Connect every tool through MCP
Your agents reach the whole stack.
…and any other MCP server, API, or service you connect.
MCP server included
A workspace-scoped MCP endpoint exposes your agents, tasks, and projects to any MCP client, including Claude.ai.
- Workspace-scoped MCP endpoint out of the box
- Works with any MCP client, including Claude.ai
- Exposes your agents, tasks and projects
Tools your team uses
Slack, GitHub, Linear, Notion, databases, and your own APIs, reachable by every agent in the workspace.
- Slack, GitHub, Linear, Notion, Drive and more
- Your own internal APIs become agent tools
- Connect once, available to every agent
Scoped & safe
Each connection is scoped to a workspace and governed by the same budgets and approvals as everything else.
- Expose only the capabilities you choose
- Every call runs under budgets and approvals
- Full audit trail on every tool call
Plugs into the tools your team already uses
How integrations & mcp works
- 1
Connect a tool
Add an MCP server, API, or service to your workspace once.
- 2
Scope what it can do
Expose exactly the capabilities you want, and nothing more.
- 3
Every agent can use it
No per-agent wiring. The whole workforce reaches it instantly.
- 4
Calls stay governed
Each action runs under the same budgets, approvals, and audit trail.
See it in context
Close the loop in Slack
Before
Your agent produces a great answer, then a human has to copy it into Slack and tag the right channel.
With Padiso
The agent posts directly to the right Slack channel, threads the reply, and pings the owner, all on its own.
Act on your own data
Before
Agents can reason about your business but cannot touch the database where the real records live.
With Padiso
You expose a read-and-update tool over your DB as MCP, and agents work the records safely within scope.
What teams use it for
Connect your SaaS stack
Slack, GitHub, Linear, Notion, Google Drive, and more, reachable by every agent.
Expose internal APIs
Turn internal services into governed agent tools without building a bespoke integration each time.
Power external clients
The same MCP endpoint serves your dashboard, the CLI, and clients like Claude.ai.
The numbers behind agentic operations
You don't have to take our word for it. Here's what the analysts and operators are reporting right now.
real-time
DHL’s logistics agents monitor global shipments and autonomously reroute around delays and shortages.
trends → SKUs
Walmart’s multi-agent engine turns social and search trends into product concepts, compressing timelines.
40%
of enterprise apps will use task-specific AI agents by 2026, up from under 5% in 2025.
Most teams reach payback within a quarter or two of going live.
Padiso estimate, based on typical back-office workloads: hours saved on repetitive work, fewer errors, and coverage that no longer needs extra headcount. Your mileage depends on volume and the processes you automate first.
It already works at this scale
Not a demo. A team in the same kind of work, with results they published.
Klarna
Customer service
By Q3 2025, Klarna’s AI assistant was doing the workload of around 853 employees and driving an estimated $60M in savings, while keeping resolution times a fraction of human handling.
$60M
estimated savings
853
employees’ worth of work
2/3
of support chats
The strongest results come from scoped use cases with connected data and clear KPIs, and from keeping humans in the loop on the hard cases. That is exactly the model Padiso is built around.
1 click
to connect a tool to every agent
Add a tool once and your entire agent workforce can use it, safely and instantly.
Run your business on agents.
Start free, or talk to us about putting an agent workforce to work across your operations.