The 5 Most Open SaaS Vendors for AI Agents (and the 5 Most Closed)

Every enterprise software buyer today must weigh a key new consideration when shopping for business tools. Can my AI agents work with it?

It’s no longer hypothetical. Organizations are deploying agents that take actions across business systems: updating CRM records, managing invoices, triaging support tickets, and orchestrating workflows across departments. The bottleneck isn’t the model. It’s whether the vendor on the other side of the integration will let the agent in.

MCP (Model Context Protocol) is the open standard that governs how agents connect to software. Created by Anthropic, open-sourced, and donated to the Linux Foundation, MCP gives any AI agent a single protocol for authenticating, reading, and writing to any business application. Think of it as the HTTP layer for agent-to-application communication.

But saying “we support MCP” is easy. Actually shipping a quality integration is harder. Vague tool definitions, missing schemas, and broken error handling can make an MCP server useless to agents even if it technically exists. Arcade.dev’s ToolBench scores every public MCP server on definition quality, protocol readiness, and real-world reliability. The rankings below reflect not just whether a vendor has an MCP server, but whether it’s built well enough for agents to depend on in production.

Which vendors are making their platforms accessible to AI agents, and which ones are keeping the doors locked?

The 5 Most Open SaaS Vendors

These companies are making it straightforward for AI agents to work with their platforms: open APIs, first-party MCP servers, and no proprietary gatekeeping.

1. GitHub

GitHub isn’t just hosting MCP servers in repositories. They’re actively building the infrastructure for agents to operate on the platform. GitHub ships a first-party MCP server and has embedded MCP support directly into Copilot, making it one of the earliest major platforms to treat agent connectivity as a core product capability. Their open APIs have made it possible for the broader MCP ecosystem to grow rapidly. Tools like Arcade’s ToolBench are built directly on top of GitHub’s publicly available data. They’ve become the foundation that the open ecosystem runs on.

2. Figma

Figma ships a first-party MCP server that works bidirectionally. AI agents can read a design file and generate production code, or take a live web page and push it back into Figma as editable layers. Beyond that, Figma’s APIs are open enough that teams can build custom MCP servers for workflows Figma hasn’t templated yet. That combination—a solid first-party server plus open APIs for custom builds—is what real openness looks like.

3. Linear

Linear’s MCP server is built on OAuth: authorize through your browser once and you’re connected. No API keys to manage. An AI agent can then create issues, update projects, and pull context from ongoing work. Linear’s APIs are also open, making it straightforward to build custom MCP servers for more specialized workflows. For engineering teams already running their day-to-day in Linear, this turns an AI assistant into a genuine productivity multiplier: triaging bugs, drafting tickets, keeping projects moving without anyone switching between tools.

4. Hugging Face

Hugging Face is the largest open community for AI models, datasets, and tools. What makes their MCP approach unique is that any application hosted on Hugging Face can become a tool that AI agents use with a single click. Thousands of community-built capabilities—from image editing to document scanning to text-to-speech—are accessible to any AI agent through a single connection. It’s an open app store for agent capabilities, and it’s growing fast.

5. Stripe

Stripe’s MCP server runs on OAuth, and any authorized AI agent can manage customers, products, payments, and invoicing. Like Figma and Linear, Stripe’s APIs are open enough that teams can build custom MCP servers for payment workflows beyond what Stripe has templated. In March 2026, Stripe went further with the Machine Payments Protocol (co-authored with Tempo): an open standard that lets AI agents make and receive payments autonomously. Stripe is going beyond simply reading payment data—they’re building the infrastructure for agents to transact.

The 5 Most Closed SaaS Vendors

These companies are making it harder—sometimes deliberately—for AI agents to work with their platforms. In a market where the direction is clear, they’re swimming upstream.

1. Slack

Slack should be one of the easiest places for an AI assistant to add value: summarizing threads, surfacing information, catching teams up on what they missed. Instead, Slack recently tightened API restrictions, severely limiting how quickly AI tools can access message history. They’ve launched a first-party MCP server, but the rate limits still apply. The door is technically open, but barely a crack. Meanwhile, platforms like LangChain and OpenClaw are building agent integrations into chat interfaces at speed. Slack is the one still blocking the path. Enterprise teams report that these restrictions are actively slowing down AI adoption inside their organizations.

2. Meta

Meta wants to be seen as the open-source AI leader, and their Llama models are freely available and widely used. But when it comes to their actual products, the picture is different.

WhatsApp doesn’t support MCP for personal accounts, and getting a business account approved is an extremely scrutinized process. Even once approved, the integration path is limited.

Meta’s advertising tools have no MCP path at all. Ad campaign management is exactly the kind of repetitive, data-heavy work agents are built for. Without a standard integration path, teams report resorting to browser automation tools with full account access just to manage ad spend. That’s not a solution. It’s a security risk born out of frustration.

The social network itself? Understandable that it stays locked, given the lessons of Cambridge Analytica. But paid business services don’t carry the same justification.

3. Workday

Workday manages payroll, benefits, and HR data for many of the world’s largest employers. That’s exactly the kind of system agents need access to for useful work: looking up PTO balances, processing expense reports, answering employee questions. But after acquiring the AI company Sana for a reported $1.1 billion, Workday channeled all AI agent access through its own proprietary system. Even where the open standard is technically supported, Workday controls the gateway. For companies trying to connect AI assistants across multiple business systems, Workday becomes a dead end.

4. LinkedIn

LinkedIn is locked down with no MCP path for AI agents. Some of this makes sense to protect the social network.

But the bigger missed opportunity is Sales Navigator. Companies pay significant money for this premium sales tool, and it already has built-in protections against misuse. An MCP integration would be valuable for teams that want agents to help track and manage lead generation. Sales teams would pay for that. It’s the kind of feature that could accelerate LinkedIn’s business, not threaten it.

5. Discord

Discord is where developer and gaming communities live. It’s where open-source projects coordinate, where AI researchers collaborate, and where startups run their support channels. But building an AI agent that works with Discord is still limited to basic bot tokens with narrow capabilities. There’s no MCP path and no modern way for AI agents to integrate natively. For a platform so central to the communities building the AI future, that’s a notable gap.

Why This Matters for the Enterprise

For enterprises evaluating their software stack, MCP openness is becoming a procurement consideration. The ability for AI agents to connect to a vendor’s platform directly affects time-to-value on agent initiatives, the cost and complexity of custom integration work, and whether a vendor becomes a bottleneck in your broader automation strategy.

The companies on the open list are betting that interoperability drives retention. The companies on the closed list are betting that control does. History suggests the open bet wins. The vendors that embraced open APIs in the cloud era became the platforms enterprises standardized on. The ones that locked down became the systems that enterprises migrated away from.

AI agents are the new integration layer. Software stacks will need to support AI agents to be effective—the only uncertainty is whether the vendors you’re paying today are ready to do just that.