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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.

Dashboard Image
Dashboard Image
Dashboard Image

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

Background

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.

Background

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.

Background

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.

Background

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.

Background

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.

Background

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.

Background

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.

Background

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.

Background

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.

Background

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.

Background

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.

Background

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.

Abstract
Abstract

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.

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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

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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

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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

Background Lines

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

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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

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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

Background Lines

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

Background Lines

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

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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

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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

Background Lines

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

Background Lines

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

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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

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Logo

Others

Multitenancy

Multitenancy

Built-in, true multitenancy

Built-in, true multitenancy

Each user manages own workflow

Each user manages own workflow

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White-labeling

White-labeling

Full brand control

Full brand control

Not always the case

Not always the case

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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

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SDK / Developer Tools

SDK / Developer Tools

SDKs & APIs available

SDKs & APIs available

Dev platform, but limited embedding

Dev platform, but limited embedding

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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

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Analytics & Monitoring

Analytics & Monitoring

Centralized observability

Centralized observability

Minimal usage insights

Minimal usage insights

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Versus Background
Versus Background
Logo

Others

Multitenancy

Built-in, true multitenancy

Each user manages own workflow

Background Lines

Each user manages own workflow

White-labeling

Full brand control

Not always the case

Background Lines

Scalability

Enterprise-ready , any number of apps under one commad layer

Scales poorly across tenants

Background Lines

SDK / Developer Tools

SDKs & APIs available

Dev platform, but limited embedding

Background Lines

Enterprise Flexibility


Dynamic schema adaptation with fallback strategies and mapping resolution

Rigid static schema mapping; fragile with dynamic data

Background Lines

Analytics & Monitoring

Centralized observability

Minimal usage insights

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Real-World Analogy

Real-World Analogy

Background
Background
Background

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.

Background
Background
Background

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

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.

Got any specific questions?

Got any specific questions?

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.

Copyright © 2024 Fastn, Inc.

fastn.ai

Copyright © 2025 Fastn, Inc.