OpenAPI and MCP-based agent creation
Create an agent by providing an OpenAPI specification or MCP server URL, with support for custom headers. This connects the agent to the product capabilities already exposed by the SaaS team.
A2A Net is an AI agent platform for B2B SaaS teams. It turns an existing OpenAPI specification or MCP server into a customer-facing agent that can perform multi-step workflows across a website, app, Slack, Teams/Copilot, and Gemini Enterprise.
A2A Net is an AI agent platform for B2B SaaS product and engineering teams. It creates customer-facing agents from an existing OpenAPI specification or MCP server, allowing customers to perform actions, analyze data, and complete complex multi-step workflows in the SaaS product.
The workflow covers agent creation, conversational testing, rubric-based session evaluation, and automated optimization. Teams can test prompts and tool calls in a staging environment before publishing an agent to a website, app, Slack, Teams/Copilot, or Gemini Enterprise. The platform also supports variables and secrets for customer-specific authentication data, file exchange, and protocol compatibility with AG-UI and A2A.
Create an agent by providing an OpenAPI specification or MCP server URL, with support for custom headers. This connects the agent to the product capabilities already exposed by the SaaS team.
Use the playground to test the agent with real conversations, define evaluation rubrics, and rate sessions against criteria such as task completion, communication quality, and correct tool or parameter use.
Use session ratings and an LLM-based judge to optimize the agent’s system instruction and prompt behavior for conversational workflows.
Test prompts and tool calls in staging without affecting production data, then publish the configured agent when it is ready.
Add variables and secrets to instructions and tools, send values as API request headers or set them during customer authentication, and use a customizable Python sandbox to write code, call tools, and create files.
Publish agents to a website, app, Slack, Teams/Copilot, and Gemini Enterprise. Agents can exchange images, PDFs, and spreadsheets, and can generate channel-native elements such as buttons, images, and tables.
A product team with an OpenAPI specification or MCP server can create an agent around its current APIs instead of designing a separate action layer for customer workflows.
An engineering or product team can hold conversations with the agent, identify failures, define rubrics, and test tool calls in staging before the agent reaches live product data.
A SaaS provider can expose actions and data analysis through a conversational agent so customers can complete complex workflows in the product rather than handling each step separately.
Once the agent is ready, a provider can publish it beyond its website or app to Slack, Teams/Copilot, or Gemini Enterprise, giving customers additional interaction channels.
Agents can receive or send images, PDFs, and spreadsheets, and can present supported results through interface elements such as buttons, images, and tables.
You can start with an OpenAPI specification or an MCP server URL and add custom headers. The agent is then connected to the capabilities exposed by those interfaces.
You can chat with an agent in the playground, define rubrics, rate sessions, and use those ratings with an LLM-based judge and optimization workflow to improve the agent. Staging is available for testing prompts and tool calls without affecting production data.
The site lists publishing to a website, app, Slack, Teams/Copilot, and Gemini Enterprise. It also states that agents are built to meet the requirements for publication to Slack, Microsoft, and Google marketplaces.
The site distinguishes A2A Net from platforms such as Intercom, Sierra, and Decagon by focusing on agents for B2B SaaS products. Its stated purpose is to let a product’s customers use the product’s APIs to take actions, analyze data, and complete multi-step workflows.
Yes. Agents can send and receive images, PDFs, and spreadsheets. Variables and secrets can be used in instructions and tools, sent as API request headers, or set per customer during authentication.
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