal APIs, etc.)
Unified Command Layer
One interface to command any system (Slack, Gmail, Snowflake, internal APIs, etc.)
Enterprise Ready
Built-in auth, monitoring, observability and multi-tenant by design
Enterprise Ready
Built-in auth, monitoring, observability and multi-tenant by design
Enterprise Ready
Built-in auth, monitoring, observability and multi-tenant by design
Enterprise Ready
Built-in auth, monitoring, observability and multi-tenant by design
Resilient Infrastructure
Production-ready resilience with retries, timeouts, and batch processing
Resilient Infrastructure
Production-ready resilience with retries, timeouts, and batch processing
Resilient Infrastructure
Production-ready resilience with retries, timeouts, and batch processing
Resilient Infrastructure
Production-ready resilience with retries, timeouts, and batch processing
AI Optimized
Schema-flexible design works across dynamic enterprise data
AI Optimized
Schema-flexible design works across dynamic enterprise data
AI Optimized
Schema-flexible design works across dynamic enterprise data
AI Optimized
Schema-flexible design works across dynamic enterprise data
Zero Maintenance
Managed infrastructure — no need to host MCP servers locally
Zero Maintenance
Managed infrastructure — no need to host MCP servers locally
Zero Maintenance
Managed infrastructure — no need to host MCP servers locally
Zero Maintenance
Managed infrastructure — no need to host MCP servers locally
What is UCL?
What is UCL?
What is UCL?
What is UCL?
Why We Built UCL
Why We Built UCL
Why We Built UCL
Why We Built UCL
With fastn UCL, your AI product doesn't just talk to APIs — it speaks the same language, securely and at scale.
Functional Examples
Enterprise Ops
Project Manager
Task:
"Update the status to complete."
MCP knows what systems to update without explicit instructions:
Updates the Asana card
Closes the related GitHub issue
Updates the status to 'Done' in Airtable
Enterprise Ops
Project Manager
Task:
"Update the status to complete."
MCP knows what systems to update without explicit instructions:
Updates the Asana card
Closes the related GitHub issue
Updates the status to 'Done' in Airtable
Enterprise Ops
Project Manager
Task:
"Update the status to complete."
MCP knows what systems to update without explicit instructions:
Updates the Asana card
Closes the related GitHub issue
Updates the status to 'Done' in Airtable
Enterprise Ops
Project Manager
Task:
"Update the status to complete."
MCP knows what systems to update without explicit instructions:
Updates the Asana card
Closes the related GitHub issue
Updates the status to 'Done' in Airtable
Finance & Procurement
Finance Approver
Task:
"Approve this purchase."
MCP knows the right approval paths by context:
Routes hardware purchases through Coupa
Logs software approvals in Jira Service Desk
Notifies Procurement team in Slack
Triggers Okta provisioning when needed
Finance & Procurement
Finance Approver
Task:
"Approve this purchase."
MCP knows the right approval paths by context:
Routes hardware purchases through Coupa
Logs software approvals in Jira Service Desk
Notifies Procurement team in Slack
Triggers Okta provisioning when needed
Finance & Procurement
Finance Approver
Task:
"Approve this purchase."
MCP knows the right approval paths by context:
Routes hardware purchases through Coupa
Logs software approvals in Jira Service Desk
Notifies Procurement team in Slack
Triggers Okta provisioning when needed
Finance & Procurement
Finance Approver
Task:
"Approve this purchase."
MCP knows the right approval paths by context:
Routes hardware purchases through Coupa
Logs software approvals in Jira Service Desk
Notifies Procurement team in Slack
Triggers Okta provisioning when needed
HR & IT
IT Manager
Task:
"Update the status to complete."
MCP knows the right approval paths by context:
Deactivates accounts in Okta
Closes IT tickets in Jira
Notifies HR via Workday
Schedules exit interview in Calendly
HR & IT
IT Manager
Task:
"Update the status to complete."
MCP knows the right approval paths by context:
Deactivates accounts in Okta
Closes IT tickets in Jira
Notifies HR via Workday
Schedules exit interview in Calendly
HR & IT
IT Manager
Task:
"Update the status to complete."
MCP knows the right approval paths by context:
Deactivates accounts in Okta
Closes IT tickets in Jira
Notifies HR via Workday
Schedules exit interview in Calendly
HR & IT
IT Manager
Task:
"Update the status to complete."
MCP knows the right approval paths by context:
Deactivates accounts in Okta
Closes IT tickets in Jira
Notifies HR via Workday
Schedules exit interview in Calendly
Fastn.ai vs Traditional Solutions
Fastn.ai vs Traditional Solutions
How Fastn.ai compares to traditional solutions like Others
How Fastn.ai compares to traditional solutions like Others


Others
Multitenancy
Multitenancy
Built-in, true multitenancy
Built-in, true multitenancy
Each user manages own workflow
Each user manages own workflow
White-labeling
White-labeling
Full brand control
Full brand control
Not always the case
Not always the case
Scalability
Scalability
Enterprise-ready , any number of apps under one commad layer
Enterprise-ready , any number of apps under one commad layer
Scales poorly across tenants
Scales poorly across tenants
SDK / Developer Tools
SDK / Developer Tools
SDKs & APIs available
SDKs & APIs available
Dev platform, but limited embedding
Dev platform, but limited embedding
Enterprise Flexibility |
Dynamic schema adaptation with fallback strategies and mapping resolution
Dynamic schema adaptation with fallback strategies and mapping resolution
Rigid static schema mapping; fragile with dynamic data
Rigid static schema mapping; fragile with dynamic data
Analytics & Monitoring
Analytics & Monitoring
Centralized observability
Centralized observability
Minimal usage insights
Minimal usage insights

Others
Multitenancy
Built-in, true multitenancy
Each user manages own workflow
Each user manages own workflow
White-labeling
Full brand control
Not always the case
Scalability
Enterprise-ready , any number of apps under one commad layer
Scales poorly across tenants
SDK / Developer Tools
SDKs & APIs available
Dev platform, but limited embedding
Enterprise Flexibility |
Dynamic schema adaptation with fallback strategies and mapping resolution
Rigid static schema mapping; fragile with dynamic data
Analytics & Monitoring
Centralized observability
Minimal usage insights
Real-World Analogy
Real-World Analogy
You say: "Send this to the team."
Email us here
Fastn knows:
This tenant uses Teams → it sends it to Teams
Another tenant uses Slack → message goes to Slack
You don't write if-statements. You just issue commands.
You say: "Fetch yesterday’s orders."
Email us here
Fastn knows:
Customer A runs on Shopify
Customer B uses Magento
Customer C has a custom-built order system
No branching logic. Just plug in Fastn.
Key Benefits
Key Benefits
Streamlined commands, not integration code
Universal access to every tool in your ecosystem
Your central command center for agent operations
Instant execution from instruction to action
Streamlined commands, not integration code
Universal access to every tool in your ecosystem
Your central command center for agent operations
Instant execution from instruction to action
Streamlined commands, not integration code
Universal access to every tool in your ecosystem
Your central command center for agent operations
Instant execution from instruction to action
Streamlined commands, not integration code
Universal access to every tool in your ecosystem
Your central command center for agent operations
Instant execution from instruction to action
Streamlined commands, not integration code
Universal access to every tool in your ecosystem
Your central command center for agent operations
Instant execution from instruction to action
Streamlined commands, not integration code
Universal access to every tool in your ecosystem
Your central command center for agent operations
Instant execution from instruction to action
Streamlined commands, not integration code
Universal access to every tool in your ecosystem
Your central command center for agent operations
Instant execution from instruction to action
Streamlined commands, not integration code
Universal access to every tool in your ecosystem
Your central command center for agent operations
Instant execution from instruction to action
FAQ
FAQ
FAQ
FAQ
Common Questions & Answers
Common Questions & Answers
Here’s everything you need to know about MCP, from features to getting started.
Here’s everything you need to know about MCP, from features to getting started.
What is UCL?
What is UCL (Unified Command Layer)? UCL stands for Unified Command Layer — it’s a core feature of Fastn that allows AI agents to talk to any app or tool through one standard interface, instead of writing separate logic for each integration.
What is MCP?
Is MCP secure?
How much does Fastn MCP cost?
Can I use Fastn MCP with any AI platform?
How fast can I get started?
Do I need to host my own MCP server?
Does Fastn provide SDKs or client libraries?
Can I test my tools before going live?
How does Fastn handle retries and timeouts?
Is there logging or observability for debugging?
Can I build custom tools on Fastn?
Can I control where my data is stored?
How do I support multiple tenants in my app?
Do I need to change my existing APIs to work with Fastn?
Can I connect to multiple MCP endpoints?
Can I simulate agent calls in development?
Does Fastn support streaming (SSE/Webhooks)?
How does the agent know which tool to call?
What types of tools can I register in Fastn?
What if a tool fails during execution?
Can I group tools by use case or app?
Can I control which agent can access which tools?
Can I disable or pause a tool without deleting it?
Can I track usage per agent or tool?
What is UCL?
What is UCL (Unified Command Layer)? UCL stands for Unified Command Layer — it’s a core feature of Fastn that allows AI agents to talk to any app or tool through one standard interface, instead of writing separate logic for each integration.
What is MCP?
Is MCP secure?
How much does Fastn MCP cost?
Can I use Fastn MCP with any AI platform?
How fast can I get started?
Do I need to host my own MCP server?
Does Fastn provide SDKs or client libraries?
Can I test my tools before going live?
How does Fastn handle retries and timeouts?
Is there logging or observability for debugging?
Can I build custom tools on Fastn?
Can I control where my data is stored?
How do I support multiple tenants in my app?
Do I need to change my existing APIs to work with Fastn?
Can I connect to multiple MCP endpoints?
Can I simulate agent calls in development?
Does Fastn support streaming (SSE/Webhooks)?
How does the agent know which tool to call?
What types of tools can I register in Fastn?
What if a tool fails during execution?
Can I group tools by use case or app?
Can I control which agent can access which tools?
Can I disable or pause a tool without deleting it?
Can I track usage per agent or tool?
What is UCL?
What is UCL (Unified Command Layer)? UCL stands for Unified Command Layer — it’s a core feature of Fastn that allows AI agents to talk to any app or tool through one standard interface, instead of writing separate logic for each integration.
What is MCP?
Is MCP secure?
How much does Fastn MCP cost?
Can I use Fastn MCP with any AI platform?
How fast can I get started?
Do I need to host my own MCP server?
Does Fastn provide SDKs or client libraries?
Can I test my tools before going live?
How does Fastn handle retries and timeouts?
Is there logging or observability for debugging?
Can I build custom tools on Fastn?
Can I control where my data is stored?
How do I support multiple tenants in my app?
Do I need to change my existing APIs to work with Fastn?
Can I connect to multiple MCP endpoints?
Can I simulate agent calls in development?
Does Fastn support streaming (SSE/Webhooks)?
How does the agent know which tool to call?
What types of tools can I register in Fastn?
What if a tool fails during execution?
Can I group tools by use case or app?
Can I control which agent can access which tools?
Can I disable or pause a tool without deleting it?
Can I track usage per agent or tool?
What is UCL?
What is UCL (Unified Command Layer)? UCL stands for Unified Command Layer — it’s a core feature of Fastn that allows AI agents to talk to any app or tool through one standard interface, instead of writing separate logic for each integration.
What is MCP?
Is MCP secure?
How much does Fastn MCP cost?
Can I use Fastn MCP with any AI platform?
How fast can I get started?
Do I need to host my own MCP server?
Does Fastn provide SDKs or client libraries?
Can I test my tools before going live?
How does Fastn handle retries and timeouts?
Is there logging or observability for debugging?
Can I build custom tools on Fastn?
Can I control where my data is stored?
How do I support multiple tenants in my app?
Do I need to change my existing APIs to work with Fastn?
Can I connect to multiple MCP endpoints?
Can I simulate agent calls in development?
Does Fastn support streaming (SSE/Webhooks)?
How does the agent know which tool to call?
What types of tools can I register in Fastn?
What if a tool fails during execution?
Can I group tools by use case or app?
Can I control which agent can access which tools?
Can I disable or pause a tool without deleting it?
Can I track usage per agent or tool?
Unlock your potential with Fastn MCP.
Unlock your potential with Fastn MCP.
Launch your first AI assistant to boost efficiency.
fastn.ai
Copyright © 2025 Fastn, Inc.
fastn.ai
Copyright © 2025 Fastn, Inc.
Copyright © 2024 Fastn, Inc.
Copyright © 2024 Fastn, Inc.